OpenVerse Wiki - User contributions [en]

Virtual Worlds Association SRIA

2026-09-07T12:55:59Z

CollectiveIntelligenceAdmin: Reviewed, checked for factual issues in the summary, fixed links.

=== Virtual Worlds Association Strategic Research & Innovation Agenda (June 2025) ===

<blockquote>'''AI Acknowledgement''' The content has been provided by the Virtual and Augmented Reality Industrial Coalition. The content has been summarised using AI technologies, and validated by a human author.</blockquote>

The '''Virtual Worlds Strategic Research & Innovation Agenda (SRIA) 2025''' defines a comprehensive, human-centric trajectory for Europe's immersive technology ecosystem. It outlines key applications across seven vertical sectors, identifies six technical and five socio-economic challenge domains, and provides a multi-horizon scientific roadmap to establish European strategic autonomy, technological leadership, and digital sovereignty.

Aligned with the European Commission’s ''Web 4.0 and Virtual Worlds'' strategy, the agenda establishes a values-driven framework where privacy, inclusivity, transparency, and accessibility are embedded directly into hardware and software design.

==== 1.1 Basic Identification ====
* '''Full SRIDA/SRIA Title & Version:''' ''Strategic Research & Innovation Agenda: Solving Real World Problems'' (v1.0, June 2025)
* '''Publication / Last Update Date:''' June 2025
* '''Editors:''' Theo Papadopoulos (Siemens), Matthieu Worm (Siemens)
* '''Website / Source:''' https://www.virtualworldsassociation.eu/actions/strategic-research-innovation-agenda-virtual-worlds-eu

==== 1.2 Objectives and strategic outline ====
===== Vision Statement =====
To establish a human-centric European Virtual Worlds ecosystem that seamlessly blends physical and digital realities to solve real-world problems. Consumers experience unparalleled engagement and personalisation; workers benefit from enhanced, cross-border collaboration with Digital Twins; and public services are streamlined for accessibility, efficiency, and social inclusion. This pursuit of digital strategic autonomy ensures that European values of privacy, transparency, and inclusivity are embedded by design, preventing reliance on external actors and fostering an open, ethically sound digital future.

===== Core Mission / Objectives (6 Key Missions) =====
# '''Solving Real-World Problems:''' Drive the practical deployment of Virtual Worlds (VW) across industry, healthcare, education, arts, public administration, and security.
# '''Achieving Technological Autonomy:''' Mitigate dependency on non-European providers by developing core European components across the full XR value chain (processors, optics, software).
# '''Native Accessibility and Inclusion:''' Guarantee universal access to VW for people of all abilities, cultures, and languages, actively bridging the digital divide.
# '''Ethics, Safety, and Trust by Design:''' Establish robust frameworks for privacy-preserving sensing, explainable AI (XAI), and child-safe virtual spaces.
# '''Interoperable Standards and Portability:''' Drive global standardization for avatar portability, digital asset ownership, and secure decentralized data sharing.
# '''Co-Creation and Capacity Building:''' Empower European creators, SMEs, and researchers through multidisciplinary training, collaborative platforms, and open-source toolkits.

===== Policy Alignment =====
* '''European Commission Web 4.0 and Virtual Worlds Strategy (July 2023):''' Core strategic framework driving industrial ecosystems, public sector applications (CitiVerse, Local Digital Twins), and global governance.
* '''Horizon Europe Cluster 4 (Digital, Industry and Space):''' Anchor funding programme, supporting initiatives like GenAI4EU and Core Technologies for Virtual Worlds.
* '''Digital Decade Policy Programme 2030:''' Aligned with European targets for advanced digital skills, secure infrastructures, digital public services, and business transition.
* '''European Legislative Framework:''' Strictly aligned with the General Data Protection Regulation (GDPR), Artificial Intelligence Act (AI Act), Data Act, Data Governance Act, Digital Services Act (DSA), and Digital Markets Act (DMA).
* '''The European Green Deal:''' Leveraging VW to optimize logistics, reduce material prototyping waste, and foster ecological awareness.

==== 1.3 Technological & Thematic Priorities ====
The Virtual Worlds SRIA structures its research and innovation actions across three main thematic pillars, supported by context-enabling disciplines:

{| class="wikitable" style="width:100%;"
|-
! style="background:#f2f2f2; width:25%;" | Pillar
! style="background:#f2f2f2; width:35%;" | Domain / Chapter
! style="background:#f2f2f2; width:40%;" | Key Research and Innovation Objectives
|-
| rowspan="7" | '''Pillar 1: Applications in Key Sectors'''
| '''1a. Industry & Logistics'''
| Standardized Digital Twins (DT); rapid prototyping with collaborative design; Virtual Factory Integration; intralogistics fleet management; collaborative remote maintenance.
|-
| '''1b. Healthcare & Well-being'''
| Personalized clinical care with Patient DTs; European Virtual Human Twin; real-time intraoperative surgical assistance; XR-supported rehabilitation; special education therapies.
|-
| '''1c. Media & Entertainment'''
| AI-driven virtual production; real-time volumetric media and avatar presence; Open XR stage tracking; immersive interactive events; secure, decentralized media licensing.
|-
| '''1d. Arts & Culture'''
| User-centred museum XR experiences; performing arts in virtual spaces; digital archiving of cultural events; virtual cultural tourism; documentation of intangible cultural heritage.
|-
| '''1e. Education & Training'''
| Immersive classrooms; vocational training; adaptive training for high-risk technical professions; teacher professional development; AI-tutor adaptive support.
|-
| '''1f. Security & Defence'''
| Persistent military/civil protection training; immersive mission planning; ruggedized on-field operational assistance; real-time biofeedback stress modeling; technological autonomy.
|-
| '''1g. Cities & Public Administration'''
| City-scale DTs (CitiVerse); Local Digital Twins; virtual city halls for civic services; AI-driven urban decision support; public outreach and georeferenced visualisations.
|-
| rowspan="6" | '''Pillar 2: Technical Outlook & Challenges'''
| '''2a. Visualisation, Sensing & Immersion'''
| Foveated display, Micro-OLED/MicroLED light engines; flat optics/metasurfaces; vergence-accommodation conflict (VAC) mitigation; privacy-aware sensing; multi-sensory feedback (haptic, spatial audio, olfaction).
|-
| '''2b. Real-Time User Interaction'''
| Whole-body sensor fusion; runtime interoperability (OpenXR, WebXR); spatial computing mapping; avatar embodiment standards; cognitive load optimization; Living Labs testing.
|-
| '''2c. Authoring & Experience Design'''
| European dedicated XR engines; low-code/no-code creator empowerment; collaborative 3D scene versioning; human-AI co-editing; context-aware dynamic adaptation.
|-
| '''2d. Standardisation & Interoperability'''
| European Interoperability Framework (EIF) alignment; common data formats; Asset Administration Shell (AAS) standardization; federated identity; digital asset ownership schemas.
|-
| '''2e. Digital Twins, Assets & People'''
| Model Order Reduction (MOR); Uncertainty Quantification (UQ); automated NeRF/Gaussian Splatting reconstruction; human DT modeling; marker-less motion capture; DevOps for DTs.
|-
| '''2f. Applied AI for Virtual Worlds'''
| Multi-modal LLMs and foundational models; On-device edge AI inference; federated learning; physics-informed neural networks; conversational NPCs; multi-agent coordination.
|-
| rowspan="5" | '''Pillar 3: Socio-Economic Outlook & Challenges'''
| '''3a. Human Rights, Safety & Values'''
| Bridging the digital divide; native accessibility guidelines (XR WCAG equivalent); diverse avatar representation; GDPR-compliant minor protection; safety-by-design (blocking/safety bubbles).
|-
| '''3b. Governance & Law Enforcement'''
| Harmonised borderless legal frameworks; co-regulation models; multi-stakeholder governance pilots; 3D forensic evidence capture; Selective Traceability in pseudonymous worlds.
|-
| '''3c. Economics & Innovation'''
| Data monetisation redistribution (data dividends); royalty mechanisms for 3D creators; hardware affordability; legal frameworks for IP/trademark validity in co-creation ecosystems.
|-
| '''3d. Sustainability, Health & Environment'''
| Hardware circular economy; software eco-conception (DRY, micro-coding); real-time footprint monitoring; ergonomic XR visual health clinical trials; technostress mitigation.
|-
| '''3e. Trust & Human Oversight'''
| Explainable AI (XAI) tailored for 3D/AR; independent platform algorithmic auditing; AI-generated content labeling (deepfake detection); codes of conduct against dark patterns.
|}

===== Scientific Roadmap: Three Horizons of Technological Development =====
* '''Short-term Technological Developments (3-5 Years):''' Development of ergonomic, lightweight XR hardware with adaptive systems to mitigate motion sickness; rollout of accessible no-code/low-code authoring tools; AI-assisted moderation and generative content creation tools; adaptive governance frameworks (GDPR, AI Act, Data Act compliance); adoption of interoperable standards for DTs and cross-platform VW experiences.
* '''Mid-term Technological Developments (5-7 Years):''' Advanced XR devices integrating improved optical systems with rich multisensory feedback; deployment of scalable, cloud-edge distributed infrastructures; human-centric AI interactions via context-aware virtual avatars; establishment of transparent, explainable AI (XAI) and ethics-by-design authoring pipelines.
* '''Long-term Technological Developments (7-10 Years):''' Next-generation brain-computer interfaces (BCIs) for seamless neural input; device-free interaction with bio-integrated sensors; adaptive, self-evolving AI models utilizing decentralized edge networks; environmental sustainability integration with circular economy models for XR hardware; and impact-based green funding frameworks.

==== 1.4 Building-Block Crosswalk (EC Staff Working Document Alignment) ====
The Virtual Worlds SRIA priorities align precisely with the European Commission's technical building blocks:

{| class="wikitable" style="width:100%;"
|-
! style="background:#f2f2f2; width:30%;" | EC Technical Building Block
! style="background:#f2f2f2; width:70%;" | Virtual Worlds SRIA Alignment & Chapter Focus
|-
| '''Cloud–Edge–IoT Continuum'''
| Distributed intelligence architectures, on-device edge AI inference (2f.4, 2f.6), and scalable cloud-edge middleware for distributed rendering (2c.8).
|-
| '''Artificial Intelligence & ML'''
| Core of Pillar 2f (Applied AI), including generative models for 3D content, conversational NPCs, and multi-modal scene analysis.
|-
| '''High-Performance Computing (HPC)'''
| Compute-intensive spatial mapping, high-speed networks, and real-time physical rendering (2b.6), utilizing EuroHPC AI Factories.
|-
| '''Data Spaces & Interoperability'''
| Secure decentralized data sharing frameworks (2d.6) aligned with Manufacturing-X, common European Health Data Spaces, and Common European Data Spaces for Cultural Heritage.
|-
| '''Digital Identity & Trust Frameworks'''
| Trust and human oversight (Pillar 3e), decentralized self-sovereign identity (SSI) models, and eIDAS-aligned avatar authentication (2d.13, 2d.15).
|-
| '''Extended Reality (XR)'''
| Core visualization hardware (2a), whole-body sensor interaction (2b), and EU-sovereign authoring platforms (2c).
|-
| '''Digital Twins'''
| Pillar 2e (Digital Twins, Assets & People), encompassing Model Order Reduction, DevOps for continuous validation, and the European Virtual Human Twin.
|-
| '''Standards & Interoperability'''
| Pillar 2d, European Interoperability Framework (EIF) layered model, glTF/OpenXR adoption, and Asset Administration Shell (AAS) standardization.
|-
| '''Human–Machine Collaboration'''
| Whole human-body HCCI interfaces (2b.1), multimodal haptics (2a.16), and brain-computer interfaces (BCIs).
|-
| '''Security & Compliance'''
| Co-regulatory platform frameworks (3b.4), robust cybersecurity compliance (NIS2, Cyber Resilience Act) (3a.19), and compliance-by-design authoring tools.
|}

==== 1.5 Governance & Ecosystem ====
* '''Leading Organisations / Associations:''' Co-programmed Horizon Europe Partnership on Virtual Worlds, backed by the Virtual and Augmented Reality Industrial Coalition.
* '''Ecosystem Stakeholders:''' 3,700+ European XR actors, including major industrial enterprises, SMEs, individual content creators, artists, universities, and research institutes.
* '''Coordinating EU Initiatives:''' High-level coordination with the Big Data Value Association (BDVA), AI, Data and Robotics Association (ADRA), Smart Networks and Services JU (6G-IA), and Photonics21.
* '''Engagement Mechanisms:''' Distributed "Virtual World Labs" acting as a European Cultural XR Infrastructure; multi-stakeholder governance bodies; European Citizens' Panels; legal sandboxes for urban and public administrative testing.
* '''Update Frequency:''' Triennial (aligned with Horizon Europe Work Programme planning cycles).

Virtual Worlds Association SRIA

2026-09-07T12:29:37Z

CollectiveIntelligenceAdmin: Created page with "=== Virtual Worlds Association Strategic Research & Innovation Agenda (June 2025) === <blockquote>'''AI Acknowledgement''' The content has been provided by the Virtual and Augmented Reality Industrial Coalition. The content has been summarised using AI technologies, and validated by a human author.</blockquote> The '''Virtual Worlds Strategic Research & Innovation Agenda (SRIA) 2025''' defines a comprehensive, human-centric trajectory for Europe's immersive technology..."

=== Virtual Worlds Association Strategic Research & Innovation Agenda (June 2025) ===

<blockquote>'''AI Acknowledgement''' The content has been provided by the Virtual and Augmented Reality Industrial Coalition. The content has been summarised using AI technologies, and validated by a human author.</blockquote>

The '''Virtual Worlds Strategic Research & Innovation Agenda (SRIA) 2025''' defines a comprehensive, human-centric trajectory for Europe's immersive technology ecosystem. It outlines key applications across seven vertical sectors, identifies six technical and five socio-economic challenge domains, and provides a multi-horizon scientific roadmap to establish European strategic autonomy, technological leadership, and digital sovereignty.

Aligned with the European Commission’s ''Web 4.0 and Virtual Worlds'' strategy, the agenda establishes a values-driven framework where privacy, inclusivity, transparency, and accessibility are embedded directly into hardware and software design.

For '''OPENVERSE''', this SRIA represents the '''strategic and user-application blueprint'''. While EUCloudEdgeIoT defines the compute backbone and ADRA provides the semantic and trust layers, the Virtual Worlds SRIA articulates the actual application use cases, immersive interface requirements, and socio-technical boundaries that shape virtual spaces. As a collaborative collective intelligence, OPENVERSE can leverage this SRIA to align European research efforts, pilot interoperable standards, and build a cohesive co-creation toolkit for the European Virtual Worlds ecosystem.

==== 1.1 Basic Identification ====
* '''Initiative / Partnership Name:''' Candidate Horizon Europe Partnership on Virtual Worlds / Virtual and Augmented Reality Industrial Coalition
* '''Full SRIDA/SRIA Title & Version:''' ''Strategic Research & Innovation Agenda: Solving Real World Problems'' (v1.0, June 2025)
* '''Publication / Last Update Date:''' June 2025
* '''Governing Body / Association:''' Virtual and Augmented Reality Industrial Coalition (established in 2020 by the European Commission), serving as the foundation for the candidate Horizon Europe Partnership on Virtual Worlds.
* '''Type:''' Candidate Co-programmed European Partnership under [https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-europe/cluster-4-digital-industry-and-space_en Horizon Europe, Cluster 4]
* '''Editors:''' Theo Papadopoulos (Siemens), Matthieu Worm (Siemens)
* '''Key Chapter Penholders:''' Francisco Ibáñez (Brainstorm Multimedia), Spiros Nikolopoulos (CERTH), Marco Sacco (CNR-STIIMA), Maud Marchal (CNRS), Olivier Balet (CS Group), Didier Stricker (DFKI), Richard Bosmans (EssilorLuxottica), Leif Opperman (Fraunhofer FIT), Simon Delaere (imec), Julien Castet (Immersion), Natalie Bertels (KU Leuven), Bert Pluymers (KU Leuven), Laszlo Arnould (PopulAR), Frank Feinbube (SAP), Mariano Luis Alcañiz Raya (Universidad Politécnica de Valencia), Krzysztof Walczak (Uniwersytet Ekonomiczny w Poznaniu), Andre Miodezky (Voxel Sensors), Mike Matton (VRT)
* '''Website / Source:''' [https://digital-strategy.ec.europa.eu/en/policies/virtual-worlds Virtual Worlds Industrial Coalition Key Documents]

==== 1.2 Strategic Orientation ====
===== Vision Statement =====
To establish a human-centric European Virtual Worlds ecosystem that seamlessly blends physical and digital realities to solve real-world problems. Consumers experience unparalleled engagement and personalisation; workers benefit from enhanced, cross-border collaboration with Digital Twins; and public services are streamlined for accessibility, efficiency, and social inclusion. This pursuit of digital strategic autonomy ensures that European values of privacy, transparency, and inclusivity are embedded by design, preventing reliance on external actors and fostering an open, ethically sound digital future.

===== Core Mission / Objectives (6 Key Missions) =====
# '''Solving Real-World Problems:''' Drive the practical deployment of Virtual Worlds (VW) across industry, healthcare, education, arts, public administration, and security.
# '''Achieving Technological Autonomy:''' Mitigate dependency on non-European providers by developing core European components across the full XR value chain (processors, optics, software).
# '''Native Accessibility and Inclusion:''' Guarantee universal access to VW for people of all abilities, cultures, and languages, actively bridging the digital divide.
# '''Ethics, Safety, and Trust by Design:''' Establish robust frameworks for privacy-preserving sensing, explainable AI (XAI), and child-safe virtual spaces.
# '''Interoperable Standards and Portability:''' Drive global standardization for avatar portability, digital asset ownership, and secure decentralized data sharing.
# '''Co-Creation and Capacity Building:''' Empower European creators, SMEs, and researchers through multidisciplinary training, collaborative platforms, and open-source toolkits.

===== Policy Alignment =====
* '''European Commission Web 4.0 and Virtual Worlds Strategy (July 2023):''' Core strategic framework driving industrial ecosystems, public sector applications (CitiVerse, Local Digital Twins), and global governance.
* '''Horizon Europe Cluster 4 (Digital, Industry and Space):''' Anchor funding programme, supporting initiatives like GenAI4EU and Core Technologies for Virtual Worlds.
* '''Digital Decade Policy Programme 2030:''' Aligned with European targets for advanced digital skills, secure infrastructures, digital public services, and business transition.
* '''European Legislative Framework:''' Strictly aligned with the General Data Protection Regulation (GDPR), Artificial Intelligence Act (AI Act), Data Act, Data Governance Act, Digital Services Act (DSA), and Digital Markets Act (DMA).
* '''The European Green Deal:''' Leveraging VW to optimize logistics, reduce material prototyping waste, and foster ecological awareness.

==== 1.3 Technological & Thematic Priorities ====
The Virtual Worlds SRIA structures its research and innovation actions across three main thematic pillars, supported by context-enabling disciplines:

{| class="wikitable" style="width:100%;"
|-
! style="background:#f2f2f2; width:25%;" | Pillar
! style="background:#f2f2f2; width:35%;" | Domain / Chapter
! style="background:#f2f2f2; width:40%;" | Key Research and Innovation Objectives
|-
| rowspan="7" | '''Pillar 1: Applications in Key Sectors'''
| '''1a. Industry & Logistics'''
| Standardized Digital Twins (DT); rapid prototyping with collaborative design; Virtual Factory Integration; intralogistics fleet management; collaborative remote maintenance.
|-
| '''1b. Healthcare & Well-being'''
| Personalized clinical care with Patient DTs; European Virtual Human Twin; real-time intraoperative surgical assistance; XR-supported rehabilitation; special education therapies.
|-
| '''1c. Media & Entertainment'''
| AI-driven virtual production; real-time volumetric media and avatar presence; Open XR stage tracking; immersive interactive events; secure, decentralized media licensing.
|-
| '''1d. Arts & Culture'''
| User-centred museum XR experiences; performing arts in virtual spaces; digital archiving of cultural events; virtual cultural tourism; documentation of intangible cultural heritage.
|-
| '''1e. Education & Training'''
| Immersive classrooms; vocational training; adaptive training for high-risk technical professions; teacher professional development; AI-tutor adaptive support.
|-
| '''1f. Security & Defence'''
| Persistent military/civil protection training; immersive mission planning; ruggedized on-field operational assistance; real-time biofeedback stress modeling; technological autonomy.
|-
| '''1g. Cities & Public Administration'''
| City-scale DTs (CitiVerse); Local Digital Twins; virtual city halls for civic services; AI-driven urban decision support; public outreach and georeferenced visualisations.
|-
| rowspan="6" | '''Pillar 2: Technical Outlook & Challenges'''
| '''2a. Visualisation, Sensing & Immersion'''
| Foveated display, Micro-OLED/MicroLED light engines; flat optics/metasurfaces; vergence-accommodation conflict (VAC) mitigation; privacy-aware sensing; multi-sensory feedback (haptic, spatial audio, olfaction).
|-
| '''2b. Real-Time User Interaction'''
| Whole-body sensor fusion; runtime interoperability (OpenXR, WebXR); spatial computing mapping; avatar embodiment standards; cognitive load optimization; Living Labs testing.
|-
| '''2c. Authoring & Experience Design'''
| European dedicated XR engines; low-code/no-code creator empowerment; collaborative 3D scene versioning; human-AI co-editing; context-aware dynamic adaptation.
|-
| '''2d. Standardisation & Interoperability'''
| European Interoperability Framework (EIF) alignment; common data formats; Asset Administration Shell (AAS) standardization; federated identity; digital asset ownership schemas.
|-
| '''2e. Digital Twins, Assets & People'''
| Model Order Reduction (MOR); Uncertainty Quantification (UQ); automated NeRF/Gaussian Splatting reconstruction; human DT modeling; marker-less motion capture; DevOps for DTs.
|-
| '''2f. Applied AI for Virtual Worlds'''
| Multi-modal LLMs and foundational models; On-device edge AI inference; federated learning; physics-informed neural networks; conversational NPCs; multi-agent coordination.
|-
| rowspan="5" | '''Pillar 3: Socio-Economic Outlook & Challenges'''
| '''3a. Human Rights, Safety & Values'''
| Bridging the digital divide; native accessibility guidelines (XR WCAG equivalent); diverse avatar representation; GDPR-compliant minor protection; safety-by-design (blocking/safety bubbles).
|-
| '''3b. Governance & Law Enforcement'''
| Harmonised borderless legal frameworks; co-regulation models; multi-stakeholder governance pilots; 3D forensic evidence capture; Selective Traceability in pseudonymous worlds.
|-
| '''3c. Economics & Innovation'''
| Data monetisation redistribution (data dividends); royalty mechanisms for 3D creators; hardware affordability; legal frameworks for IP/trademark validity in co-creation ecosystems.
|-
| '''3d. Sustainability, Health & Environment'''
| Hardware circular economy; software eco-conception (DRY, micro-coding); real-time footprint monitoring; ergonomic XR visual health clinical trials; technostress mitigation.
|-
| '''3e. Trust & Human Oversight'''
| Explainable AI (XAI) tailored for 3D/AR; independent platform algorithmic auditing; AI-generated content labeling (deepfake detection); codes of conduct against dark patterns.
|}

===== Scientific Roadmap: Three Horizons of Technological Development =====
* '''Short-term Technological Developments (3-5 Years):''' Development of ergonomic, lightweight XR hardware with adaptive systems to mitigate motion sickness; rollout of accessible no-code/low-code authoring tools; AI-assisted moderation and generative content creation tools; adaptive governance frameworks (GDPR, AI Act, Data Act compliance); adoption of interoperable standards for DTs and cross-platform VW experiences.
* '''Mid-term Technological Developments (5-7 Years):''' Advanced XR devices integrating improved optical systems with rich multisensory feedback; deployment of scalable, cloud-edge distributed infrastructures; human-centric AI interactions via context-aware virtual avatars; establishment of transparent, explainable AI (XAI) and ethics-by-design authoring pipelines.
* '''Long-term Technological Developments (7-10 Years):''' Next-generation brain-computer interfaces (BCIs) for seamless neural input; device-free interaction with bio-integrated sensors; adaptive, self-evolving AI models utilizing decentralized edge networks; environmental sustainability integration with circular economy models for XR hardware; and impact-based green funding frameworks.

==== 1.4 Building-Block Crosswalk (EC Staff Working Document Alignment) ====
The Virtual Worlds SRIA priorities align precisely with the European Commission's technical building blocks:

{| class="wikitable" style="width:100%;"
|-
! style="background:#f2f2f2; width:30%;" | EC Technical Building Block
! style="background:#f2f2f2; width:70%;" | Virtual Worlds SRIA Alignment & Chapter Focus
|-
| '''Cloud–Edge–IoT Continuum'''
| Distributed intelligence architectures, on-device edge AI inference (2f.4, 2f.6), and scalable cloud-edge middleware for distributed rendering (2c.8).
|-
| '''Artificial Intelligence & ML'''
| Core of Pillar 2f (Applied AI), including generative models for 3D content, conversational NPCs, and multi-modal scene analysis.
|-
| '''High-Performance Computing (HPC)'''
| Compute-intensive spatial mapping, high-speed networks, and real-time physical rendering (2b.6), utilizing EuroHPC AI Factories.
|-
| '''Data Spaces & Interoperability'''
| Secure decentralized data sharing frameworks (2d.6) aligned with Manufacturing-X, common European Health Data Spaces, and Common European Data Spaces for Cultural Heritage.
|-
| '''Digital Identity & Trust Frameworks'''
| Trust and human oversight (Pillar 3e), decentralized self-sovereign identity (SSI) models, and eIDAS-aligned avatar authentication (2d.13, 2d.15).
|-
| '''Extended Reality (XR)'''
| Core visualization hardware (2a), whole-body sensor interaction (2b), and EU-sovereign authoring platforms (2c).
|-
| '''Digital Twins'''
| Pillar 2e (Digital Twins, Assets & People), encompassing Model Order Reduction, DevOps for continuous validation, and the European Virtual Human Twin.
|-
| '''Standards & Interoperability'''
| Pillar 2d, European Interoperability Framework (EIF) layered model, glTF/OpenXR adoption, and Asset Administration Shell (AAS) standardization.
|-
| '''Human–Machine Collaboration'''
| Whole human-body HCCI interfaces (2b.1), multimodal haptics (2a.16), and brain-computer interfaces (BCIs).
|-
| '''Security & Compliance'''
| Co-regulatory platform frameworks (3b.4), robust cybersecurity compliance (NIS2, Cyber Resilience Act) (3a.19), and compliance-by-design authoring tools.
|}

==== 1.5 Governance & Ecosystem ====
* '''Leading Organisations / Associations:''' Co-programmed Horizon Europe Partnership on Virtual Worlds, backed by the Virtual and Augmented Reality Industrial Coalition.
* '''Ecosystem Stakeholders:''' 3,700+ European XR actors, including major industrial enterprises, SMEs, individual content creators, artists, universities, and research institutes.
* '''Coordinating EU Initiatives:''' High-level coordination with the Big Data Value Association (BDVA), AI, Data and Robotics Association (ADRA), Smart Networks and Services JU (6G-IA), and Photonics21.
* '''Engagement Mechanisms:''' Distributed "Virtual World Labs" acting as a European Cultural XR Infrastructure; multi-stakeholder governance bodies; European Citizens' Panels; legal sandboxes for urban and public administrative testing.
* '''Update Frequency:''' Triennial (aligned with Horizon Europe Work Programme planning cycles).

==== 1.6 Alignment with OPENVERSE ====
The Virtual Worlds Association SRIA serves as the theoretical and use-case blueprint for the '''OPENVERSE Collective Intelligence'''. OPENVERSE acts as the direct, practical implementation playground to address the gaps highlighted in this SRIA:
* '''Interoperability Sandbox:''' OPENVERSE provides the collaborative MediaWiki-based environment to pilot and document EIF-aligned semantic, technical, and organizational standards.
* '''Co-Creation Deployment:''' The ''OPENVERSE Co-creation Toolkit'' directly answers the SRIA's call for low-code/no-code authoring methods, democratizing access for non-expert creators and SMEs.
* '''Asset Reusability:''' The ''OPENVERSE Open and Reusable Components Repository'' acts as a prime channel to share European-developed technological bricks, helping Europe break its dependency on closed, non-EU ecosystems.
* '''Participatory Policy Testing:''' OPENVERSE's interactive discussion forums on the Technological Framework and Roadmap provide the perfect platform for multi-stakeholder governance experiments, fostering civic participation.

==== 1.7 SRIDA/SRIA Document Metadata ====
* '''Keywords / Tags:''' Virtual Worlds, Web 4.0, Immersive Technology, Extended Reality, Human-Centric, Digital Twins, Applied AI, Interoperability, Standardisation, Socio-Economic Impact, Accessibility, Sovereignty, Sustainability.
* '''Referenced Horizon Europe Cluster:''' Cluster 4 (Digital, Industry & Space) with direct cross-cutting links to Cluster 2 (Culture, Creativity and Inclusive Society) and Cluster 5 (Climate, Mobility & Energy).
* '''TRL Ranges:''' TRL 2 – 9. Low TRL (2-4) for brain-computer interfaces (BCIs), neuromorphic computing, and hybrid Model Order Reduction; High TRL (7-9) for industrial simulation, City LDTs, and WebXR.
* '''Budget and Investment Focus:''' Industrial competitiveness, open-source European authoring/distribution tools, SME capacity building, digital/AI literacy, ergonomic health research, and green-by-design computing infrastructure.
* '''Socio-Economic Indicators:'''
** VW global market projected to expand from €27B (2022) to >€800B by 2030.
** Projected creation of ~860,000 XR-related jobs in Europe by 2025.
** Cultural employment encompassing 7.9 million people (3.8% of EU workforce) across 2 million cultural enterprises (99.9% SMEs).
** 22% of European heritage collections currently digitally reproduced.
** €70M invested in digital cultural heritage through Horizon 2020.
* '''Policy and Legislative References:'''
** European Commission Strategy on Web 4.0 & Virtual Worlds (2023);
** General Data Protection Regulation (GDPR) & e-Privacy Directive;
** Artificial Intelligence Act (AI Act);
** Data Act & Data Governance Act;
** Digital Services Act (DSA) & Digital Markets Act (DMA);
** Cybersecurity Act, Cyber Resilience Act, and NIS 2 Directive;
** Net Zero Industry Act & The European Green Deal.

SRIAs and SRIDAs

2026-09-07T12:14:27Z

CollectiveIntelligenceAdmin:

This page provides a comprehensive list of the '''Strategic Research and Innovation Agendas''' and '''Strategic''' '''Research, Innovation and Deployment Agendas''' relevant to European Virtual Worlds.
* [[6G SNS]]
* [[ADRA]]
* [[BDVA]]
* [[EFFRA]]
* [[EIT Culture & Creativity]]
* [[EIT Digital]]
* [[EIT Health]]
* [[EIT Manufacturing]]
* [[EIT Urban Mobility]]
* [[EOSC]]
* [[EUCloudEdgeIoT]]
* [[Eureka]]
* [[EuroHPC]]
* [[European Game Developers Foundation]]
* [[Europeana]]
* [[IHI JU]]
* [[MyData]]
* [[NEM]]
* [[Photonics21]]
* [[THCS]]
* [[Virtual Worlds Association SRIA]]
* [[XR Interaction]]

MediaWiki:Sitenotice

2026-09-02T08:51:41Z

CollectiveIntelligenceAdmin: Blanked the page

Co-creation Toolkit

2026-09-02T08:14:16Z

CollectiveIntelligenceAdmin:

== A Toolkit for Co-Creation in Virtual Worlds ==
This page provides an overview and links to the co-creation tools developed by Politecnico di Milano in the context of the OPENVERSE project.
A core component of planning is the selection and contextual adaptation of co-creation tools. The OPENVERSE Toolkit includes a wide variety of such tools—a curated set of 48 co-creation tools mapped across the four phases of the [[wikipedia:Double_Diamond_(design_process_model)|Double Diamond]]—that support everything from early exploration to final decision-making.
[[File:Double diamond .png|alt=Image representing the Double Diamond design process model|center|thumb|790x790px|'''Double Diamond design process model''' Work by Politecnico di Milano, adapted from Design Council's original work - CC BY-NC-SA 4.0]]
The goal is to empower a diverse range of stakeholders—designers, developers, educators, VWs consumers, and citizens—to run meaningful co-creation processes in immersive environments, using a shared methodology grounded in field experimentation and design research.

<center><youtube width="100%" height="400">s2BpzupW5Qc</youtube></center>

The complete [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=0-1&p=f&t=djpkfnwCxadiCigO-0 Co-creation Toolkit] is available on the Figma platform.

<blockquote>
=== License and Attribution ===
This toolkit is designed for open collaboration, and its structure and licensing model are crafted to comply with the terms of all referenced source materials. The entire original content of this toolkit is licensed under [https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)].

The content of this toolkit is shared as CC BY-NC-SA 4.0. This license enables re-users to distribute, remix, adapt, and build upon this material in any medium or format for noncommercial purposes only, provided original attribution (BY) is always given.

Because this toolkit adopts the '''ShareAlike (SA)''' element, any new work created by adapting, remixing, or transforming the original licensed content from this toolkit must be distributed under the same or a compatible Creative Commons license.

Toolkit License: [https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en CC BY-NC-SA 4.0]

Designed in 2025 by: Riccardo Ventura, Ilaria Mariani, Venere Ferraro, Francesca Rizzo, Department of Design, Politecnico di Milano</blockquote><blockquote>
=== Source Material ===
This work includes content, methodologies, and inspiration drawn from the following sources:

* Adapted and Derivative Content (CC BY-NC-SA 4.0): Tools and methodologies were directly adapted, remixed, or inspired by materials from the AI4Gov Toolkit (CC BY-NC-SA 4.0) and Follow the Rabbit: A Field Guide to Systemic Design (CC BY-NC-SA 4.0). Due to this adaptation, the ShareAlike condition of these source licenses requires that this resulting toolkit must also adopt the CC BY-NC-SA 4.0 license.
* Inspirational Use Only (Non-Derivative): The creation of our new tools, concepts, guides, and the overall structural approach were purely inspired by the materials presented in three other sources. This process involved consulting the Servicedesigntools (CC BY-NC-ND 2.5) repository, the This is Service Design Doing – Method Library (copyrighted content), and the Share, Learn, Innovate! toolkit (copyrighted content). The team behind this toolkit consulted these materials for guides, concepts, and structure but did not adopt, adapt, or create derivative versions of their original content
</blockquote>

=== Components of the Toolkit ===
All the components are available for exploration and reuse on the Figma board, along with the full description of each of the components. This page provides a high-level overview of the components for quick reference. The components are grouped based on the four Double Diamond phases shown above. In case of overlaps across the phases, the headings will show both relevant phases.

{| class="wikitable"
! style="background-color:#E400FF; color:#FFFFFF;" | Discover
! style="background-color:#B700FF; color:#FFFFFF;" | Define
! style="background-color:#9600FF; color:#FFFFFF;" | Develop
! style="background-color:#7200FF; color:#FFFFFF;" | Deliver
|-
| [[#Cultural Probes|Cultural Probes]] || [[#Co-creating Journey Maps|Co-creating Journey Maps]] || [[#Experience Prototypes|Experience Prototypes]] || [[#Desktop System Mapping|Desktop system mapping (a.k.a. Business Origami)]]
|-
| [[#Ecosystem Map|Ecosystem Map]] || [[#Co-creating Personas|Co-creating Personas]] || [[#Role Playing|Role Playing]] || [[#Desktop Walkthrough|Desktop Walkthrough]]
|-
| [[#Envisioning the Future|Envisioning the Future]] || [[#Co-Creative Workshops|Co-Creative Workshops]] || [[#AI Functionalities Cards|AI Functionalities Cards]] || [[#Emotional Journey Feedback|Emotional Journey Feedback]]
|-
| [[#Fishbowl|Fishbowl]] || [[#Emotional Journey Map|Emotional Journey Map]] || [[#Concept Walkthrough|Concept Walkthrough]] || [[#Investigative Rehearsal|Investigative Rehearsal]]
|-
| [[#Iceberg Diagram|Iceberg Diagram]] || [[#Impact Journey|Impact Journey]] || [[#Ecosystem Map|Ecosystem Map]] || [[#Rehearsing Digital Services|Rehearsing Digital Services]]
|-
| [[#Jigsaw|Jigsaw]] || [[#Mapping Journeys|Mapping Journeys]] || [[#Future Backcasting|Future Backcasting]] || [[#Service Blueprint|Service Blueprint]]
|-
| [[#Knowledge Café|Knowledge Café / Round Table Sessions]] || [[#System Map|System Map]] || [[#Human Agent Journey|Human Agent Journey]] || [[#Service Prototype|Service Prototype]]
|-
| [[#Knowledge Fair|Knowledge Fair]] || [[#System Scenario|System Scenario]] || [[#Future-State Journey|Future-State Journey]] || [[#Subtext|Subtext]]
|-
| [[#Open Space|Open Space]] || [[#Transition Journey|Transition Journey]] || [[#Innovative Brainstorming|Innovative Brainstorming]] || [[#Experience Prototypes|Experience Prototypes]]
|-
| [[#Problem Framing|Problem Framing]] || [[#Ecosystem Loops|Ecosystem Loops]] || [[#Integrated Journey|Integrated Journey]] || [[#Role Playing|Role Playing]]
|-
| [[#Service Safari|Service Safari]] || || [[#Journey Ideation with Dramatic Arcs|Journey Ideation with Dramatic Arcs]] || [[#Rough Prototyping|Rough Prototyping]]
|-
| [[#Social Network Analysis|Social Network Analysis]] || || [[#Service Image|Service Image]] ||
|-
| [[#Sociometrics|Sociometrics]] || || [[#System UX Map Agent Journey|System UX Map Agent Journey]] ||
|-
| [[#Stakeholder Map|Stakeholder Map]] || || [[#User Scenario|User Scenarios]] ||
|-
| [[#Stakeholder Value Map|Stakeholder Value Map]] || || [[#Rough Prototyping|Rough Prototyping]] ||
|-
| [[#Ecosystem Loops|Ecosystem Loops]] || || ||
|}

=== The Toolkit in action ===
The videos below, portraying the activities of seven co-creation groups, showcases the use of several of the components of the toolkit.
{| class="wikitable"
|-
| <youtube width="400" height="240">KPemYBWjAig</youtube>
| <youtube width="400" height="240">jRE2TEP59DQ</youtube>
|-
| <youtube width="400" height="240">hY5mLs9Erv8</youtube>
| <youtube width="400" height="240">c-xghyabhfU</youtube>
|-
| <youtube width="400" height="240">LG6s8NlbvJM</youtube>
| <youtube width="400" height="240">6tQQw2Wpyh0</youtube>
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| <youtube width="400" height="240">2r_BkoknYEY</youtube>
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|}

=== Discover ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1396&t=jRTjE5JDjxvV23M4-4 Cultural Probes] ====
[[File:Cultural Probes.png|alt=Cultural probes|thumb|383x383px|Cultural probes - CC BY-NC-SA 4.0]]
Cultural Probes are stimuli-based design research tools that invite participants to document personal experiences, contexts, and thoughts through artifacts such as postcards, diaries, or in-world interactive objects. In immersive VW environments, designers distribute digital probes (VR postcards, 3D tokens, prompts) into user spaces.

Participants interact, capture audio/video responses, and and interactions in digital environments, and return probes for analysis. Through asynchronous co-creation, teams gather rich qualitative data, uncover emergent needs, and iteratively refine personas, journey maps, and system maps. Ideal for exploratory research in spatial VR or 3D platforms, Cultural Probes foster empathy, spark ideation, and ground service design in lived experiences.

'''How to use it?'''

# Decide which digital / physical objects could help users narrate their virtual worlds experiences.
# Ask users to take notes throughout the project.
# Use notes to gather useful insight for further improvement.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1545&t=jRTjE5JDjxvV23M4-4 Ecosystem Map] ====
[[File:Ecosystem Map.png|alt=Ecosystem Map|thumb|383x383px|Ecosystem Map - CC BY-NC-SA 4.0]]
Ecosystem Map portrays every entity, flow, and relationship that defines a service’s surrounding ecosystem in immersive three-dimensional space. Avatars or 3D tokens represent users, partners, suppliers, technologies, and environmental factors, while animated streams trace value exchanges, information channels, and resource movements.

Collaborators navigate the dynamic model, simulate changes—such as adding new nodes or rerouting flows—and observe systemic ripple effects in real time. Participants annotate insights, propose interventions, and iteratively refine connections. Perfect for VR-enabled co-creation workshops, Ecosystem Map fosters holistic understanding, surfaces hidden interdependencies, and aligns stakeholders around end-to-end service innovation strategies.

'''How to use it?'''

# Define a central topic and put it at the center of the canvas.
# Describe relevant players and associate to each a different shape.
# Place shapes in the map.
# Central players should be placed close to the center, secondary players peripherically.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1592&t=jRTjE5JDjxvV23M4-4 Envisioning the Future] ====
[[File:Envisioning the Future.png|alt=Envisioning the Future|thumb|380x380px|Envisioning the Future - CC BY-NC-SA 4.0]]
Envisioning the Future is a collaborative scenario-building tool that invites teams to imagine plausible worlds three to six years ahead within virtual environments. Participants embody avatars in detailed VR or 3D spaces, exploring future success states—streamlined operations, empowered customers, sustainable ecosystems.

During guided workshops, they define milestones, identify emerging trends, and co-create narratives that show how organizational goals materialize. By visualizing outcomes and backcasting interventions, Envisioning the Future fosters long-term strategic alignment, surfaces uncertainties, and sparks innovative service breakthroughs. Ideal for remote or hybrid teams, this method leverages immersive storytelling and collective foresight to translate visionary aspirations into actionable roadmaps.

'''How to use it?'''

# Select a timeframe fro 3 to 6 years.
# Answer to the provided questions.
# Describe as a scenario the vision.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1641&t=jRTjE5JDjxvV23M4-4 Fishbowl] ====
[[File:Fishbowl.png|alt=Fishbowl|thumb|371x371px|Fishbowl - CC BY-NC-SA 4.0]]
Fishbowl is an interactive dialogue technique that amplifies expert knowledge and broadens group understanding through a concentric-circle setup in virtual worlds.

In a central “bowl,” a handful of skilled avatars discuss targeted questions while an outer ring of observers listens, reflects, and captures insights on spatial whiteboards. When outer participants wish to contribute, they enter the bowl, temporarily swapping places with an inner speaker.

This fluid movement between inner and outer circles democratizes voice, encourages active listening, and fosters shared learning. Deployed in VR or 3D environments, Fishbowl’s structured yet flexible format drives deep engagement, peer teaching, and immersive co-creative exploration.

'''How to use it?'''

# Gather participants in a physical/virtual environment.
# Divide participants in 2 groups.
# Fishes (2-4 people): They have to discuss a relevant topic, at the center of the room.
# Observers (The rest of the participants): They have to take notes on the discussion and, if they wish to participate, respectfully interrupt the discussion, swapping places with a fish.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1691&t=jRTjE5JDjxvV23M4-4 Iceberg Diagram] ====
[[File:Iceberg Diagram.png|alt=Iceberg Diagram|thumb|369x369px|Iceberg Diagram - CC BY-NC-SA 4.0]]
An Iceberg Diagram visualizes beneath-the-surface forces that shape service behaviors by layering observable events, systemic structures, mental models, and underlying paradigms in a vertical 3D canvas. Participants position avatars or tokens at different strata—the tip of the iceberg representing customer actions, the submerged mass depicting processes, regulations, cultural beliefs, and deeper worldviews.

Collaborators drill down through scenarios in VR environments, annotating feedback loops, mental models, and leverage points that perpetuate current outcomes. Iterative exploration surfaces hidden constraints, reveals impactful intervention zones, and fosters systemic thinking. Ideal for immersive workshops, the Iceberg Diagram enables teams to align on root causes and co-design transformative strategies grounded in deep structural insight.

'''How to use it?'''

* Define a central topic.
* Compile brainstorm events section, highlighting relevant aspects.
* Compile patterns of behaviors section, highlighting repeating aspects.
* Compile system structures section, highlighting who/what is responsible for pattern creation.
* Compile mental models section, highlighting which assumptions and beliefs created the systemic structures.
* After looking at the big picture, place relevant aspects as icons in the iceberg.

<blockquote>Inspired by the toolkit: Follow the Rabbit Publisher: Colab

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1746&t=jRTjE5JDjxvV23M4-4 Jigsaw] ====
[[File:Jigsaw.png|alt=Jigsaw|thumb|366x366px|Jigsaw - CC BY-NC-SA 4.0]]
Jigsaw is a cooperative learning strategy adapted for virtual worlds that divides a complex service challenge into interlocking “puzzle pieces.” Small expert teams explore an assigned component—such as user research, technology integration, or policy constraints—and develop deep insights. Avatars reconvene in a shared 3D space to assemble findings, linking visual tokens, diagrams, and narratives to complete the holistic picture.

This method leverages spatial distribution, collaborative assembly, and peer teaching to build collective expertise and foster ownership. By transforming individual discoveries into a cohesive ecosystem map, Jigsaw enhances cross-functional understanding, drives mutual accountability, and accelerates integrated service design through immersive, puzzle-based co-creation.

'''How to use it?'''

# Divide participants in groups.
# Assign to each group a relevant topic/area to discuss
# Discuss in groups and keep track of the findings.
# Reassemble the pieces and discuss together the bigger picture.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1895&t=jRTjE5JDjxvV23M4-4 Knowledge Café] ====
[[File:Knowledge Café.png|alt=Knowledge Café|thumb|362x362px|Knowledge Café - CC BY-NC-SA 4.0]]
Knowledge Café or Round Table Sessions is an avatar-led dialogue method that builds collective intelligence in virtual worlds. Participants gather at themed café tables, sharing experiences and posting digital notes on shared canvases. After a timed session, avatars rotate to new tables, carrying forward insights and weaving ideas into a knowledge web.

Each table host curates threads and captures emergent patterns, ensuring continuity. By assuming that every participant is a source of wisdom, the format surfaces novel perspectives and cross-pollinates ideas across the group. Ideal for VR or 3D co-creation spaces, Knowledge Café fosters immersive collaboration and amplifies shared understanding.

'''How to use it?'''

# Gather participants in a shared collaborative setting.
# Define relevant topics of discussion.
# Define how much time to spend on each discussion before rotating.
# Divide participants in groups and ask each group to identify a reporter of the insights.
# Sit on the tables and start the timer, when time is off, rotate and change table/topic.
# After a full rotation, take some time to share what emerged from each topic between the groups.

<blockquote>Inspired by the toolkit: Follow the Rabbit Publisher: Colab

Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2041&t=jRTjE5JDjxvV23M4-4 Knowledge Fair] ====
[[File:Knowledge Fair.png|alt=Knowledge Fair|thumb|363x363px|Knowledge Fair - CC BY-NC-SA 4.0]]
Knowledge Fair is a virtual event for sharing insights from diverse experts through immersive booths, dynamic displays, and interactive presentations. In a 3D or VR expo hall, participants navigate avatar-driven pavilions themed around specific domains—data privacy, user research, policy design—and engage with multimedia panels showcasing research findings, prototypes, and case studies.

Exhibitors use digital posters, video kiosks, live demos, and spatial annotations to spark dialogue and crowdsourced ideation. Roleplay elements, such as expert avatars hosting Q&A sessions or scenario workshops, deepen engagement. Participants can vote on emerging ideas and form ad-hoc focus groups for deeper exploration. Ideal for large-scale VW co-creation, Knowledge Fair democratizes expertise and accelerates innovative service diffusion.

'''How to use?'''

# Gather participants in a shared collaborative setting.
# Define relevant topics of discussion.
# Divide participants in groups and ask each group to identify a reporter of the insights.
# Ask groups to build a personalized virtual/digital space for each topic.
# Ask reporters to stay in the space and discuss the topic with visitors.
# Ask other participants to move and discuss the topics freely in the space.
# When discussions are finished, confront notes of the reporters and gather useful information.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2482&t=jRTjE5JDjxvV23M4-4 Open Space] ====
[[File:Open Space.png|alt=Open Space|thumb|364x364px|Open Space - CC BY-NC-SA 4.0]]
Open Space is a participant-driven agenda creation method that harnesses the self-organizing capacity of virtual-world attendees. In a shared 3D plaza or VR amphitheater, avatars propose topics by posting spatial markers, then gather around interest hubs to co-create content and agendas. Participants dynamically form breakout circles, author session titles, and schedule discussions in real time, shaping learning objectives and collaborative outcomes.

The informal, flexible format empowers autonomy and emergent insights, while facilitators capture key outcomes on virtual whiteboards. Ideal for large-scale VW events, Open Space fosters deep engagement, immersive networked learning, and co-creation by blurring roles between organizers and participants.

'''How to use it?'''

# Gather participants in a shared collaborative setting.
# Define relevant topics of discussion.
# Allow participants to discuss in a free and untstructured space the topics.
# Ask groups to build a project agenda on the next steps
# When discussions are finished, gather useful informations

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2807&t=jRTjE5JDjxvV23M4-4 Problem Framing] ====
[[File:Problem Framing.png|alt=Problem Framing|thumb|374x374px|Problem Framing - CC BY-NC-SA 4.0]]
Problem Framing is a visual synthesis method that defines and structures ambiguous or complex challenges. Teams collaborate in a 3D canvas to externalize problem elements—constraints, assumptions, stakeholders, and unknowns—as digital nodes or clusters. Participants drag and group digital sticky notes, icons, and shapes to represent pain points, policy constraints, technical uncertainties, and user needs.

Over iterative sessions, they refine connections, annotate dependencies, and expose gaps in understanding. By framing a structured problem frame, teams reduce ambiguity, align on research focus, and establish a clear foundation for design. Ideal for early-stage co-creation workshops, Problem Framing guides planning and stakeholder consensus.

'''How to use it?'''

* ''''''Identify the specific problem you want to answer with the project.
* Identify one or two types of audience affected by the project
* Identify the long-term impact of the problem, and its general goals
* Identify the physical or abstract space in which the problem manifests and which kind of affordances and interactions does it allow

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2832&t=jRTjE5JDjxvV23M4-4 Service Safari] ====
[[File:Service Safari.png|alt=Service Safari|thumb|373x373px|Service Safari - CC BY-NC-SA 4.0]]
Service Safari immerses designers in first-person explorations of a service using avatar-led autoethnography within virtual worlds. Participants navigate key touchpoints—booking, service delivery, support—experiencing each interaction exactly as a customer would. As they move through the environment, they capture contextual insights via spatial annotations, voice memos, and reflective prompts triggered at meaningful moments.

This method uncovers hidden pain points, emotional reactions, and design opportunities with authentic “lived” perspective. Ideal for VR headsets or 3D platforms, Service Safari combines deep empathy and active roleplay to generate rich qualitative data, inspire creative solutions, and guide user-centered service innovation.

'''How to use it?'''

* Identify strong suits of the project.
* Identify pain points of the project
* Identify miscellaneous aspects of the project
* Place in the different temporal columns the identified aspects.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2880&t=jRTjE5JDjxvV23M4-4 Social Network Analysis] ====
[[File:Social Network Analysis.png|alt=Social Network Analysis|thumb|366x366px|Social Network Analysis - CC BY-NC-SA 4.0]]
Social Network Analysis visualizes the web of relationships and knowledge flows among individuals, teams, and organizations within a service ecosystem. In a virtual world, nodes—avatars representing people or groups—are positioned in 3D space, with linkages animating communication channels, collaboration ties, and information exchanges.

Participants can navigate the network, inspect connection strengths, and simulate changes (e.g., adding new roles or breaking silos) to observe systemic impacts. This method uncovers hidden influencers, bottlenecks, and expertise hubs, guiding targeted interventions. Ideal for VR or immersive 3D platforms, Social Network Analysis enhances stakeholder alignment by making invisible social structures visible and tunable for optimized service co-creation.

'''How to use it?'''

* Identify a meaningful stakeholder to analyze.
* Identify other relevant stakeholders to include in the social network.
* Place in the map the different stakeholders and visualize the ecosystem.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2952&t=jRTjE5JDjxvV23M4-4 Sociometrics] ====
[[File:Sociometrics.png|alt=Sociometrics|thumb|359x359px|Sociometrics - CC BY-NC-SA 4.0]]
Sociometrics uses embodied spatial modelling in virtual worlds to map social dynamics, influence patterns, and group interactions. Participants assume avatar roles and position themselves within 3D spaces to represent relationships—cooperation, authority, trust—connecting with lines or proximity triggers that reveal network density and communication pathways.

By externalizing interpersonal ties and emergent power structures, Sociometrics surfaces hidden influencers, friction points, and collaboration opportunities. Ideal for VR or desktop-based immersive platforms, this method enhances team alignment, deepens social insight, and supports targeted interventions in service ecosystem co-creation.

Košir, K., & Pečjak, S. (2005). Sociometry as a method for investigating peer relationships: What does it actually measure? Educational Research, 47(1), 127–144. <nowiki>https://doi.org/10.1080/0013188042000337604</nowiki>

'''How to use it?'''

* Identify relevant social dynamics, influence patterns, and social interactions as well as relevant stakeholders.
* Create clusters (Group 1, Group 2...).
* Map the notes in the canvas, ranging from low to high social rejection and from low to high social acceptance.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3017&t=jRTjE5JDjxvV23M4-4 Stakeholder Map] ====
[[File:Stakeholder Map.png|alt=Stakeholder Map|thumb|360x360px|Stakeholder Map - CC BY-NC-SA 4.0]]
Stakeholder Map visually arranges all actors in a service ecosystem by plotting individuals, groups, and organizations on axes of influence and interest within a shared virtual canvas. Designers place avatar tokens or 3D icons to represent each stakeholder, then draw animated links to illustrate relationships, dependencies, and communication channels.

Participants can filter by attributes, inspect persona profiles, and simulate scenario overlays to see how policy changes or market shifts affect power dynamics. Suitable for VR workshops or desktop co-creation sessions, Stakeholder Map clarifies project scope, aligns cross-functional teams, and surfaces key partners or friction points for targeted engagement.

'''How to use it?'''

* Identify all relevant stakeholders.
* Create categories and cluster the stakeholders.
* Map stakeholders in the canvas, ranging from low to high agency and from low to high impact.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3074&t=jRTjE5JDjxvV23M4-0 Stakeholder Value Map] ====
[[File:Stakeholder Value Map.png|alt=Stakeholder Value Map|thumb|359x359px|Stakeholder Value Map - CC BY-NC-SA 4.0]]
A Stakeholder Value Map distills the core motivations and needs of each stakeholder within a service ecosystem by plotting practical, social, and higher personal values on a shared virtual canvas. Participants assume avatar roles representing users, partners, regulators, or employees and annotate a 3D map with value attributes—basic necessities, relational priorities, and dignity-driven aspirations.

Through interactive dialogues, avatars voice their value-driven perspectives at key journey phases, while collaborators cluster and compare value patterns to uncover emerging tensions or alignments. Ideal for VR or 3D workshops, this immersive method enhances empathy, grounds decision-making in stakeholder priorities, and supports narrative-driven co-creation to optimize value exchange.

'''How to use it?'''

* Identify meaningful stakeholders to analyze.
* For the cluster of Personal Needs, add note(s) describing what your user desires to do.
* For the cluster of Practical Needs, add note(s) describing what your user should be able to practically do while interacting with the virtual world.
* For the cluster of Social Needs, add note(s) describing how does your user expect to interact with others in the virtual world.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Discover // Define ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3108&t=jRTjE5JDjxvV23M4-4 Ecosystem Loops] ====
[[File:Ecosystem Loops.png|alt=Ecosystem Loops|thumb|356x356px|Ecosystem Loops - CC BY-NC-SA 4.0]]
Ecosystem Loops is an immersive mapping tool that visualizes complex service ecosystems across multiple scales—users, stakeholders, partner networks, objects, and environments—within virtual worlds. Participants arrange and connect 3D tokens or avatars to represent entities and draw animated flows that trace value exchanges, information transfers, and dependencies.

By toggling between micro-interactions and macro-system overviews, teams uncover feedback loops, bottlenecks, and leverage points in real time. Ideal for VR or spatial 3D platforms, Ecosystem Loops fosters high collaboration as stakeholders co-create and manipulate the living system model together. This method drives holistic insight, aligns diverse perspectives, and informs resilient, scalable service design strategies.

'''How to use it?'''

* Identify the main areas of interest and related topics as sub-areas, if needed.
* Identify relevant stakeholders and potential users and place them in the map.
* Define connections of different types between them to create an ecosystem.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Define ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-11&t=jRTjE5JDjxvV23M4-4 Co-creating Journey Maps] ====
[[File:Co-creating Journey Maps.png|alt=Co-creating Journey Maps|thumb|352x352px|Co-creating Journey Maps - CC BY-NC-SA 4.0]]
Co-creating Journey Maps harnesses the collective expertise of invited participants to collaboratively construct detailed customer journeys within immersive virtual environments. Participants embody avatars representing diverse user roles and pool first-hand insights, documenting touchpoints, pain points, emotional states, and backstage processes along a shared 3D timeline. As contributors add and cluster digital sticky notes, icons, and sketches, the group iterates on journey phases, pauses to explore branching scenarios, and surfaces opportunities for innovation.

Live annotation, voting, and role-swapping ensure diverse perspectives shape the narrative. Ideal for VR or spatial collaboration platforms, Co-creating Journey Maps fosters deep empathy, aligns stakeholder understanding, and accelerates co-design of optimized end-to-end service experiences.

'''How to use it?'''

# Break down the user Journey of the project in steps and list them in the purple slots.
# Define dimensions such as Physical/digital Touchpoints, Negative/Positive Experience etc... and list them in the slots on the left
# Place relevant User acticities across the canvas, mapping the journey of the user with a conenction line.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-57&t=jRTjE5JDjxvV23M4-4 Co-creating Personas] ====
[[File:Co-creating Personas.png|alt=Co-creating Personas|thumb|345x345px|Co-creating Personas - CC BY-NC-SA 4.0]]
Co-creating Personas is a collaborative method that leverages the collective expertise of invited participants to develop rich, context-driven user archetypes and associated journey maps or service blueprints in virtual worlds. Workshop attendees assume avatar roles representing target segments and co-design persona profiles by contributing real-world insights, behaviors, motivations, and pain points.

As personas crystallize, teams animate them through scenario enactments, roleplay, and narrative sessions to validate assumptions and uncover hidden needs. This immersive approach fosters shared ownership, aligns diverse stakeholders, and embeds empathy throughout the design process. Flexible for VR or 3D desktop platforms, Co-creating Personas drives depth, nuance, and stakeholder buy-in.

'''How to use it?'''

# Identify relevant stakeholders to analyze and meaningful personas.
# Define an archetype for your persona.
# Describe the motivations that move the user.
# Describe the pain points the persona could encounter.
# Decorate with emojis/images the picture of the persona to better define its profile.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-115&t=jRTjE5JDjxvV23M4-4 Co-Creative Workshops] ====
[[File:Co-Creative Workshops.png|alt=Co-Creative Workshops|thumb|343x343px|Co-Creative Workshops - CC BY-NC-SA 4.0]]
Co-creative Workshops leverage the expertise of invited stakeholders to jointly develop rich personas and service artifacts within virtual worlds. Participants adopt avatar identities aligned with target segments and contribute real-world observations, motivations, behaviors, and pain points through interactive exercises.

As the group clusters and refines characteristics, they animate personas in scenario enactments to validate assumptions and reveal hidden needs. Facilitators guide collaborative storytelling, encourage role-swapping, and capture emergent themes on 3D canvases. Ideal for VR or desktop 3D platforms, Co-creative Workshops foster shared ownership, deepen empathy, build consensus, and deliver nuanced personas that inform subsequent journey mapping, prototyping, and co-design activities.

'''How to use it?'''

# Select a topic of discussion
# Assign to each participant a role from the archetype wheel and list it in the boxes.
# Identify a reporter of the discussion.
# Start the discussion and make sure every participant is interpreting the point of view of their archetype.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-242&t=jRTjE5JDjxvV23M4-4 Emotional Journey Map] ====
[[File:Emotional Journey Map.png|alt=Emotional Journey Map|thumb|340x340px|Emotional Journey Map - CC BY-NC-SA 4.0]]
Emotional Journey maps shifts in user perception and emotional valence across a service experience in a virtual world. Designers plot rising and falling emotional states along a spatial timeline using 3D curves or color-coded overlays. During scenario enactments, avatars display real-time emotional cues—gestures, facial animations, environmental feedback—which observers annotate to pinpoint stress peaks, delight moments, or ambivalence.

Through iterative replay, teams co-design interventions to smooth pain points and amplify positive highlights. Ideal for VR or immersive 3D platforms, Emotional Journey fosters deep empathy by externalizing subjective experience, aligning stakeholders around shared emotional insights, and driving targeted, affective service improvements.

'''How to use it?'''

# Break down the user Journey of the project in steps and represent them in the slots.
# Following the User Journey above, represent with a line the emotions the user feels while going through its journey.
# For every significant emotional step, note down which opportunities emerge.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-293&t=jRTjE5JDjxvV23M4-4 Impact Journey] ====
[[File:Impact Journey.png|alt=Impact Journey|thumb|340x340px|Impact Journey - CC BY-NC-SA 4.0]]
Impact Journey is a foresight tool that models and evaluates effects of a service experience across environmental, social, and economic dimensions in an interactive virtual world. Participants enact key touchpoints as avatars—customers, service personnel, suppliers—while indicators trace resource consumption, waste streams, community benefits, and carbon footprints along the timeline.

Observers pause and propose sustainable alternatives—material substitutions, process optimizations, circular loops—and visualize their impact using dynamic overlays. By embedding sustainability metrics into storytelling and roleplay, Impact Journey fosters empathy, uncovers unintended consequences, and generates actionable creative ideas for sustainable, resilient service ecosystems. Ideal for VR workshops on sustainable innovation.

'''How to use it?'''

# Break down the System Phases of the project in steps and list them in the slots on the left.
# Define meaningful areas of impact for the project such as environment, society, economy etc... and list them.
# For every area, define metrics of evaluation such as resource consumption, waste streams, community benefits, carbon footprints etc... and list them.
# Crossing the system phases of your project and the areas of impact, define (when necessary) relevant sustainable alternatives for the current solutions.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-356&t=jRTjE5JDjxvV23M4-4 Mapping Journeys] ====
[[File:Mapping Journeys.png|alt=Mapping Journeys|thumb|338x338px|Mapping Journeys - CC BY-NC-SA 4.0]]
Mapping Journeys visualizes the service ecosystem around physical and digital products by creating spatial, interactive maps in VR or 3D platforms. Participants drag and connect avatars, 3D tokens, or digital artifacts to represent users, touchpoints, channels, and product interactions across layered environments. As teams assemble and reposition elements, they surface dependencies, information flows, and ecosystem boundaries, running “what-if” experiments by introducing new nodes or rerouting connections.

Observers and co-creators annotate live, revealing optimization opportunities and integration points. While it offers limited narrative depth on its own, Mapping Journeys excels at immersive spatial analytics, fostering collaborative sense-making and aligning cross-functional teams around holistic service landscapes.

'''How to use it?'''

# Identify relevant actors to analyze (Users, Industries...).
# Identify relevant actions to analyze (Purchase, Log-in...).
# Identify relevant connections to analyze (Personal relationship, wi-fi connection...).
# Create as many user journeys as necessary for comparison and gather relevant insights from it.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-465&t=jRTjE5JDjxvV23M4-4 System Map] ====
[[File:System Map.png|alt=System Map|thumb|347x347px|System Map - CC BY-NC-SA 4.0]]
System Map is an immersive spatial tool for visualizing all actors and components involved in service delivery within virtual worlds. Designers create a shared 3D canvas where avatars or tokens represent users, frontline staff, support systems, digital platforms, and environmental elements.

Participants drag, position, and link these modules to trace information flows, handoffs, and boundaries between subsystems. Observers could filter layers, highlight dependencies, and annotate friction points in real time.

While direct roleplay is minimal, teams can embed scenarios by triggering animations or path simulations. Ideal for VR or desktop-based 3D workshops, System Map fosters clarity of complex architectures, aligns cross-functional understanding, and informs optimization strategies.

'''How to use it?'''

# Identify relevant actors to analyze (Users, Industries...).
# Identify relevant touchpoints to analyze (Social media engagement, in-person interactions...).
# Identify relevant connections to analyze (Personal relationship, wi-fi connection...).
# Add all the element in the map and profile a comprehensive system.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-565&t=jRTjE5JDjxvV23M4-4 System Scenario] ====
[[File:System Scenario.png|alt=System Scenario|thumb|349x349px|System Scenario - CC BY-NC-SA 4.0]]
System Scenario is a dynamic simulation tool that models how a service ecosystem adapts and evolves under specific conditions. In a virtual 3D or VR environment, participants configure scenario parameters—seasonal demand spikes, regulatory shifts, tech failures—and watch animated system components (avatars, processes, data flows) respond in real time.

Observers can pause, tweak variables, and branch into alternative futures to test resilience and spot emergent behaviors.

Ideal for avatar-driven storytelling and scenario planning in immersive platforms, System Scenarios deepen understanding of systemic dynamics, foster collaborative “what-if” exploration, and surface strategic interventions before real-world rollout.

'''How to use it?'''

# Define a scenario and express it with a What-if formula
# Give a title to the scenario.
# Define and prioritize relevant actors.
# Place them in the map and define their connections.
# Identify emerging pain points and opportunities.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-636&t=jRTjE5JDjxvV23M4-4 Transition Journey] ====
[[File:Transition Journey.png|alt=Transition Journey|thumb|339x339px|Transition Journey - CC BY-NC-SA 4.0]]
Transition Journey is a dynamic tool that maps and analyzes how user behavior and roles evolve over time within a service ecosystem. In virtual worlds, participants embody avatars that transition through sequential personas—novice to expert, customer to advocate—navigating branching scenarios that illustrate changing motivations, skills, and expectations.

Teams simulate multiple horizons and tweak transition triggers (feature rollouts, policy shifts, social influences) in real time, uncovering new experience archetypes and potential friction points. Observers pause, annotate, and co-design adaptive interventions on the fly.

Ideal for immersive VR workshops, Transition Journey combines narrative forecasting with spatial roleplay to drive strategic foresight and align stakeholders around future-ready service roadmaps.

'''How to use it?'''

# Define the target user.
# Identify their motivations and pain points.
# Define multiple possible user journeys.
# Use transition arrows to explore where the journeys could transit, in order to discover pain points and opportunities.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Develop ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3164&t=jRTjE5JDjxvV23M4-4 AI Functionalities Cards] ====
[[File:AI Functionalities Cards.png|alt=AI Functionalities Cards|thumb|335x335px|AI Functionalities Cards - CC BY-NC-SA 4.0]]
AI Functionalities Cards are a spatial ideation tool designed to spark innovation by showcasing modular AI capabilities—natural language processing, computer vision, recommendation engines, anomaly detection, and more—as tangible cards in virtual environments. Participants navigate VR or 3D workspaces where avatars draw from a digital deck of functionality cards, combining and placing them along service journeys or ecosystem maps.

Through iterative play, teams discover novel applications, align technical possibilities with user needs, and generate creative service enhancements. Ideal for immersive brainstorming sessions, AI Functionalities Cards democratize AI knowledge, foster cross-disciplinary collaboration, and accelerate the translation of emerging technologies into practical, user-centered service concepts.

'''How to use it?'''

# After defining your project, identify which category of AI could be implemented among the four.
# Use the AI functionalities cards to gain knowledge and inspiration for AI integration.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3250&t=jRTjE5JDjxvV23M4-4 Concept Walkthrough] ====
[[File:Concept Walkthrough.png|alt=Concept Walkthrough|thumb|335x335px|Concept Walkthrough - CC BY-NC-SA 4.0]]
Concept Walkthrough is a guided, immersive, step-by-step 3D or VR tour that presents a service concept through sequential stages, enabling stakeholders to experience proposed features and flows in context. Creators animate avatars or interactive hotspots to demonstrate each touchpoint—from discovery to service completion—while participants observe, comment, and suggest ongoing improvements in real time.

By visualizing the envisioned journey step by step, teams gain early user feedback, validate assumptions, and align on requirements before heavy investment. Ideal for VR-enabled workshops or desktop co-creation sessions, Concept Walkthroughs offer moderate immersion, clarity of vision, and structured, seamless collaboration to refine service concepts collaboratively.

'''How to use it?'''

# Define the user journey of your project.
# Use text to define every step of the journey.
# Use drawing/images to add details to every step, paying attention to the crucial steps of the journey.
# Note down pain point and opportunities emerging.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3299&t=jRTjE5JDjxvV23M4-4 Ecosystem Map] ====
[[File:Ecosystem Map .png|alt=Ecosystem Map|thumb|335x335px|Ecosystem Map - CC BY-NC-SA 4.0]]
The Ecosystem Map is an immersive, synthetic visualization that captures all stakeholders and value exchanges within a service ecosystem. Participants arrange avatars or 3D tokens to represent individuals, organizations, technological components, and environmental elements in a looping network, then animate flows to trace information, resource, or interaction exchanges.

In VR or 3D platforms, collaborators navigate the spatial model, simulate adding or removing nodes, and observe systemic impacts in real time. Observers annotate insights and co-design strategic interventions on the fly. Perfect for high-collaboration workshops, the Ecosystem Map aligns diverse perspectives, uncovers hidden relationships, and drives holistic service strategy through richly immersive co-creation.

'''How to use it?'''

# Define a central user and put it at the center of the canvas.
# Describe relevant players and associate to each a different shape.
# Place shapes in the map.
# Central players should be placed close to the center, secondary players peripherically.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3340&t=jRTjE5JDjxvV23M4-4 Future Backcasting] ====
[[File:Future Backcasting.png|alt=Future Backcasting|thumb|332x332px|Future Backcasting - CC BY-NC-SA 4.0]]
Future Backcasting is a foresight tool that reverses time to identify pathways from desired future outcomes back to present-day actions within virtual worlds. Participants embody avatars representing future stakeholders to enact scenarios in 3D or VR environments, dramatizing how emerging trends and innovations influence service evolution.

By simulating and discussing milestones—policy shifts, technological breakthroughs, user behaviors—teams map backward through decision points, uncovering present-day interventions and design inspirations. This method fosters long-term thinking, anticipates challenges, and aligns organizational vision by translating futures into actionable roadmaps. Ideal for co-creative workshops in VR or virtual platforms, Future Backcasting drives foresight and strategic innovation.

'''How to use it?'''

# Identify a relevant topic or a relevant industry.
# Define a year in the future to set the backcasting.
# Decide in which category of future (Possible, Plausible, Probable, Preferred) the backcasting will be set.
# Describe the foresight.
# Describe which steps are needed to achieve the foresight.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3391&t=jRTjE5JDjxvV23M4-4 System UX Map Human Agent Journey] ====
[[File:System UX Map Human Agent Journey.png|alt=System UX Map Human Agent Journey|thumb|335x335px|System UX Map Human Agent Journey - CC BY-NC-SA 4.0]]
Human Agent Journey visualizes the step-by-step path a person takes to achieve a goal, illustrating agent, scenario, expectations, phases, actions, and insights in an immersive virtual environment. Participants embody an avatar representing the human agent and progress through journey stages—awareness, exploration, decision, fulfillment, and reflection—within a shared 3D or VR space.

Observers annotate key touchpoints, emotional states, and backstage processes in real time, then pause to highlight pain points or design opportunities. By spatializing each phase and mapping opportunities directly onto the journey, this method fosters empathy, aligns stakeholders around human motivations, and accelerates co-creation of service experiences shaped by real user needs.

'''How to use it?'''

# Define a human agent (user)
# Identify a scenario and expectations
# Break down the user journey in phases and list them.
# Define which actions (High-level behaviors and steps taken by users. They have a narrative scope, they're not meant to be a step-by-step log of every discrete interaction) the human agent will perform.
# Identify emerging opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3444&t=jRTjE5JDjxvV23M4-4 Future-State Journey] ====
[[File:Future-State Journey.png|alt=Future-State Journey|thumb|332x332px|Future-State Journey - CC BY-NC-SA 4.0]]
Future-State Journey uses narrative structures to guide co-creative exploration of envisioned service experiences. Participants apply the classic dramatic arc—exposition, rising action, climax, falling action, resolution—to a future-state customer journey mapped three to five years ahead. In virtual 3D or VR environments, collaborators embody avatars to spatialize journey stages, enact critical moments, and iterate plot-driven touchpoints.

By dramatizing emotional peaks and challenges, teams spark innovative ideas, uncover pivotal design opportunities, and maintain focus on strategic objectives. Ideal for immersive workshops, this method balances storytelling, spatial roleplay, and moderate collaboration, facilitating cohesive stakeholder alignment and rapidly accelerating future-focused ideation.

'''How to use it?'''

# Define a user journey or, if present, consider an existing one for this exercise. Focus on the emotional peaks and challenges arising from the experience.
# Identify where there is room for Jobs To Be Done (JTBD) and highlight it on the map .
# Now, rework the user journey imagining the experience in the future. How can JTBD be addressed by future developments?
# Identify which are the emerging opportunities.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3625&t=jRTjE5JDjxvV23M4-4 Innovative Brainstorming] ====
[[File:Innovative Brainstorming.png|alt=Innovative Brainstorming|thumb|334x334px|Innovative Brainstorming - CC BY-NC-SA 4.0]]
Innovative Brainstorming is an inclusive, fast-paced ideation technique that stimulates spontaneous thought by leveraging spatialized virtual tools and avatar-led interaction. In a VW workshop, participants converge on a shared digital whiteboard or 3D canvas, where facilitators introduce provocations, constraints, or stimulus cards.

Avatars then rapidly generate, cluster, and remix ideas through drawing, tagging, and connecting virtual sticky notes, while voice or gesture commands add energy and variety. Real-time voting and theme-based breakout areas help surface promising concepts. By combining classic free-form brainstorming with immersive, gamified mechanics, Innovative Brainstorming boosts engagement, taps collective creativity, and fuels a rich pipeline of breakthrough service innovations.

'''How to use it?'''

# Define a topic to brainstorm.
# Brainstorm any idea related to the topic in question in the warming up section.
# Select ideas within close personal or obvious contexts and list them in the braindump section.
# Use braindump ideas to inspire new ideas going in different . directions and list them in the divergent thinking section.
# Use the most promising ideas from the divergent thinking section to create new creative ideas in the creative ideation section.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3646&t=jRTjE5JDjxvV23M4-4 Integrated Journey] ====
[[File:Integrated Journey.png|alt=Integrated Journey|thumb|329x329px|Integrated Journey - CC BY-NC-SA 4.0]]
Integrated Journey extends traditional journey mapping into a comprehensive service blueprint within virtual worlds, visualizing customer touchpoints alongside backstage processes, technology systems, and stakeholder roles. In an immersive 3D environment, designers arrange avatars, swimlanes, and interactive nodes on a shared timeline to show how front-stage interactions trigger behind-the-scenes support functions and data flows.

Participants witness real-time animations of handoffs, decision points, and policy enforcements, pausing to annotate inefficiencies or propose enhancements. Avatars can enact role-specific perspectives—agent, IT, logistics—adding realism. Perfect for VR-enabled co-creation workshops, Integrated Journey aligns multidisciplinary teams, uncovers interdependencies, and accelerates holistic service innovation.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Define, for each phase, the technical journey (Steps and activities that the technical artifact performs behind the scenes to support interactions with/between human agents.)
# Define, for each phase, the provider journey (Steps, choices, activities, and interactions that providers perform while offering a service to reach a particular goal, they can be visible to users or performed in the back-end / asynchronously).
# Identify emerging opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3712&t=jRTjE5JDjxvV23M4-4 Journey Ideation with Dramatic Arcs] ====
[[File:Journey Ideation with Dramatic Arcs.png|alt=Journey Ideation with Dramatic Arcs|thumb|330x330px|Journey Ideation with Dramatic Arcs - CC BY-NC-SA 4.0]]
Journey Ideation with Dramatic Arcs is a co-creation method that applies narrative structures to service design in virtual worlds. Teams leverage classic dramatic arcs to outline user journeys, mapping emotional peaks and transitions across touchpoints.

In immersive 3D or VR environments, participants embody avatars to spatialize journey stages, visually enact pivotal moments, and explore plotlines. Observers refine service concepts by injecting unexpected challenges, resolving friction, and imagining future scenarios.

This approach deepens empathy, sparks insights, and aligns stakeholders around rich narratives. Ideal for future-focused workshops, it transforms abstract journeys into engaging storyworlds for iterative ideation.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Color the numbers ranking the customer engagement levels of every step of your journey from 1 (Low) to 6 (High).
# Reflect on the shape and rhythm of the whole arc. Is it overloaded? Frontloaded? Are the periods of low engagement or high engagement too long?
# Must a highlight be added, or - this is often more practical - should a less engaging step be spotlighted to increase engagement and show value more clearly?

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing
Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3856&t=jRTjE5JDjxvV23M4-4 Service Image] ====
[[File:Service Image.png|alt=Service Image|thumb|329x329px|Service Image - CC BY-NC-SA 4.0]]
Service Image distills the essence of a service experience into a single, impactful visual snapshot within a virtual world. Designers stage a 3D scene with avatars, environmental cues, and animated highlights to convey core touchpoints and emotional tone at a glance. This diorama-style frame employs perspective, lighting, and symbolic elements to communicate user motivations, pain points, and moments of delight cohesively.

By presenting an evocative north-star vision, Service Image aligns stakeholders around the narrative, sparks creative ideation, and guides subsequent design iterations. Ideal for kickoff sessions, pitches, and virtual galleries, it crystallizes complex experiences into an instantly sharable form.

'''How to use it?'''

# Create a service image, it can be a montage of different photos and scenes, or a post-produced photo realized ad hoc, focused on a hero moment that is able to encapsulate the core value of the service experience.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3868&t=jRTjE5JDjxvV23M4-4 System UX Map Artificial Agent Journey] ====
[[File:System UX Map Artificial Agent Journey.png|alt=System UX Map Artificial Agent Journey|thumb|326x326px|System UX Map Artificial Agent Journey - CC BY-NC-SA 4.0]]
System UX Map Agent Journey visualizes AI/ML system interactions and human collaboration within virtual worlds. Participants guide avatars representing data pipelines, models, and human operators across a spatial timeline that highlights when core AI elements—data ingestion, feature engineering, model training, inference—are generated and required.

Relationships between automated agents and human stakeholders are dynamically mapped, enabling stakeholders to pause, annotate, and adjust nodal connections in real time. Ideal for VR or 3D workshops with multidisciplinary teams, this tool clarifies technical workflows, uncovers integration bottlenecks, and fosters shared understanding. By combining agent-driven storytelling with immersive simulation, teams co-design robust, human-centered AI services.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Define, for each phase, the technical journey (Steps and activities that the technical artifact performs behind the scenes to support interactions with/between human agents).
# Define, for each phase, the artificial journey (Internal processes and interactions that support service delivery through the technical artifact. They involve the agency of Al systems).
# Identify emerging opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3935&t=jRTjE5JDjxvV23M4-4 User Scenario] ====
[[File:User Scenario.png|alt=User Scenario|thumb|335x335px|User Scenario - CC BY-NC-SA 4.0]]
User Scenarios bring envisioned service experiences to life through compelling narratives that follow a user’s journey in context. In a virtual 3D or VR environment, avatars embody personas and enact stories that illustrate goals, motivations, and pain points at each stage of interaction—discovery, decision, execution, and reflection.

Observers and co-designers watch, annotate, and pause the action to probe underlying assumptions, explore alternative paths, or inject new ideas. By weaving storytelling with spatial simulation, User Scenarios deepen empathy, align stakeholder mental models, and reveal hidden requirements. Ideal for co-creative workshops in immersive platforms, User Scenarios seamlessly integrate simulation, roleplay, and narrative ideation into service design.

'''How to use it?'''

# Define a context for each scenario.
# Define the characters (e.g. users, providers...) involved in the scenario.
# Identify the needs involved.
# Writing a story, define a user scenario in a narrative manner, focusing in describing how the user is going to interact with the service during a specific situation of everyday life.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Develop // Deliver ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3996&t=jRTjE5JDjxvV23M4-4 Rough Prototyping] ====
[[File:Rough Prototyping.png|alt=Rough Prototyping|thumb|330x330px|Rough Prototyping - CC BY-NC-SA 4.0]]
Rough Prototyping is a rapid, low-fidelity method for mocking up service ideas using simple virtual assets available on demand in VR or 3D platforms. Teams embody avatars that assemble, rearrange, and annotate digital placeholders—such as basic shapes, sketch overlays, or interactive widgets—to explore concepts in real time.

By minimizing production effort, participants test multiple variations, iterate service touchpoints, and gather immediate feedback without heavy technical overhead. Although roleplay depth is limited compared to immersive simulations, Rough Prototyping excels at fostering spontaneous creativity, aligning stakeholder understanding, and validating design assumptions. This high-velocity approach empowers teams to quickly brainstorm and converge collaboratively.

'''How to use it?'''

# Define, which are the main touchpoints (Devices, places, tools, perceivable clues that users interact with) involved in the project.
# For each touchpoint, define the technical requirements.
# Create paper/digital mockups for all the touchpoints and start experimenting/testing the user journey.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-4026&t=jRTjE5JDjxvV23M4-4 Experience Prototypes] ====
[[File:Experience Prototypes.png|alt=Experience Prototypes|thumb|322x322px|Experience Prototypes - CC BY-NC-SA 4.0]]
Experience Prototypes are interactive simulations of key service touchpoints within virtual worlds. They let teams rapidly prototype and test specific moments in a journey—such as checkout kiosks, support chatbots, or onboarding flows—by building high-fidelity mock-ups in VR or 3D spaces.

Participants embodied as avatars interact with digital artifacts, providing real-time feedback on usability, emotional resonance, and process efficiency. Through iterative cycles, designs are refined on the fly, uncovering hidden pain points and validating solutions before development. Ideal for virtual co-design workshops, Experience Prototypes enhance immersion, align stakeholders around tangible interactions, and accelerate service innovation within a holistic end-to-end context.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Prototype, for each phase, the user journey and start experimenting/testing the touchpoints.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-4074&t=jRTjE5JDjxvV23M4-4 Role Playing] ====
[[File:Role Playing.png|alt=Role Playing|thumb|320x320px|Role Playing - CC BY-NC-SA 4.0]]
Role Playing brings a hypothetical service to life through avatar enactment in virtual worlds. Users assume persona roles—customers, frontline staff, or partners—and act out journey scenarios in immersive VR or 3D environments. As avatars, participants navigate scripted or spontaneous interactions, responding to prompts, making decisions, and adapting to system feedback.

Observers can pause, annotate, and adjust scenarios on the fly to explore alternative behaviors, emotional responses, and process variations. This high-engagement method fosters deep empathy, surfaces usability issues, and validates service flows before development. Ideal for remote co-creation workshops, Role Playing aligns multidisciplinary teams around user perspectives and informs iterative design improvements.

'''How to use it?'''

# Create a scenario: define the context, the characters and the needs involved and narrate through a story the scene.
# Define some roles (e.g. the user, the service employee, etc.) and assign them to the participants.
# If needed, prepare rough prototypes or other materials that can facilitate the performance.
# While a team is acting out their story, the rest of the audience learn about the idea, understand the high-level sequence of actions required and get to know the hero moments.
# List the hero moment(s).

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Deliver ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-821&t=jRTjE5JDjxvV23M4-4 Desktop System Mapping] ====
[[File:Desktop System Mapping.png|alt=Desktop System Mapping|thumb|322x322px|Desktop System Mapping - CC BY-NC-SA 4.0]]
Desktop System Mapping, known as Business Origami, is a tactile method for visualizing complex value networks by arranging simple paper cutouts—or, in virtual worlds, draggable avatars and 3D tokens—on a shared collaborative workspace. Participants represent key people, locations, channels, and touchpoints with standardized symbols, connecting elements to reveal relationships, dependencies, and information flows.

In VR or immersive 3D platforms, collaborators reposition tokens, annotate linkages, and simulate network changes in real time. This approach clarifies service ecosystems, aligns stakeholder mental models, and fosters collective sense-making. Desktop System Mapping excels at uncovering structural insights, driving collaborative strategy, and achieving strategic alignment.

'''How to use it?'''

# Define the main scope of your prototype
# Define the level of detail of the prototype
# Create paper/digital cutouts of the prototype and start testing/simulate talking points using the models on the table.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-854&t=jRTjE5JDjxvV23M4-4 Desktop Walkthrough] ====
[[File:Desktop Walkthrough.png|alt=Desktop Walkthrough|thumb|320x320px|Desktop Walkthrough - CC BY-NC-SA 4.0]]
Desktop Walkthrough is a low-fidelity prototyping tool that brings teams together around a shared simulation of a service journey in a virtual world. Participants embody avatars to step through each critical touchpoint—sign-up, payment, support—while observers annotate pain points, decision triggers, and contextual cues.

By projecting simple mock-ups of screens, environments, and process steps into a 3D or VR space, teams quickly gain a unified understanding of end-to-end experiences and surface hidden issues. Iterative “play-throughs” enable real-time adjustments to sequences, handoffs, and interface layouts. Ideal for early-stage co-creation workshops, Desktop Walkthrough accelerates alignment, empathy, and rapid identification of critical journey enhancements.

'''How to use it?'''

# Define the user journey of your project and create a visual representation of it using emojis/imported images

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1021&t=jRTjE5JDjxvV23M4-4 Emotional Journey Feedback] ====
[[File:Emotional Journey Feedback.png|alt=Emotional Journey Feedback|thumb|317x317px|Emotional Journey Feedback - CC BY-NC-SA 4.0]]
Emotional Journey Feedback extends the System UX Map by overlaying users’ emotional states across every phase of their experience in virtual worlds. A continuous “emotion line” traces peaks and valleys—signaling stress points, moments of delight, and transitional shifts—plotted along a spatialized service timeline.

In VR or 3D environments, avatars convey real-time emotional cues through gestures, facial expressions, or ambient lighting changes that correspond to the graph. Participants can pause, annotate, and iterate scenarios to smooth pain points or amplify positive highlights. Ideal for immersive co-design workshops, this tool deepens empathy, enhances feedback loops, and strengthens narrative-driven storytelling in service innovation.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Define, for each phase, the technical journey (Steps and activities that the technical artifact performs behind the scenes to support interactions with/between human agents.)
# For each step, consider the emotional feedback of the user and keep track of it in the canvas.
# Identify emerging pain points and opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1081&t=jRTjE5JDjxvV23M4-4 Investigative Rehearsal] ====
[[File:Investigative Rehearsal.png|alt=Investigative Rehearsal|thumb|316x316px|Investigative Rehearsal - CC BY-NC-SA 4.0]]
Investigative Rehearsal is a theatrical tool that uses iterative roleplay to uncover and refine service behaviors within virtual worlds. Participants embody avatars to act out scenarios—customer interactions, back-end workflows, decision points—while observers note emergent patterns and friction points.

Through multiple rehearsal loops, teams adjust roles, scripts, and environment affordances in real time, testing alternative responses and process variations. This method fosters deep empathy, reveals implicit knowledge, and surfaces systemic issues that workshops might miss. Ideal for VR or richly immersive 3D platforms, Investigative Rehearsal accelerates behavioral insight, aligns stakeholder mental models, and co-designs optimized service experiences grounded in lived enactment.

'''How to use it?'''

# Define the scene and research question.
# Assign actors with roles and scenario details.
# Observers watch a brief scene enactment.
# Observers reflect on current knowledge and feelings.
# Replay the scene, pausing to suggest changes and improvements.
# Document observations and insights throughout.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1136&t=jRTjE5JDjxvV23M4-4 Rehearsing Digital Services] ====
[[File:Rehearsing Digital Services.png|alt=Rehearsing Digital Services|thumb|319x319px|Rehearsing Digital Services - CC BY-NC-SA 4.0]]
Rehearsing Digital Services is a variant of Investigative Rehearsal that prototypes digital interfaces through embodied, actor-led simulations in virtual worlds. Participants—represented as avatars—take on customer, agent, or system roles and act out conversational and transactional flows: chatbot dialogs, voice assistants, form interactions, and error recoveries.

Facilitators guide scenarios in VR or 3D platforms, narrating screen states and system prompts aloud as avatars interact with on-screen elements. Iterative enactments expose usability gaps, friction points, and emotional reactions, enabling real-time script tweaks, UI refinements, and branching-logic tests. Ideal for immersive co-creation workshops, Rehearsing Digital Services drives shared understanding, empathy, and alignment around seamless digital service experiences.

'''How to use this?'''

# Define the scene and research question.
# Assign roles and outline the scenario.
# Have teams act out the scene briefly to observe.
# Observe, understand feelings and current dynamics.
# Iterate by pausing and suggesting changes focused on service digitalization.
# Reflect on how to digitally transform and enact the service experience.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1193&t=jRTjE5JDjxvV23M4-4 Service Blueprint] ====
[[File:Service Blueprint.png|alt=Service Blueprint|thumb|316x316px|Service Blueprint - CC BY-NC-SA 4.0]]
Service Blueprint is a comprehensive mapping technique that visualizes every stage of service delivery—front-stage interactions, backstage processes, support systems, and physical or digital touchpoints—in a unified blueprint. In virtual environments, designers arrange swim-lane structures on a 3D canvas, deploying avatars to simulate customer and staff roles and animating process flows in real time.

Participants annotate decision gateways, handoffs, and dependencies while observing both visible and hidden service elements. This immersive representation reveals systemic inefficiencies, clarifies ownership, and guides co-design of seamless experiences. Ideal for VR or desktop-based co-creation workshops, Service Blueprint accelerates alignment, optimizes workflows, and de-risks implementation through collective visualization and iteration.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, a main user and secondary users and place them in the other areas.
# Consider the Interaction Area and place other entities the main user interacts with and the Visibility Area and place players, functionalities invisible to the user.
# Map connection between the users and define the project ecosystem.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1226&t=jRTjE5JDjxvV23M4-4 Service Prototype] ====
[[File:Service Prototype.png|alt=Service Prototype|thumb|312x312px|Service Prototype - CC BY-NC-SA 4.0]]
Service Prototype simulates real user interactions with service touchpoints in virtual environments. Designers create interactive mock-ups—digital kiosks, chatbots, mobile interfaces—and deploy them in VR or 3D worlds.

Participants embody avatars to engage with prototypes as they would in real life: querying a virtual assistant, placing an order through a mock interface, or interacting with augmented customer support. Real-time feedback sessions record usability metrics, emotional reactions, and friction points. Iterative cycles refine prototypes, ensuring functionality, aesthetics, and experience quality align with user expectations. Perfect for immersive co-creation workshops, Service Prototypes accelerate validation, enhance stakeholder feedback, and de-risk service launch.

'''How to use it?'''

# Define a precise User Journey and describe it in steps.
# Assign roles to participants.
# Choose touchpoints to be prototyped.
# Reenact the service using the prototypes. This tool has the objective of replicating, as much as possible, the final experience of interacting with the service, in order to test and validate all the design choices.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1300&t=jRTjE5JDjxvV23M4-4 Subtext] ====
[[File:Subtext.png|alt=Subtext|thumb|316x316px|Subtext - CC BY-NC-SA 4.0]]
Subtext is a theatrical method that can reveal deeper motivations and needs by focusing on unspoken thoughts in a rehearsal session.

Perfect for exploring non-verbal communication and emotions in VW rehearsals; enhances depth of co-creative exploration.

'''How to use it?'''

# Choose a key scene you want to understand more deeply
# Select and assign roles of actors, who will play the key scene once.
# Select and assign roles of subtext actors for each actor.
# The character actors will play the scene as usual – or perhaps a little slower – and the subtext actors will simply speak what they believe their characters are thinking at any moment, using “I” or “me” statements when possible. For example, the character actor might say, “Can you prioritize that?” and his subtext actor might rage, “For f*ck’s sake! Help me before I lose my job, you idiot!”
# Iterate.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

Co-creation Toolkit

2026-09-02T08:14:03Z

CollectiveIntelligenceAdmin:

== A Toolkit for Co-Creation in Virtual Worlds ==
This page provides an overview and links to the co-creation tools developed by Politecnico di Milano in the context of the OPENVERSE project.
A core component of planning is the selection and contextual adaptation of co-creation tools. The OPENVERSE Toolkit includes a wide variety of such tools—a curated set of 48 co-creation tools mapped across the four phases of the [[wikipedia:Double_Diamond_(design_process_model)|Double Diamond]]—that support everything from early exploration to final decision-making.
[[File:Double diamond .png|alt=Image representing the Double Diamond design process model|center|thumb|790x790px|'''Double Diamond design process model''' Work by Politecnico di Milano, adapted from Design Council's original work - CC BY-NC-SA 4.0]]
The goal is to empower a diverse range of stakeholders—designers, developers, educators, VWs consumers, and citizens—to run meaningful co-creation processes in immersive environments, using a shared methodology grounded in field experimentation and design research.

<center>youtube width="100%" height="400">s2BpzupW5Qc</youtube></center>

The complete [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=0-1&p=f&t=djpkfnwCxadiCigO-0 Co-creation Toolkit] is available on the Figma platform.

<blockquote>
=== License and Attribution ===
This toolkit is designed for open collaboration, and its structure and licensing model are crafted to comply with the terms of all referenced source materials. The entire original content of this toolkit is licensed under [https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)].

The content of this toolkit is shared as CC BY-NC-SA 4.0. This license enables re-users to distribute, remix, adapt, and build upon this material in any medium or format for noncommercial purposes only, provided original attribution (BY) is always given.

Because this toolkit adopts the '''ShareAlike (SA)''' element, any new work created by adapting, remixing, or transforming the original licensed content from this toolkit must be distributed under the same or a compatible Creative Commons license.

Toolkit License: [https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en CC BY-NC-SA 4.0]

Designed in 2025 by: Riccardo Ventura, Ilaria Mariani, Venere Ferraro, Francesca Rizzo, Department of Design, Politecnico di Milano</blockquote><blockquote>
=== Source Material ===
This work includes content, methodologies, and inspiration drawn from the following sources:

* Adapted and Derivative Content (CC BY-NC-SA 4.0): Tools and methodologies were directly adapted, remixed, or inspired by materials from the AI4Gov Toolkit (CC BY-NC-SA 4.0) and Follow the Rabbit: A Field Guide to Systemic Design (CC BY-NC-SA 4.0). Due to this adaptation, the ShareAlike condition of these source licenses requires that this resulting toolkit must also adopt the CC BY-NC-SA 4.0 license.
* Inspirational Use Only (Non-Derivative): The creation of our new tools, concepts, guides, and the overall structural approach were purely inspired by the materials presented in three other sources. This process involved consulting the Servicedesigntools (CC BY-NC-ND 2.5) repository, the This is Service Design Doing – Method Library (copyrighted content), and the Share, Learn, Innovate! toolkit (copyrighted content). The team behind this toolkit consulted these materials for guides, concepts, and structure but did not adopt, adapt, or create derivative versions of their original content
</blockquote>

=== Components of the Toolkit ===
All the components are available for exploration and reuse on the Figma board, along with the full description of each of the components. This page provides a high-level overview of the components for quick reference. The components are grouped based on the four Double Diamond phases shown above. In case of overlaps across the phases, the headings will show both relevant phases.

{| class="wikitable"
! style="background-color:#E400FF; color:#FFFFFF;" | Discover
! style="background-color:#B700FF; color:#FFFFFF;" | Define
! style="background-color:#9600FF; color:#FFFFFF;" | Develop
! style="background-color:#7200FF; color:#FFFFFF;" | Deliver
|-
| [[#Cultural Probes|Cultural Probes]] || [[#Co-creating Journey Maps|Co-creating Journey Maps]] || [[#Experience Prototypes|Experience Prototypes]] || [[#Desktop System Mapping|Desktop system mapping (a.k.a. Business Origami)]]
|-
| [[#Ecosystem Map|Ecosystem Map]] || [[#Co-creating Personas|Co-creating Personas]] || [[#Role Playing|Role Playing]] || [[#Desktop Walkthrough|Desktop Walkthrough]]
|-
| [[#Envisioning the Future|Envisioning the Future]] || [[#Co-Creative Workshops|Co-Creative Workshops]] || [[#AI Functionalities Cards|AI Functionalities Cards]] || [[#Emotional Journey Feedback|Emotional Journey Feedback]]
|-
| [[#Fishbowl|Fishbowl]] || [[#Emotional Journey Map|Emotional Journey Map]] || [[#Concept Walkthrough|Concept Walkthrough]] || [[#Investigative Rehearsal|Investigative Rehearsal]]
|-
| [[#Iceberg Diagram|Iceberg Diagram]] || [[#Impact Journey|Impact Journey]] || [[#Ecosystem Map|Ecosystem Map]] || [[#Rehearsing Digital Services|Rehearsing Digital Services]]
|-
| [[#Jigsaw|Jigsaw]] || [[#Mapping Journeys|Mapping Journeys]] || [[#Future Backcasting|Future Backcasting]] || [[#Service Blueprint|Service Blueprint]]
|-
| [[#Knowledge Café|Knowledge Café / Round Table Sessions]] || [[#System Map|System Map]] || [[#Human Agent Journey|Human Agent Journey]] || [[#Service Prototype|Service Prototype]]
|-
| [[#Knowledge Fair|Knowledge Fair]] || [[#System Scenario|System Scenario]] || [[#Future-State Journey|Future-State Journey]] || [[#Subtext|Subtext]]
|-
| [[#Open Space|Open Space]] || [[#Transition Journey|Transition Journey]] || [[#Innovative Brainstorming|Innovative Brainstorming]] || [[#Experience Prototypes|Experience Prototypes]]
|-
| [[#Problem Framing|Problem Framing]] || [[#Ecosystem Loops|Ecosystem Loops]] || [[#Integrated Journey|Integrated Journey]] || [[#Role Playing|Role Playing]]
|-
| [[#Service Safari|Service Safari]] || || [[#Journey Ideation with Dramatic Arcs|Journey Ideation with Dramatic Arcs]] || [[#Rough Prototyping|Rough Prototyping]]
|-
| [[#Social Network Analysis|Social Network Analysis]] || || [[#Service Image|Service Image]] ||
|-
| [[#Sociometrics|Sociometrics]] || || [[#System UX Map Agent Journey|System UX Map Agent Journey]] ||
|-
| [[#Stakeholder Map|Stakeholder Map]] || || [[#User Scenario|User Scenarios]] ||
|-
| [[#Stakeholder Value Map|Stakeholder Value Map]] || || [[#Rough Prototyping|Rough Prototyping]] ||
|-
| [[#Ecosystem Loops|Ecosystem Loops]] || || ||
|}

=== The Toolkit in action ===
The videos below, portraying the activities of seven co-creation groups, showcases the use of several of the components of the toolkit.
{| class="wikitable"
|-
| <youtube width="400" height="240">KPemYBWjAig</youtube>
| <youtube width="400" height="240">jRE2TEP59DQ</youtube>
|-
| <youtube width="400" height="240">hY5mLs9Erv8</youtube>
| <youtube width="400" height="240">c-xghyabhfU</youtube>
|-
| <youtube width="400" height="240">LG6s8NlbvJM</youtube>
| <youtube width="400" height="240">6tQQw2Wpyh0</youtube>
|-
| <youtube width="400" height="240">2r_BkoknYEY</youtube>
|
|}

=== Discover ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1396&t=jRTjE5JDjxvV23M4-4 Cultural Probes] ====
[[File:Cultural Probes.png|alt=Cultural probes|thumb|383x383px|Cultural probes - CC BY-NC-SA 4.0]]
Cultural Probes are stimuli-based design research tools that invite participants to document personal experiences, contexts, and thoughts through artifacts such as postcards, diaries, or in-world interactive objects. In immersive VW environments, designers distribute digital probes (VR postcards, 3D tokens, prompts) into user spaces.

Participants interact, capture audio/video responses, and and interactions in digital environments, and return probes for analysis. Through asynchronous co-creation, teams gather rich qualitative data, uncover emergent needs, and iteratively refine personas, journey maps, and system maps. Ideal for exploratory research in spatial VR or 3D platforms, Cultural Probes foster empathy, spark ideation, and ground service design in lived experiences.

'''How to use it?'''

# Decide which digital / physical objects could help users narrate their virtual worlds experiences.
# Ask users to take notes throughout the project.
# Use notes to gather useful insight for further improvement.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1545&t=jRTjE5JDjxvV23M4-4 Ecosystem Map] ====
[[File:Ecosystem Map.png|alt=Ecosystem Map|thumb|383x383px|Ecosystem Map - CC BY-NC-SA 4.0]]
Ecosystem Map portrays every entity, flow, and relationship that defines a service’s surrounding ecosystem in immersive three-dimensional space. Avatars or 3D tokens represent users, partners, suppliers, technologies, and environmental factors, while animated streams trace value exchanges, information channels, and resource movements.

Collaborators navigate the dynamic model, simulate changes—such as adding new nodes or rerouting flows—and observe systemic ripple effects in real time. Participants annotate insights, propose interventions, and iteratively refine connections. Perfect for VR-enabled co-creation workshops, Ecosystem Map fosters holistic understanding, surfaces hidden interdependencies, and aligns stakeholders around end-to-end service innovation strategies.

'''How to use it?'''

# Define a central topic and put it at the center of the canvas.
# Describe relevant players and associate to each a different shape.
# Place shapes in the map.
# Central players should be placed close to the center, secondary players peripherically.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1592&t=jRTjE5JDjxvV23M4-4 Envisioning the Future] ====
[[File:Envisioning the Future.png|alt=Envisioning the Future|thumb|380x380px|Envisioning the Future - CC BY-NC-SA 4.0]]
Envisioning the Future is a collaborative scenario-building tool that invites teams to imagine plausible worlds three to six years ahead within virtual environments. Participants embody avatars in detailed VR or 3D spaces, exploring future success states—streamlined operations, empowered customers, sustainable ecosystems.

During guided workshops, they define milestones, identify emerging trends, and co-create narratives that show how organizational goals materialize. By visualizing outcomes and backcasting interventions, Envisioning the Future fosters long-term strategic alignment, surfaces uncertainties, and sparks innovative service breakthroughs. Ideal for remote or hybrid teams, this method leverages immersive storytelling and collective foresight to translate visionary aspirations into actionable roadmaps.

'''How to use it?'''

# Select a timeframe fro 3 to 6 years.
# Answer to the provided questions.
# Describe as a scenario the vision.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1641&t=jRTjE5JDjxvV23M4-4 Fishbowl] ====
[[File:Fishbowl.png|alt=Fishbowl|thumb|371x371px|Fishbowl - CC BY-NC-SA 4.0]]
Fishbowl is an interactive dialogue technique that amplifies expert knowledge and broadens group understanding through a concentric-circle setup in virtual worlds.

In a central “bowl,” a handful of skilled avatars discuss targeted questions while an outer ring of observers listens, reflects, and captures insights on spatial whiteboards. When outer participants wish to contribute, they enter the bowl, temporarily swapping places with an inner speaker.

This fluid movement between inner and outer circles democratizes voice, encourages active listening, and fosters shared learning. Deployed in VR or 3D environments, Fishbowl’s structured yet flexible format drives deep engagement, peer teaching, and immersive co-creative exploration.

'''How to use it?'''

# Gather participants in a physical/virtual environment.
# Divide participants in 2 groups.
# Fishes (2-4 people): They have to discuss a relevant topic, at the center of the room.
# Observers (The rest of the participants): They have to take notes on the discussion and, if they wish to participate, respectfully interrupt the discussion, swapping places with a fish.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1691&t=jRTjE5JDjxvV23M4-4 Iceberg Diagram] ====
[[File:Iceberg Diagram.png|alt=Iceberg Diagram|thumb|369x369px|Iceberg Diagram - CC BY-NC-SA 4.0]]
An Iceberg Diagram visualizes beneath-the-surface forces that shape service behaviors by layering observable events, systemic structures, mental models, and underlying paradigms in a vertical 3D canvas. Participants position avatars or tokens at different strata—the tip of the iceberg representing customer actions, the submerged mass depicting processes, regulations, cultural beliefs, and deeper worldviews.

Collaborators drill down through scenarios in VR environments, annotating feedback loops, mental models, and leverage points that perpetuate current outcomes. Iterative exploration surfaces hidden constraints, reveals impactful intervention zones, and fosters systemic thinking. Ideal for immersive workshops, the Iceberg Diagram enables teams to align on root causes and co-design transformative strategies grounded in deep structural insight.

'''How to use it?'''

* Define a central topic.
* Compile brainstorm events section, highlighting relevant aspects.
* Compile patterns of behaviors section, highlighting repeating aspects.
* Compile system structures section, highlighting who/what is responsible for pattern creation.
* Compile mental models section, highlighting which assumptions and beliefs created the systemic structures.
* After looking at the big picture, place relevant aspects as icons in the iceberg.

<blockquote>Inspired by the toolkit: Follow the Rabbit Publisher: Colab

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1746&t=jRTjE5JDjxvV23M4-4 Jigsaw] ====
[[File:Jigsaw.png|alt=Jigsaw|thumb|366x366px|Jigsaw - CC BY-NC-SA 4.0]]
Jigsaw is a cooperative learning strategy adapted for virtual worlds that divides a complex service challenge into interlocking “puzzle pieces.” Small expert teams explore an assigned component—such as user research, technology integration, or policy constraints—and develop deep insights. Avatars reconvene in a shared 3D space to assemble findings, linking visual tokens, diagrams, and narratives to complete the holistic picture.

This method leverages spatial distribution, collaborative assembly, and peer teaching to build collective expertise and foster ownership. By transforming individual discoveries into a cohesive ecosystem map, Jigsaw enhances cross-functional understanding, drives mutual accountability, and accelerates integrated service design through immersive, puzzle-based co-creation.

'''How to use it?'''

# Divide participants in groups.
# Assign to each group a relevant topic/area to discuss
# Discuss in groups and keep track of the findings.
# Reassemble the pieces and discuss together the bigger picture.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1895&t=jRTjE5JDjxvV23M4-4 Knowledge Café] ====
[[File:Knowledge Café.png|alt=Knowledge Café|thumb|362x362px|Knowledge Café - CC BY-NC-SA 4.0]]
Knowledge Café or Round Table Sessions is an avatar-led dialogue method that builds collective intelligence in virtual worlds. Participants gather at themed café tables, sharing experiences and posting digital notes on shared canvases. After a timed session, avatars rotate to new tables, carrying forward insights and weaving ideas into a knowledge web.

Each table host curates threads and captures emergent patterns, ensuring continuity. By assuming that every participant is a source of wisdom, the format surfaces novel perspectives and cross-pollinates ideas across the group. Ideal for VR or 3D co-creation spaces, Knowledge Café fosters immersive collaboration and amplifies shared understanding.

'''How to use it?'''

# Gather participants in a shared collaborative setting.
# Define relevant topics of discussion.
# Define how much time to spend on each discussion before rotating.
# Divide participants in groups and ask each group to identify a reporter of the insights.
# Sit on the tables and start the timer, when time is off, rotate and change table/topic.
# After a full rotation, take some time to share what emerged from each topic between the groups.

<blockquote>Inspired by the toolkit: Follow the Rabbit Publisher: Colab

Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2041&t=jRTjE5JDjxvV23M4-4 Knowledge Fair] ====
[[File:Knowledge Fair.png|alt=Knowledge Fair|thumb|363x363px|Knowledge Fair - CC BY-NC-SA 4.0]]
Knowledge Fair is a virtual event for sharing insights from diverse experts through immersive booths, dynamic displays, and interactive presentations. In a 3D or VR expo hall, participants navigate avatar-driven pavilions themed around specific domains—data privacy, user research, policy design—and engage with multimedia panels showcasing research findings, prototypes, and case studies.

Exhibitors use digital posters, video kiosks, live demos, and spatial annotations to spark dialogue and crowdsourced ideation. Roleplay elements, such as expert avatars hosting Q&A sessions or scenario workshops, deepen engagement. Participants can vote on emerging ideas and form ad-hoc focus groups for deeper exploration. Ideal for large-scale VW co-creation, Knowledge Fair democratizes expertise and accelerates innovative service diffusion.

'''How to use?'''

# Gather participants in a shared collaborative setting.
# Define relevant topics of discussion.
# Divide participants in groups and ask each group to identify a reporter of the insights.
# Ask groups to build a personalized virtual/digital space for each topic.
# Ask reporters to stay in the space and discuss the topic with visitors.
# Ask other participants to move and discuss the topics freely in the space.
# When discussions are finished, confront notes of the reporters and gather useful information.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2482&t=jRTjE5JDjxvV23M4-4 Open Space] ====
[[File:Open Space.png|alt=Open Space|thumb|364x364px|Open Space - CC BY-NC-SA 4.0]]
Open Space is a participant-driven agenda creation method that harnesses the self-organizing capacity of virtual-world attendees. In a shared 3D plaza or VR amphitheater, avatars propose topics by posting spatial markers, then gather around interest hubs to co-create content and agendas. Participants dynamically form breakout circles, author session titles, and schedule discussions in real time, shaping learning objectives and collaborative outcomes.

The informal, flexible format empowers autonomy and emergent insights, while facilitators capture key outcomes on virtual whiteboards. Ideal for large-scale VW events, Open Space fosters deep engagement, immersive networked learning, and co-creation by blurring roles between organizers and participants.

'''How to use it?'''

# Gather participants in a shared collaborative setting.
# Define relevant topics of discussion.
# Allow participants to discuss in a free and untstructured space the topics.
# Ask groups to build a project agenda on the next steps
# When discussions are finished, gather useful informations

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2807&t=jRTjE5JDjxvV23M4-4 Problem Framing] ====
[[File:Problem Framing.png|alt=Problem Framing|thumb|374x374px|Problem Framing - CC BY-NC-SA 4.0]]
Problem Framing is a visual synthesis method that defines and structures ambiguous or complex challenges. Teams collaborate in a 3D canvas to externalize problem elements—constraints, assumptions, stakeholders, and unknowns—as digital nodes or clusters. Participants drag and group digital sticky notes, icons, and shapes to represent pain points, policy constraints, technical uncertainties, and user needs.

Over iterative sessions, they refine connections, annotate dependencies, and expose gaps in understanding. By framing a structured problem frame, teams reduce ambiguity, align on research focus, and establish a clear foundation for design. Ideal for early-stage co-creation workshops, Problem Framing guides planning and stakeholder consensus.

'''How to use it?'''

* ''''''Identify the specific problem you want to answer with the project.
* Identify one or two types of audience affected by the project
* Identify the long-term impact of the problem, and its general goals
* Identify the physical or abstract space in which the problem manifests and which kind of affordances and interactions does it allow

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2832&t=jRTjE5JDjxvV23M4-4 Service Safari] ====
[[File:Service Safari.png|alt=Service Safari|thumb|373x373px|Service Safari - CC BY-NC-SA 4.0]]
Service Safari immerses designers in first-person explorations of a service using avatar-led autoethnography within virtual worlds. Participants navigate key touchpoints—booking, service delivery, support—experiencing each interaction exactly as a customer would. As they move through the environment, they capture contextual insights via spatial annotations, voice memos, and reflective prompts triggered at meaningful moments.

This method uncovers hidden pain points, emotional reactions, and design opportunities with authentic “lived” perspective. Ideal for VR headsets or 3D platforms, Service Safari combines deep empathy and active roleplay to generate rich qualitative data, inspire creative solutions, and guide user-centered service innovation.

'''How to use it?'''

* Identify strong suits of the project.
* Identify pain points of the project
* Identify miscellaneous aspects of the project
* Place in the different temporal columns the identified aspects.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2880&t=jRTjE5JDjxvV23M4-4 Social Network Analysis] ====
[[File:Social Network Analysis.png|alt=Social Network Analysis|thumb|366x366px|Social Network Analysis - CC BY-NC-SA 4.0]]
Social Network Analysis visualizes the web of relationships and knowledge flows among individuals, teams, and organizations within a service ecosystem. In a virtual world, nodes—avatars representing people or groups—are positioned in 3D space, with linkages animating communication channels, collaboration ties, and information exchanges.

Participants can navigate the network, inspect connection strengths, and simulate changes (e.g., adding new roles or breaking silos) to observe systemic impacts. This method uncovers hidden influencers, bottlenecks, and expertise hubs, guiding targeted interventions. Ideal for VR or immersive 3D platforms, Social Network Analysis enhances stakeholder alignment by making invisible social structures visible and tunable for optimized service co-creation.

'''How to use it?'''

* Identify a meaningful stakeholder to analyze.
* Identify other relevant stakeholders to include in the social network.
* Place in the map the different stakeholders and visualize the ecosystem.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2952&t=jRTjE5JDjxvV23M4-4 Sociometrics] ====
[[File:Sociometrics.png|alt=Sociometrics|thumb|359x359px|Sociometrics - CC BY-NC-SA 4.0]]
Sociometrics uses embodied spatial modelling in virtual worlds to map social dynamics, influence patterns, and group interactions. Participants assume avatar roles and position themselves within 3D spaces to represent relationships—cooperation, authority, trust—connecting with lines or proximity triggers that reveal network density and communication pathways.

By externalizing interpersonal ties and emergent power structures, Sociometrics surfaces hidden influencers, friction points, and collaboration opportunities. Ideal for VR or desktop-based immersive platforms, this method enhances team alignment, deepens social insight, and supports targeted interventions in service ecosystem co-creation.

Košir, K., & Pečjak, S. (2005). Sociometry as a method for investigating peer relationships: What does it actually measure? Educational Research, 47(1), 127–144. <nowiki>https://doi.org/10.1080/0013188042000337604</nowiki>

'''How to use it?'''

* Identify relevant social dynamics, influence patterns, and social interactions as well as relevant stakeholders.
* Create clusters (Group 1, Group 2...).
* Map the notes in the canvas, ranging from low to high social rejection and from low to high social acceptance.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3017&t=jRTjE5JDjxvV23M4-4 Stakeholder Map] ====
[[File:Stakeholder Map.png|alt=Stakeholder Map|thumb|360x360px|Stakeholder Map - CC BY-NC-SA 4.0]]
Stakeholder Map visually arranges all actors in a service ecosystem by plotting individuals, groups, and organizations on axes of influence and interest within a shared virtual canvas. Designers place avatar tokens or 3D icons to represent each stakeholder, then draw animated links to illustrate relationships, dependencies, and communication channels.

Participants can filter by attributes, inspect persona profiles, and simulate scenario overlays to see how policy changes or market shifts affect power dynamics. Suitable for VR workshops or desktop co-creation sessions, Stakeholder Map clarifies project scope, aligns cross-functional teams, and surfaces key partners or friction points for targeted engagement.

'''How to use it?'''

* Identify all relevant stakeholders.
* Create categories and cluster the stakeholders.
* Map stakeholders in the canvas, ranging from low to high agency and from low to high impact.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3074&t=jRTjE5JDjxvV23M4-0 Stakeholder Value Map] ====
[[File:Stakeholder Value Map.png|alt=Stakeholder Value Map|thumb|359x359px|Stakeholder Value Map - CC BY-NC-SA 4.0]]
A Stakeholder Value Map distills the core motivations and needs of each stakeholder within a service ecosystem by plotting practical, social, and higher personal values on a shared virtual canvas. Participants assume avatar roles representing users, partners, regulators, or employees and annotate a 3D map with value attributes—basic necessities, relational priorities, and dignity-driven aspirations.

Through interactive dialogues, avatars voice their value-driven perspectives at key journey phases, while collaborators cluster and compare value patterns to uncover emerging tensions or alignments. Ideal for VR or 3D workshops, this immersive method enhances empathy, grounds decision-making in stakeholder priorities, and supports narrative-driven co-creation to optimize value exchange.

'''How to use it?'''

* Identify meaningful stakeholders to analyze.
* For the cluster of Personal Needs, add note(s) describing what your user desires to do.
* For the cluster of Practical Needs, add note(s) describing what your user should be able to practically do while interacting with the virtual world.
* For the cluster of Social Needs, add note(s) describing how does your user expect to interact with others in the virtual world.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Discover // Define ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3108&t=jRTjE5JDjxvV23M4-4 Ecosystem Loops] ====
[[File:Ecosystem Loops.png|alt=Ecosystem Loops|thumb|356x356px|Ecosystem Loops - CC BY-NC-SA 4.0]]
Ecosystem Loops is an immersive mapping tool that visualizes complex service ecosystems across multiple scales—users, stakeholders, partner networks, objects, and environments—within virtual worlds. Participants arrange and connect 3D tokens or avatars to represent entities and draw animated flows that trace value exchanges, information transfers, and dependencies.

By toggling between micro-interactions and macro-system overviews, teams uncover feedback loops, bottlenecks, and leverage points in real time. Ideal for VR or spatial 3D platforms, Ecosystem Loops fosters high collaboration as stakeholders co-create and manipulate the living system model together. This method drives holistic insight, aligns diverse perspectives, and informs resilient, scalable service design strategies.

'''How to use it?'''

* Identify the main areas of interest and related topics as sub-areas, if needed.
* Identify relevant stakeholders and potential users and place them in the map.
* Define connections of different types between them to create an ecosystem.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Define ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-11&t=jRTjE5JDjxvV23M4-4 Co-creating Journey Maps] ====
[[File:Co-creating Journey Maps.png|alt=Co-creating Journey Maps|thumb|352x352px|Co-creating Journey Maps - CC BY-NC-SA 4.0]]
Co-creating Journey Maps harnesses the collective expertise of invited participants to collaboratively construct detailed customer journeys within immersive virtual environments. Participants embody avatars representing diverse user roles and pool first-hand insights, documenting touchpoints, pain points, emotional states, and backstage processes along a shared 3D timeline. As contributors add and cluster digital sticky notes, icons, and sketches, the group iterates on journey phases, pauses to explore branching scenarios, and surfaces opportunities for innovation.

Live annotation, voting, and role-swapping ensure diverse perspectives shape the narrative. Ideal for VR or spatial collaboration platforms, Co-creating Journey Maps fosters deep empathy, aligns stakeholder understanding, and accelerates co-design of optimized end-to-end service experiences.

'''How to use it?'''

# Break down the user Journey of the project in steps and list them in the purple slots.
# Define dimensions such as Physical/digital Touchpoints, Negative/Positive Experience etc... and list them in the slots on the left
# Place relevant User acticities across the canvas, mapping the journey of the user with a conenction line.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-57&t=jRTjE5JDjxvV23M4-4 Co-creating Personas] ====
[[File:Co-creating Personas.png|alt=Co-creating Personas|thumb|345x345px|Co-creating Personas - CC BY-NC-SA 4.0]]
Co-creating Personas is a collaborative method that leverages the collective expertise of invited participants to develop rich, context-driven user archetypes and associated journey maps or service blueprints in virtual worlds. Workshop attendees assume avatar roles representing target segments and co-design persona profiles by contributing real-world insights, behaviors, motivations, and pain points.

As personas crystallize, teams animate them through scenario enactments, roleplay, and narrative sessions to validate assumptions and uncover hidden needs. This immersive approach fosters shared ownership, aligns diverse stakeholders, and embeds empathy throughout the design process. Flexible for VR or 3D desktop platforms, Co-creating Personas drives depth, nuance, and stakeholder buy-in.

'''How to use it?'''

# Identify relevant stakeholders to analyze and meaningful personas.
# Define an archetype for your persona.
# Describe the motivations that move the user.
# Describe the pain points the persona could encounter.
# Decorate with emojis/images the picture of the persona to better define its profile.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-115&t=jRTjE5JDjxvV23M4-4 Co-Creative Workshops] ====
[[File:Co-Creative Workshops.png|alt=Co-Creative Workshops|thumb|343x343px|Co-Creative Workshops - CC BY-NC-SA 4.0]]
Co-creative Workshops leverage the expertise of invited stakeholders to jointly develop rich personas and service artifacts within virtual worlds. Participants adopt avatar identities aligned with target segments and contribute real-world observations, motivations, behaviors, and pain points through interactive exercises.

As the group clusters and refines characteristics, they animate personas in scenario enactments to validate assumptions and reveal hidden needs. Facilitators guide collaborative storytelling, encourage role-swapping, and capture emergent themes on 3D canvases. Ideal for VR or desktop 3D platforms, Co-creative Workshops foster shared ownership, deepen empathy, build consensus, and deliver nuanced personas that inform subsequent journey mapping, prototyping, and co-design activities.

'''How to use it?'''

# Select a topic of discussion
# Assign to each participant a role from the archetype wheel and list it in the boxes.
# Identify a reporter of the discussion.
# Start the discussion and make sure every participant is interpreting the point of view of their archetype.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-242&t=jRTjE5JDjxvV23M4-4 Emotional Journey Map] ====
[[File:Emotional Journey Map.png|alt=Emotional Journey Map|thumb|340x340px|Emotional Journey Map - CC BY-NC-SA 4.0]]
Emotional Journey maps shifts in user perception and emotional valence across a service experience in a virtual world. Designers plot rising and falling emotional states along a spatial timeline using 3D curves or color-coded overlays. During scenario enactments, avatars display real-time emotional cues—gestures, facial animations, environmental feedback—which observers annotate to pinpoint stress peaks, delight moments, or ambivalence.

Through iterative replay, teams co-design interventions to smooth pain points and amplify positive highlights. Ideal for VR or immersive 3D platforms, Emotional Journey fosters deep empathy by externalizing subjective experience, aligning stakeholders around shared emotional insights, and driving targeted, affective service improvements.

'''How to use it?'''

# Break down the user Journey of the project in steps and represent them in the slots.
# Following the User Journey above, represent with a line the emotions the user feels while going through its journey.
# For every significant emotional step, note down which opportunities emerge.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-293&t=jRTjE5JDjxvV23M4-4 Impact Journey] ====
[[File:Impact Journey.png|alt=Impact Journey|thumb|340x340px|Impact Journey - CC BY-NC-SA 4.0]]
Impact Journey is a foresight tool that models and evaluates effects of a service experience across environmental, social, and economic dimensions in an interactive virtual world. Participants enact key touchpoints as avatars—customers, service personnel, suppliers—while indicators trace resource consumption, waste streams, community benefits, and carbon footprints along the timeline.

Observers pause and propose sustainable alternatives—material substitutions, process optimizations, circular loops—and visualize their impact using dynamic overlays. By embedding sustainability metrics into storytelling and roleplay, Impact Journey fosters empathy, uncovers unintended consequences, and generates actionable creative ideas for sustainable, resilient service ecosystems. Ideal for VR workshops on sustainable innovation.

'''How to use it?'''

# Break down the System Phases of the project in steps and list them in the slots on the left.
# Define meaningful areas of impact for the project such as environment, society, economy etc... and list them.
# For every area, define metrics of evaluation such as resource consumption, waste streams, community benefits, carbon footprints etc... and list them.
# Crossing the system phases of your project and the areas of impact, define (when necessary) relevant sustainable alternatives for the current solutions.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-356&t=jRTjE5JDjxvV23M4-4 Mapping Journeys] ====
[[File:Mapping Journeys.png|alt=Mapping Journeys|thumb|338x338px|Mapping Journeys - CC BY-NC-SA 4.0]]
Mapping Journeys visualizes the service ecosystem around physical and digital products by creating spatial, interactive maps in VR or 3D platforms. Participants drag and connect avatars, 3D tokens, or digital artifacts to represent users, touchpoints, channels, and product interactions across layered environments. As teams assemble and reposition elements, they surface dependencies, information flows, and ecosystem boundaries, running “what-if” experiments by introducing new nodes or rerouting connections.

Observers and co-creators annotate live, revealing optimization opportunities and integration points. While it offers limited narrative depth on its own, Mapping Journeys excels at immersive spatial analytics, fostering collaborative sense-making and aligning cross-functional teams around holistic service landscapes.

'''How to use it?'''

# Identify relevant actors to analyze (Users, Industries...).
# Identify relevant actions to analyze (Purchase, Log-in...).
# Identify relevant connections to analyze (Personal relationship, wi-fi connection...).
# Create as many user journeys as necessary for comparison and gather relevant insights from it.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-465&t=jRTjE5JDjxvV23M4-4 System Map] ====
[[File:System Map.png|alt=System Map|thumb|347x347px|System Map - CC BY-NC-SA 4.0]]
System Map is an immersive spatial tool for visualizing all actors and components involved in service delivery within virtual worlds. Designers create a shared 3D canvas where avatars or tokens represent users, frontline staff, support systems, digital platforms, and environmental elements.

Participants drag, position, and link these modules to trace information flows, handoffs, and boundaries between subsystems. Observers could filter layers, highlight dependencies, and annotate friction points in real time.

While direct roleplay is minimal, teams can embed scenarios by triggering animations or path simulations. Ideal for VR or desktop-based 3D workshops, System Map fosters clarity of complex architectures, aligns cross-functional understanding, and informs optimization strategies.

'''How to use it?'''

# Identify relevant actors to analyze (Users, Industries...).
# Identify relevant touchpoints to analyze (Social media engagement, in-person interactions...).
# Identify relevant connections to analyze (Personal relationship, wi-fi connection...).
# Add all the element in the map and profile a comprehensive system.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-565&t=jRTjE5JDjxvV23M4-4 System Scenario] ====
[[File:System Scenario.png|alt=System Scenario|thumb|349x349px|System Scenario - CC BY-NC-SA 4.0]]
System Scenario is a dynamic simulation tool that models how a service ecosystem adapts and evolves under specific conditions. In a virtual 3D or VR environment, participants configure scenario parameters—seasonal demand spikes, regulatory shifts, tech failures—and watch animated system components (avatars, processes, data flows) respond in real time.

Observers can pause, tweak variables, and branch into alternative futures to test resilience and spot emergent behaviors.

Ideal for avatar-driven storytelling and scenario planning in immersive platforms, System Scenarios deepen understanding of systemic dynamics, foster collaborative “what-if” exploration, and surface strategic interventions before real-world rollout.

'''How to use it?'''

# Define a scenario and express it with a What-if formula
# Give a title to the scenario.
# Define and prioritize relevant actors.
# Place them in the map and define their connections.
# Identify emerging pain points and opportunities.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-636&t=jRTjE5JDjxvV23M4-4 Transition Journey] ====
[[File:Transition Journey.png|alt=Transition Journey|thumb|339x339px|Transition Journey - CC BY-NC-SA 4.0]]
Transition Journey is a dynamic tool that maps and analyzes how user behavior and roles evolve over time within a service ecosystem. In virtual worlds, participants embody avatars that transition through sequential personas—novice to expert, customer to advocate—navigating branching scenarios that illustrate changing motivations, skills, and expectations.

Teams simulate multiple horizons and tweak transition triggers (feature rollouts, policy shifts, social influences) in real time, uncovering new experience archetypes and potential friction points. Observers pause, annotate, and co-design adaptive interventions on the fly.

Ideal for immersive VR workshops, Transition Journey combines narrative forecasting with spatial roleplay to drive strategic foresight and align stakeholders around future-ready service roadmaps.

'''How to use it?'''

# Define the target user.
# Identify their motivations and pain points.
# Define multiple possible user journeys.
# Use transition arrows to explore where the journeys could transit, in order to discover pain points and opportunities.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Develop ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3164&t=jRTjE5JDjxvV23M4-4 AI Functionalities Cards] ====
[[File:AI Functionalities Cards.png|alt=AI Functionalities Cards|thumb|335x335px|AI Functionalities Cards - CC BY-NC-SA 4.0]]
AI Functionalities Cards are a spatial ideation tool designed to spark innovation by showcasing modular AI capabilities—natural language processing, computer vision, recommendation engines, anomaly detection, and more—as tangible cards in virtual environments. Participants navigate VR or 3D workspaces where avatars draw from a digital deck of functionality cards, combining and placing them along service journeys or ecosystem maps.

Through iterative play, teams discover novel applications, align technical possibilities with user needs, and generate creative service enhancements. Ideal for immersive brainstorming sessions, AI Functionalities Cards democratize AI knowledge, foster cross-disciplinary collaboration, and accelerate the translation of emerging technologies into practical, user-centered service concepts.

'''How to use it?'''

# After defining your project, identify which category of AI could be implemented among the four.
# Use the AI functionalities cards to gain knowledge and inspiration for AI integration.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3250&t=jRTjE5JDjxvV23M4-4 Concept Walkthrough] ====
[[File:Concept Walkthrough.png|alt=Concept Walkthrough|thumb|335x335px|Concept Walkthrough - CC BY-NC-SA 4.0]]
Concept Walkthrough is a guided, immersive, step-by-step 3D or VR tour that presents a service concept through sequential stages, enabling stakeholders to experience proposed features and flows in context. Creators animate avatars or interactive hotspots to demonstrate each touchpoint—from discovery to service completion—while participants observe, comment, and suggest ongoing improvements in real time.

By visualizing the envisioned journey step by step, teams gain early user feedback, validate assumptions, and align on requirements before heavy investment. Ideal for VR-enabled workshops or desktop co-creation sessions, Concept Walkthroughs offer moderate immersion, clarity of vision, and structured, seamless collaboration to refine service concepts collaboratively.

'''How to use it?'''

# Define the user journey of your project.
# Use text to define every step of the journey.
# Use drawing/images to add details to every step, paying attention to the crucial steps of the journey.
# Note down pain point and opportunities emerging.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3299&t=jRTjE5JDjxvV23M4-4 Ecosystem Map] ====
[[File:Ecosystem Map .png|alt=Ecosystem Map|thumb|335x335px|Ecosystem Map - CC BY-NC-SA 4.0]]
The Ecosystem Map is an immersive, synthetic visualization that captures all stakeholders and value exchanges within a service ecosystem. Participants arrange avatars or 3D tokens to represent individuals, organizations, technological components, and environmental elements in a looping network, then animate flows to trace information, resource, or interaction exchanges.

In VR or 3D platforms, collaborators navigate the spatial model, simulate adding or removing nodes, and observe systemic impacts in real time. Observers annotate insights and co-design strategic interventions on the fly. Perfect for high-collaboration workshops, the Ecosystem Map aligns diverse perspectives, uncovers hidden relationships, and drives holistic service strategy through richly immersive co-creation.

'''How to use it?'''

# Define a central user and put it at the center of the canvas.
# Describe relevant players and associate to each a different shape.
# Place shapes in the map.
# Central players should be placed close to the center, secondary players peripherically.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3340&t=jRTjE5JDjxvV23M4-4 Future Backcasting] ====
[[File:Future Backcasting.png|alt=Future Backcasting|thumb|332x332px|Future Backcasting - CC BY-NC-SA 4.0]]
Future Backcasting is a foresight tool that reverses time to identify pathways from desired future outcomes back to present-day actions within virtual worlds. Participants embody avatars representing future stakeholders to enact scenarios in 3D or VR environments, dramatizing how emerging trends and innovations influence service evolution.

By simulating and discussing milestones—policy shifts, technological breakthroughs, user behaviors—teams map backward through decision points, uncovering present-day interventions and design inspirations. This method fosters long-term thinking, anticipates challenges, and aligns organizational vision by translating futures into actionable roadmaps. Ideal for co-creative workshops in VR or virtual platforms, Future Backcasting drives foresight and strategic innovation.

'''How to use it?'''

# Identify a relevant topic or a relevant industry.
# Define a year in the future to set the backcasting.
# Decide in which category of future (Possible, Plausible, Probable, Preferred) the backcasting will be set.
# Describe the foresight.
# Describe which steps are needed to achieve the foresight.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3391&t=jRTjE5JDjxvV23M4-4 System UX Map Human Agent Journey] ====
[[File:System UX Map Human Agent Journey.png|alt=System UX Map Human Agent Journey|thumb|335x335px|System UX Map Human Agent Journey - CC BY-NC-SA 4.0]]
Human Agent Journey visualizes the step-by-step path a person takes to achieve a goal, illustrating agent, scenario, expectations, phases, actions, and insights in an immersive virtual environment. Participants embody an avatar representing the human agent and progress through journey stages—awareness, exploration, decision, fulfillment, and reflection—within a shared 3D or VR space.

Observers annotate key touchpoints, emotional states, and backstage processes in real time, then pause to highlight pain points or design opportunities. By spatializing each phase and mapping opportunities directly onto the journey, this method fosters empathy, aligns stakeholders around human motivations, and accelerates co-creation of service experiences shaped by real user needs.

'''How to use it?'''

# Define a human agent (user)
# Identify a scenario and expectations
# Break down the user journey in phases and list them.
# Define which actions (High-level behaviors and steps taken by users. They have a narrative scope, they're not meant to be a step-by-step log of every discrete interaction) the human agent will perform.
# Identify emerging opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3444&t=jRTjE5JDjxvV23M4-4 Future-State Journey] ====
[[File:Future-State Journey.png|alt=Future-State Journey|thumb|332x332px|Future-State Journey - CC BY-NC-SA 4.0]]
Future-State Journey uses narrative structures to guide co-creative exploration of envisioned service experiences. Participants apply the classic dramatic arc—exposition, rising action, climax, falling action, resolution—to a future-state customer journey mapped three to five years ahead. In virtual 3D or VR environments, collaborators embody avatars to spatialize journey stages, enact critical moments, and iterate plot-driven touchpoints.

By dramatizing emotional peaks and challenges, teams spark innovative ideas, uncover pivotal design opportunities, and maintain focus on strategic objectives. Ideal for immersive workshops, this method balances storytelling, spatial roleplay, and moderate collaboration, facilitating cohesive stakeholder alignment and rapidly accelerating future-focused ideation.

'''How to use it?'''

# Define a user journey or, if present, consider an existing one for this exercise. Focus on the emotional peaks and challenges arising from the experience.
# Identify where there is room for Jobs To Be Done (JTBD) and highlight it on the map .
# Now, rework the user journey imagining the experience in the future. How can JTBD be addressed by future developments?
# Identify which are the emerging opportunities.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3625&t=jRTjE5JDjxvV23M4-4 Innovative Brainstorming] ====
[[File:Innovative Brainstorming.png|alt=Innovative Brainstorming|thumb|334x334px|Innovative Brainstorming - CC BY-NC-SA 4.0]]
Innovative Brainstorming is an inclusive, fast-paced ideation technique that stimulates spontaneous thought by leveraging spatialized virtual tools and avatar-led interaction. In a VW workshop, participants converge on a shared digital whiteboard or 3D canvas, where facilitators introduce provocations, constraints, or stimulus cards.

Avatars then rapidly generate, cluster, and remix ideas through drawing, tagging, and connecting virtual sticky notes, while voice or gesture commands add energy and variety. Real-time voting and theme-based breakout areas help surface promising concepts. By combining classic free-form brainstorming with immersive, gamified mechanics, Innovative Brainstorming boosts engagement, taps collective creativity, and fuels a rich pipeline of breakthrough service innovations.

'''How to use it?'''

# Define a topic to brainstorm.
# Brainstorm any idea related to the topic in question in the warming up section.
# Select ideas within close personal or obvious contexts and list them in the braindump section.
# Use braindump ideas to inspire new ideas going in different . directions and list them in the divergent thinking section.
# Use the most promising ideas from the divergent thinking section to create new creative ideas in the creative ideation section.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3646&t=jRTjE5JDjxvV23M4-4 Integrated Journey] ====
[[File:Integrated Journey.png|alt=Integrated Journey|thumb|329x329px|Integrated Journey - CC BY-NC-SA 4.0]]
Integrated Journey extends traditional journey mapping into a comprehensive service blueprint within virtual worlds, visualizing customer touchpoints alongside backstage processes, technology systems, and stakeholder roles. In an immersive 3D environment, designers arrange avatars, swimlanes, and interactive nodes on a shared timeline to show how front-stage interactions trigger behind-the-scenes support functions and data flows.

Participants witness real-time animations of handoffs, decision points, and policy enforcements, pausing to annotate inefficiencies or propose enhancements. Avatars can enact role-specific perspectives—agent, IT, logistics—adding realism. Perfect for VR-enabled co-creation workshops, Integrated Journey aligns multidisciplinary teams, uncovers interdependencies, and accelerates holistic service innovation.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Define, for each phase, the technical journey (Steps and activities that the technical artifact performs behind the scenes to support interactions with/between human agents.)
# Define, for each phase, the provider journey (Steps, choices, activities, and interactions that providers perform while offering a service to reach a particular goal, they can be visible to users or performed in the back-end / asynchronously).
# Identify emerging opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3712&t=jRTjE5JDjxvV23M4-4 Journey Ideation with Dramatic Arcs] ====
[[File:Journey Ideation with Dramatic Arcs.png|alt=Journey Ideation with Dramatic Arcs|thumb|330x330px|Journey Ideation with Dramatic Arcs - CC BY-NC-SA 4.0]]
Journey Ideation with Dramatic Arcs is a co-creation method that applies narrative structures to service design in virtual worlds. Teams leverage classic dramatic arcs to outline user journeys, mapping emotional peaks and transitions across touchpoints.

In immersive 3D or VR environments, participants embody avatars to spatialize journey stages, visually enact pivotal moments, and explore plotlines. Observers refine service concepts by injecting unexpected challenges, resolving friction, and imagining future scenarios.

This approach deepens empathy, sparks insights, and aligns stakeholders around rich narratives. Ideal for future-focused workshops, it transforms abstract journeys into engaging storyworlds for iterative ideation.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Color the numbers ranking the customer engagement levels of every step of your journey from 1 (Low) to 6 (High).
# Reflect on the shape and rhythm of the whole arc. Is it overloaded? Frontloaded? Are the periods of low engagement or high engagement too long?
# Must a highlight be added, or - this is often more practical - should a less engaging step be spotlighted to increase engagement and show value more clearly?

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing
Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3856&t=jRTjE5JDjxvV23M4-4 Service Image] ====
[[File:Service Image.png|alt=Service Image|thumb|329x329px|Service Image - CC BY-NC-SA 4.0]]
Service Image distills the essence of a service experience into a single, impactful visual snapshot within a virtual world. Designers stage a 3D scene with avatars, environmental cues, and animated highlights to convey core touchpoints and emotional tone at a glance. This diorama-style frame employs perspective, lighting, and symbolic elements to communicate user motivations, pain points, and moments of delight cohesively.

By presenting an evocative north-star vision, Service Image aligns stakeholders around the narrative, sparks creative ideation, and guides subsequent design iterations. Ideal for kickoff sessions, pitches, and virtual galleries, it crystallizes complex experiences into an instantly sharable form.

'''How to use it?'''

# Create a service image, it can be a montage of different photos and scenes, or a post-produced photo realized ad hoc, focused on a hero moment that is able to encapsulate the core value of the service experience.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3868&t=jRTjE5JDjxvV23M4-4 System UX Map Artificial Agent Journey] ====
[[File:System UX Map Artificial Agent Journey.png|alt=System UX Map Artificial Agent Journey|thumb|326x326px|System UX Map Artificial Agent Journey - CC BY-NC-SA 4.0]]
System UX Map Agent Journey visualizes AI/ML system interactions and human collaboration within virtual worlds. Participants guide avatars representing data pipelines, models, and human operators across a spatial timeline that highlights when core AI elements—data ingestion, feature engineering, model training, inference—are generated and required.

Relationships between automated agents and human stakeholders are dynamically mapped, enabling stakeholders to pause, annotate, and adjust nodal connections in real time. Ideal for VR or 3D workshops with multidisciplinary teams, this tool clarifies technical workflows, uncovers integration bottlenecks, and fosters shared understanding. By combining agent-driven storytelling with immersive simulation, teams co-design robust, human-centered AI services.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Define, for each phase, the technical journey (Steps and activities that the technical artifact performs behind the scenes to support interactions with/between human agents).
# Define, for each phase, the artificial journey (Internal processes and interactions that support service delivery through the technical artifact. They involve the agency of Al systems).
# Identify emerging opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3935&t=jRTjE5JDjxvV23M4-4 User Scenario] ====
[[File:User Scenario.png|alt=User Scenario|thumb|335x335px|User Scenario - CC BY-NC-SA 4.0]]
User Scenarios bring envisioned service experiences to life through compelling narratives that follow a user’s journey in context. In a virtual 3D or VR environment, avatars embody personas and enact stories that illustrate goals, motivations, and pain points at each stage of interaction—discovery, decision, execution, and reflection.

Observers and co-designers watch, annotate, and pause the action to probe underlying assumptions, explore alternative paths, or inject new ideas. By weaving storytelling with spatial simulation, User Scenarios deepen empathy, align stakeholder mental models, and reveal hidden requirements. Ideal for co-creative workshops in immersive platforms, User Scenarios seamlessly integrate simulation, roleplay, and narrative ideation into service design.

'''How to use it?'''

# Define a context for each scenario.
# Define the characters (e.g. users, providers...) involved in the scenario.
# Identify the needs involved.
# Writing a story, define a user scenario in a narrative manner, focusing in describing how the user is going to interact with the service during a specific situation of everyday life.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Develop // Deliver ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3996&t=jRTjE5JDjxvV23M4-4 Rough Prototyping] ====
[[File:Rough Prototyping.png|alt=Rough Prototyping|thumb|330x330px|Rough Prototyping - CC BY-NC-SA 4.0]]
Rough Prototyping is a rapid, low-fidelity method for mocking up service ideas using simple virtual assets available on demand in VR or 3D platforms. Teams embody avatars that assemble, rearrange, and annotate digital placeholders—such as basic shapes, sketch overlays, or interactive widgets—to explore concepts in real time.

By minimizing production effort, participants test multiple variations, iterate service touchpoints, and gather immediate feedback without heavy technical overhead. Although roleplay depth is limited compared to immersive simulations, Rough Prototyping excels at fostering spontaneous creativity, aligning stakeholder understanding, and validating design assumptions. This high-velocity approach empowers teams to quickly brainstorm and converge collaboratively.

'''How to use it?'''

# Define, which are the main touchpoints (Devices, places, tools, perceivable clues that users interact with) involved in the project.
# For each touchpoint, define the technical requirements.
# Create paper/digital mockups for all the touchpoints and start experimenting/testing the user journey.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-4026&t=jRTjE5JDjxvV23M4-4 Experience Prototypes] ====
[[File:Experience Prototypes.png|alt=Experience Prototypes|thumb|322x322px|Experience Prototypes - CC BY-NC-SA 4.0]]
Experience Prototypes are interactive simulations of key service touchpoints within virtual worlds. They let teams rapidly prototype and test specific moments in a journey—such as checkout kiosks, support chatbots, or onboarding flows—by building high-fidelity mock-ups in VR or 3D spaces.

Participants embodied as avatars interact with digital artifacts, providing real-time feedback on usability, emotional resonance, and process efficiency. Through iterative cycles, designs are refined on the fly, uncovering hidden pain points and validating solutions before development. Ideal for virtual co-design workshops, Experience Prototypes enhance immersion, align stakeholders around tangible interactions, and accelerate service innovation within a holistic end-to-end context.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Prototype, for each phase, the user journey and start experimenting/testing the touchpoints.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-4074&t=jRTjE5JDjxvV23M4-4 Role Playing] ====
[[File:Role Playing.png|alt=Role Playing|thumb|320x320px|Role Playing - CC BY-NC-SA 4.0]]
Role Playing brings a hypothetical service to life through avatar enactment in virtual worlds. Users assume persona roles—customers, frontline staff, or partners—and act out journey scenarios in immersive VR or 3D environments. As avatars, participants navigate scripted or spontaneous interactions, responding to prompts, making decisions, and adapting to system feedback.

Observers can pause, annotate, and adjust scenarios on the fly to explore alternative behaviors, emotional responses, and process variations. This high-engagement method fosters deep empathy, surfaces usability issues, and validates service flows before development. Ideal for remote co-creation workshops, Role Playing aligns multidisciplinary teams around user perspectives and informs iterative design improvements.

'''How to use it?'''

# Create a scenario: define the context, the characters and the needs involved and narrate through a story the scene.
# Define some roles (e.g. the user, the service employee, etc.) and assign them to the participants.
# If needed, prepare rough prototypes or other materials that can facilitate the performance.
# While a team is acting out their story, the rest of the audience learn about the idea, understand the high-level sequence of actions required and get to know the hero moments.
# List the hero moment(s).

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Deliver ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-821&t=jRTjE5JDjxvV23M4-4 Desktop System Mapping] ====
[[File:Desktop System Mapping.png|alt=Desktop System Mapping|thumb|322x322px|Desktop System Mapping - CC BY-NC-SA 4.0]]
Desktop System Mapping, known as Business Origami, is a tactile method for visualizing complex value networks by arranging simple paper cutouts—or, in virtual worlds, draggable avatars and 3D tokens—on a shared collaborative workspace. Participants represent key people, locations, channels, and touchpoints with standardized symbols, connecting elements to reveal relationships, dependencies, and information flows.

In VR or immersive 3D platforms, collaborators reposition tokens, annotate linkages, and simulate network changes in real time. This approach clarifies service ecosystems, aligns stakeholder mental models, and fosters collective sense-making. Desktop System Mapping excels at uncovering structural insights, driving collaborative strategy, and achieving strategic alignment.

'''How to use it?'''

# Define the main scope of your prototype
# Define the level of detail of the prototype
# Create paper/digital cutouts of the prototype and start testing/simulate talking points using the models on the table.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-854&t=jRTjE5JDjxvV23M4-4 Desktop Walkthrough] ====
[[File:Desktop Walkthrough.png|alt=Desktop Walkthrough|thumb|320x320px|Desktop Walkthrough - CC BY-NC-SA 4.0]]
Desktop Walkthrough is a low-fidelity prototyping tool that brings teams together around a shared simulation of a service journey in a virtual world. Participants embody avatars to step through each critical touchpoint—sign-up, payment, support—while observers annotate pain points, decision triggers, and contextual cues.

By projecting simple mock-ups of screens, environments, and process steps into a 3D or VR space, teams quickly gain a unified understanding of end-to-end experiences and surface hidden issues. Iterative “play-throughs” enable real-time adjustments to sequences, handoffs, and interface layouts. Ideal for early-stage co-creation workshops, Desktop Walkthrough accelerates alignment, empathy, and rapid identification of critical journey enhancements.

'''How to use it?'''

# Define the user journey of your project and create a visual representation of it using emojis/imported images

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1021&t=jRTjE5JDjxvV23M4-4 Emotional Journey Feedback] ====
[[File:Emotional Journey Feedback.png|alt=Emotional Journey Feedback|thumb|317x317px|Emotional Journey Feedback - CC BY-NC-SA 4.0]]
Emotional Journey Feedback extends the System UX Map by overlaying users’ emotional states across every phase of their experience in virtual worlds. A continuous “emotion line” traces peaks and valleys—signaling stress points, moments of delight, and transitional shifts—plotted along a spatialized service timeline.

In VR or 3D environments, avatars convey real-time emotional cues through gestures, facial expressions, or ambient lighting changes that correspond to the graph. Participants can pause, annotate, and iterate scenarios to smooth pain points or amplify positive highlights. Ideal for immersive co-design workshops, this tool deepens empathy, enhances feedback loops, and strengthens narrative-driven storytelling in service innovation.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Define, for each phase, the technical journey (Steps and activities that the technical artifact performs behind the scenes to support interactions with/between human agents.)
# For each step, consider the emotional feedback of the user and keep track of it in the canvas.
# Identify emerging pain points and opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1081&t=jRTjE5JDjxvV23M4-4 Investigative Rehearsal] ====
[[File:Investigative Rehearsal.png|alt=Investigative Rehearsal|thumb|316x316px|Investigative Rehearsal - CC BY-NC-SA 4.0]]
Investigative Rehearsal is a theatrical tool that uses iterative roleplay to uncover and refine service behaviors within virtual worlds. Participants embody avatars to act out scenarios—customer interactions, back-end workflows, decision points—while observers note emergent patterns and friction points.

Through multiple rehearsal loops, teams adjust roles, scripts, and environment affordances in real time, testing alternative responses and process variations. This method fosters deep empathy, reveals implicit knowledge, and surfaces systemic issues that workshops might miss. Ideal for VR or richly immersive 3D platforms, Investigative Rehearsal accelerates behavioral insight, aligns stakeholder mental models, and co-designs optimized service experiences grounded in lived enactment.

'''How to use it?'''

# Define the scene and research question.
# Assign actors with roles and scenario details.
# Observers watch a brief scene enactment.
# Observers reflect on current knowledge and feelings.
# Replay the scene, pausing to suggest changes and improvements.
# Document observations and insights throughout.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1136&t=jRTjE5JDjxvV23M4-4 Rehearsing Digital Services] ====
[[File:Rehearsing Digital Services.png|alt=Rehearsing Digital Services|thumb|319x319px|Rehearsing Digital Services - CC BY-NC-SA 4.0]]
Rehearsing Digital Services is a variant of Investigative Rehearsal that prototypes digital interfaces through embodied, actor-led simulations in virtual worlds. Participants—represented as avatars—take on customer, agent, or system roles and act out conversational and transactional flows: chatbot dialogs, voice assistants, form interactions, and error recoveries.

Facilitators guide scenarios in VR or 3D platforms, narrating screen states and system prompts aloud as avatars interact with on-screen elements. Iterative enactments expose usability gaps, friction points, and emotional reactions, enabling real-time script tweaks, UI refinements, and branching-logic tests. Ideal for immersive co-creation workshops, Rehearsing Digital Services drives shared understanding, empathy, and alignment around seamless digital service experiences.

'''How to use this?'''

# Define the scene and research question.
# Assign roles and outline the scenario.
# Have teams act out the scene briefly to observe.
# Observe, understand feelings and current dynamics.
# Iterate by pausing and suggesting changes focused on service digitalization.
# Reflect on how to digitally transform and enact the service experience.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1193&t=jRTjE5JDjxvV23M4-4 Service Blueprint] ====
[[File:Service Blueprint.png|alt=Service Blueprint|thumb|316x316px|Service Blueprint - CC BY-NC-SA 4.0]]
Service Blueprint is a comprehensive mapping technique that visualizes every stage of service delivery—front-stage interactions, backstage processes, support systems, and physical or digital touchpoints—in a unified blueprint. In virtual environments, designers arrange swim-lane structures on a 3D canvas, deploying avatars to simulate customer and staff roles and animating process flows in real time.

Participants annotate decision gateways, handoffs, and dependencies while observing both visible and hidden service elements. This immersive representation reveals systemic inefficiencies, clarifies ownership, and guides co-design of seamless experiences. Ideal for VR or desktop-based co-creation workshops, Service Blueprint accelerates alignment, optimizes workflows, and de-risks implementation through collective visualization and iteration.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, a main user and secondary users and place them in the other areas.
# Consider the Interaction Area and place other entities the main user interacts with and the Visibility Area and place players, functionalities invisible to the user.
# Map connection between the users and define the project ecosystem.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1226&t=jRTjE5JDjxvV23M4-4 Service Prototype] ====
[[File:Service Prototype.png|alt=Service Prototype|thumb|312x312px|Service Prototype - CC BY-NC-SA 4.0]]
Service Prototype simulates real user interactions with service touchpoints in virtual environments. Designers create interactive mock-ups—digital kiosks, chatbots, mobile interfaces—and deploy them in VR or 3D worlds.

Participants embody avatars to engage with prototypes as they would in real life: querying a virtual assistant, placing an order through a mock interface, or interacting with augmented customer support. Real-time feedback sessions record usability metrics, emotional reactions, and friction points. Iterative cycles refine prototypes, ensuring functionality, aesthetics, and experience quality align with user expectations. Perfect for immersive co-creation workshops, Service Prototypes accelerate validation, enhance stakeholder feedback, and de-risk service launch.

'''How to use it?'''

# Define a precise User Journey and describe it in steps.
# Assign roles to participants.
# Choose touchpoints to be prototyped.
# Reenact the service using the prototypes. This tool has the objective of replicating, as much as possible, the final experience of interacting with the service, in order to test and validate all the design choices.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1300&t=jRTjE5JDjxvV23M4-4 Subtext] ====
[[File:Subtext.png|alt=Subtext|thumb|316x316px|Subtext - CC BY-NC-SA 4.0]]
Subtext is a theatrical method that can reveal deeper motivations and needs by focusing on unspoken thoughts in a rehearsal session.

Perfect for exploring non-verbal communication and emotions in VW rehearsals; enhances depth of co-creative exploration.

'''How to use it?'''

# Choose a key scene you want to understand more deeply
# Select and assign roles of actors, who will play the key scene once.
# Select and assign roles of subtext actors for each actor.
# The character actors will play the scene as usual – or perhaps a little slower – and the subtext actors will simply speak what they believe their characters are thinking at any moment, using “I” or “me” statements when possible. For example, the character actor might say, “Can you prioritize that?” and his subtext actor might rage, “For f*ck’s sake! Help me before I lose my job, you idiot!”
# Iterate.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

Co-creation Toolkit

2026-09-02T08:12:38Z

CollectiveIntelligenceAdmin:

== A Toolkit for Co-Creation in Virtual Worlds ==
This page provides an overview and links to the co-creation tools developed by Politecnico di Milano in the context of the OPENVERSE project.
A core component of planning is the selection and contextual adaptation of co-creation tools. The OPENVERSE Toolkit includes a wide variety of such tools—a curated set of 48 co-creation tools mapped across the four phases of the [[wikipedia:Double_Diamond_(design_process_model)|Double Diamond]]—that support everything from early exploration to final decision-making.
[[File:Double diamond .png|alt=Image representing the Double Diamond design process model|center|thumb|790x790px|'''Double Diamond design process model''' Work by Politecnico di Milano, adapted from Design Council's original work - CC BY-NC-SA 4.0]]
The goal is to empower a diverse range of stakeholders—designers, developers, educators, VWs consumers, and citizens—to run meaningful co-creation processes in immersive environments, using a shared methodology grounded in field experimentation and design research.

{{center|<youtube width="100%" height="400">s2BpzupW5Qc</youtube>}}

The complete [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=0-1&p=f&t=djpkfnwCxadiCigO-0 Co-creation Toolkit] is available on the Figma platform.

<blockquote>
=== License and Attribution ===
This toolkit is designed for open collaboration, and its structure and licensing model are crafted to comply with the terms of all referenced source materials. The entire original content of this toolkit is licensed under [https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)].

The content of this toolkit is shared as CC BY-NC-SA 4.0. This license enables re-users to distribute, remix, adapt, and build upon this material in any medium or format for noncommercial purposes only, provided original attribution (BY) is always given.

Because this toolkit adopts the '''ShareAlike (SA)''' element, any new work created by adapting, remixing, or transforming the original licensed content from this toolkit must be distributed under the same or a compatible Creative Commons license.

Toolkit License: [https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en CC BY-NC-SA 4.0]

Designed in 2025 by: Riccardo Ventura, Ilaria Mariani, Venere Ferraro, Francesca Rizzo, Department of Design, Politecnico di Milano</blockquote><blockquote>
=== Source Material ===
This work includes content, methodologies, and inspiration drawn from the following sources:

* Adapted and Derivative Content (CC BY-NC-SA 4.0): Tools and methodologies were directly adapted, remixed, or inspired by materials from the AI4Gov Toolkit (CC BY-NC-SA 4.0) and Follow the Rabbit: A Field Guide to Systemic Design (CC BY-NC-SA 4.0). Due to this adaptation, the ShareAlike condition of these source licenses requires that this resulting toolkit must also adopt the CC BY-NC-SA 4.0 license.
* Inspirational Use Only (Non-Derivative): The creation of our new tools, concepts, guides, and the overall structural approach were purely inspired by the materials presented in three other sources. This process involved consulting the Servicedesigntools (CC BY-NC-ND 2.5) repository, the This is Service Design Doing – Method Library (copyrighted content), and the Share, Learn, Innovate! toolkit (copyrighted content). The team behind this toolkit consulted these materials for guides, concepts, and structure but did not adopt, adapt, or create derivative versions of their original content
</blockquote>

=== Components of the Toolkit ===
All the components are available for exploration and reuse on the Figma board, along with the full description of each of the components. This page provides a high-level overview of the components for quick reference. The components are grouped based on the four Double Diamond phases shown above. In case of overlaps across the phases, the headings will show both relevant phases.

{| class="wikitable"
! style="background-color:#E400FF; color:#FFFFFF;" | Discover
! style="background-color:#B700FF; color:#FFFFFF;" | Define
! style="background-color:#9600FF; color:#FFFFFF;" | Develop
! style="background-color:#7200FF; color:#FFFFFF;" | Deliver
|-
| [[#Cultural Probes|Cultural Probes]] || [[#Co-creating Journey Maps|Co-creating Journey Maps]] || [[#Experience Prototypes|Experience Prototypes]] || [[#Desktop System Mapping|Desktop system mapping (a.k.a. Business Origami)]]
|-
| [[#Ecosystem Map|Ecosystem Map]] || [[#Co-creating Personas|Co-creating Personas]] || [[#Role Playing|Role Playing]] || [[#Desktop Walkthrough|Desktop Walkthrough]]
|-
| [[#Envisioning the Future|Envisioning the Future]] || [[#Co-Creative Workshops|Co-Creative Workshops]] || [[#AI Functionalities Cards|AI Functionalities Cards]] || [[#Emotional Journey Feedback|Emotional Journey Feedback]]
|-
| [[#Fishbowl|Fishbowl]] || [[#Emotional Journey Map|Emotional Journey Map]] || [[#Concept Walkthrough|Concept Walkthrough]] || [[#Investigative Rehearsal|Investigative Rehearsal]]
|-
| [[#Iceberg Diagram|Iceberg Diagram]] || [[#Impact Journey|Impact Journey]] || [[#Ecosystem Map|Ecosystem Map]] || [[#Rehearsing Digital Services|Rehearsing Digital Services]]
|-
| [[#Jigsaw|Jigsaw]] || [[#Mapping Journeys|Mapping Journeys]] || [[#Future Backcasting|Future Backcasting]] || [[#Service Blueprint|Service Blueprint]]
|-
| [[#Knowledge Café|Knowledge Café / Round Table Sessions]] || [[#System Map|System Map]] || [[#Human Agent Journey|Human Agent Journey]] || [[#Service Prototype|Service Prototype]]
|-
| [[#Knowledge Fair|Knowledge Fair]] || [[#System Scenario|System Scenario]] || [[#Future-State Journey|Future-State Journey]] || [[#Subtext|Subtext]]
|-
| [[#Open Space|Open Space]] || [[#Transition Journey|Transition Journey]] || [[#Innovative Brainstorming|Innovative Brainstorming]] || [[#Experience Prototypes|Experience Prototypes]]
|-
| [[#Problem Framing|Problem Framing]] || [[#Ecosystem Loops|Ecosystem Loops]] || [[#Integrated Journey|Integrated Journey]] || [[#Role Playing|Role Playing]]
|-
| [[#Service Safari|Service Safari]] || || [[#Journey Ideation with Dramatic Arcs|Journey Ideation with Dramatic Arcs]] || [[#Rough Prototyping|Rough Prototyping]]
|-
| [[#Social Network Analysis|Social Network Analysis]] || || [[#Service Image|Service Image]] ||
|-
| [[#Sociometrics|Sociometrics]] || || [[#System UX Map Agent Journey|System UX Map Agent Journey]] ||
|-
| [[#Stakeholder Map|Stakeholder Map]] || || [[#User Scenario|User Scenarios]] ||
|-
| [[#Stakeholder Value Map|Stakeholder Value Map]] || || [[#Rough Prototyping|Rough Prototyping]] ||
|-
| [[#Ecosystem Loops|Ecosystem Loops]] || || ||
|}

=== The Toolkit in action ===
The videos below, portraying the activities of seven co-creation groups, showcases the use of several of the components of the toolkit.
{| class="wikitable"
|-
| <youtube width="400" height="240">KPemYBWjAig</youtube>
| <youtube width="400" height="240">jRE2TEP59DQ</youtube>
|-
| <youtube width="400" height="240">hY5mLs9Erv8</youtube>
| <youtube width="400" height="240">c-xghyabhfU</youtube>
|-
| <youtube width="400" height="240">LG6s8NlbvJM</youtube>
| <youtube width="400" height="240">6tQQw2Wpyh0</youtube>
|-
| <youtube width="400" height="240">2r_BkoknYEY</youtube>
|
|}

=== Discover ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1396&t=jRTjE5JDjxvV23M4-4 Cultural Probes] ====
[[File:Cultural Probes.png|alt=Cultural probes|thumb|383x383px|Cultural probes - CC BY-NC-SA 4.0]]
Cultural Probes are stimuli-based design research tools that invite participants to document personal experiences, contexts, and thoughts through artifacts such as postcards, diaries, or in-world interactive objects. In immersive VW environments, designers distribute digital probes (VR postcards, 3D tokens, prompts) into user spaces.

Participants interact, capture audio/video responses, and and interactions in digital environments, and return probes for analysis. Through asynchronous co-creation, teams gather rich qualitative data, uncover emergent needs, and iteratively refine personas, journey maps, and system maps. Ideal for exploratory research in spatial VR or 3D platforms, Cultural Probes foster empathy, spark ideation, and ground service design in lived experiences.

'''How to use it?'''

# Decide which digital / physical objects could help users narrate their virtual worlds experiences.
# Ask users to take notes throughout the project.
# Use notes to gather useful insight for further improvement.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1545&t=jRTjE5JDjxvV23M4-4 Ecosystem Map] ====
[[File:Ecosystem Map.png|alt=Ecosystem Map|thumb|383x383px|Ecosystem Map - CC BY-NC-SA 4.0]]
Ecosystem Map portrays every entity, flow, and relationship that defines a service’s surrounding ecosystem in immersive three-dimensional space. Avatars or 3D tokens represent users, partners, suppliers, technologies, and environmental factors, while animated streams trace value exchanges, information channels, and resource movements.

Collaborators navigate the dynamic model, simulate changes—such as adding new nodes or rerouting flows—and observe systemic ripple effects in real time. Participants annotate insights, propose interventions, and iteratively refine connections. Perfect for VR-enabled co-creation workshops, Ecosystem Map fosters holistic understanding, surfaces hidden interdependencies, and aligns stakeholders around end-to-end service innovation strategies.

'''How to use it?'''

# Define a central topic and put it at the center of the canvas.
# Describe relevant players and associate to each a different shape.
# Place shapes in the map.
# Central players should be placed close to the center, secondary players peripherically.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1592&t=jRTjE5JDjxvV23M4-4 Envisioning the Future] ====
[[File:Envisioning the Future.png|alt=Envisioning the Future|thumb|380x380px|Envisioning the Future - CC BY-NC-SA 4.0]]
Envisioning the Future is a collaborative scenario-building tool that invites teams to imagine plausible worlds three to six years ahead within virtual environments. Participants embody avatars in detailed VR or 3D spaces, exploring future success states—streamlined operations, empowered customers, sustainable ecosystems.

During guided workshops, they define milestones, identify emerging trends, and co-create narratives that show how organizational goals materialize. By visualizing outcomes and backcasting interventions, Envisioning the Future fosters long-term strategic alignment, surfaces uncertainties, and sparks innovative service breakthroughs. Ideal for remote or hybrid teams, this method leverages immersive storytelling and collective foresight to translate visionary aspirations into actionable roadmaps.

'''How to use it?'''

# Select a timeframe fro 3 to 6 years.
# Answer to the provided questions.
# Describe as a scenario the vision.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1641&t=jRTjE5JDjxvV23M4-4 Fishbowl] ====
[[File:Fishbowl.png|alt=Fishbowl|thumb|371x371px|Fishbowl - CC BY-NC-SA 4.0]]
Fishbowl is an interactive dialogue technique that amplifies expert knowledge and broadens group understanding through a concentric-circle setup in virtual worlds.

In a central “bowl,” a handful of skilled avatars discuss targeted questions while an outer ring of observers listens, reflects, and captures insights on spatial whiteboards. When outer participants wish to contribute, they enter the bowl, temporarily swapping places with an inner speaker.

This fluid movement between inner and outer circles democratizes voice, encourages active listening, and fosters shared learning. Deployed in VR or 3D environments, Fishbowl’s structured yet flexible format drives deep engagement, peer teaching, and immersive co-creative exploration.

'''How to use it?'''

# Gather participants in a physical/virtual environment.
# Divide participants in 2 groups.
# Fishes (2-4 people): They have to discuss a relevant topic, at the center of the room.
# Observers (The rest of the participants): They have to take notes on the discussion and, if they wish to participate, respectfully interrupt the discussion, swapping places with a fish.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1691&t=jRTjE5JDjxvV23M4-4 Iceberg Diagram] ====
[[File:Iceberg Diagram.png|alt=Iceberg Diagram|thumb|369x369px|Iceberg Diagram - CC BY-NC-SA 4.0]]
An Iceberg Diagram visualizes beneath-the-surface forces that shape service behaviors by layering observable events, systemic structures, mental models, and underlying paradigms in a vertical 3D canvas. Participants position avatars or tokens at different strata—the tip of the iceberg representing customer actions, the submerged mass depicting processes, regulations, cultural beliefs, and deeper worldviews.

Collaborators drill down through scenarios in VR environments, annotating feedback loops, mental models, and leverage points that perpetuate current outcomes. Iterative exploration surfaces hidden constraints, reveals impactful intervention zones, and fosters systemic thinking. Ideal for immersive workshops, the Iceberg Diagram enables teams to align on root causes and co-design transformative strategies grounded in deep structural insight.

'''How to use it?'''

* Define a central topic.
* Compile brainstorm events section, highlighting relevant aspects.
* Compile patterns of behaviors section, highlighting repeating aspects.
* Compile system structures section, highlighting who/what is responsible for pattern creation.
* Compile mental models section, highlighting which assumptions and beliefs created the systemic structures.
* After looking at the big picture, place relevant aspects as icons in the iceberg.

<blockquote>Inspired by the toolkit: Follow the Rabbit Publisher: Colab

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1746&t=jRTjE5JDjxvV23M4-4 Jigsaw] ====
[[File:Jigsaw.png|alt=Jigsaw|thumb|366x366px|Jigsaw - CC BY-NC-SA 4.0]]
Jigsaw is a cooperative learning strategy adapted for virtual worlds that divides a complex service challenge into interlocking “puzzle pieces.” Small expert teams explore an assigned component—such as user research, technology integration, or policy constraints—and develop deep insights. Avatars reconvene in a shared 3D space to assemble findings, linking visual tokens, diagrams, and narratives to complete the holistic picture.

This method leverages spatial distribution, collaborative assembly, and peer teaching to build collective expertise and foster ownership. By transforming individual discoveries into a cohesive ecosystem map, Jigsaw enhances cross-functional understanding, drives mutual accountability, and accelerates integrated service design through immersive, puzzle-based co-creation.

'''How to use it?'''

# Divide participants in groups.
# Assign to each group a relevant topic/area to discuss
# Discuss in groups and keep track of the findings.
# Reassemble the pieces and discuss together the bigger picture.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1895&t=jRTjE5JDjxvV23M4-4 Knowledge Café] ====
[[File:Knowledge Café.png|alt=Knowledge Café|thumb|362x362px|Knowledge Café - CC BY-NC-SA 4.0]]
Knowledge Café or Round Table Sessions is an avatar-led dialogue method that builds collective intelligence in virtual worlds. Participants gather at themed café tables, sharing experiences and posting digital notes on shared canvases. After a timed session, avatars rotate to new tables, carrying forward insights and weaving ideas into a knowledge web.

Each table host curates threads and captures emergent patterns, ensuring continuity. By assuming that every participant is a source of wisdom, the format surfaces novel perspectives and cross-pollinates ideas across the group. Ideal for VR or 3D co-creation spaces, Knowledge Café fosters immersive collaboration and amplifies shared understanding.

'''How to use it?'''

# Gather participants in a shared collaborative setting.
# Define relevant topics of discussion.
# Define how much time to spend on each discussion before rotating.
# Divide participants in groups and ask each group to identify a reporter of the insights.
# Sit on the tables and start the timer, when time is off, rotate and change table/topic.
# After a full rotation, take some time to share what emerged from each topic between the groups.

<blockquote>Inspired by the toolkit: Follow the Rabbit Publisher: Colab

Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2041&t=jRTjE5JDjxvV23M4-4 Knowledge Fair] ====
[[File:Knowledge Fair.png|alt=Knowledge Fair|thumb|363x363px|Knowledge Fair - CC BY-NC-SA 4.0]]
Knowledge Fair is a virtual event for sharing insights from diverse experts through immersive booths, dynamic displays, and interactive presentations. In a 3D or VR expo hall, participants navigate avatar-driven pavilions themed around specific domains—data privacy, user research, policy design—and engage with multimedia panels showcasing research findings, prototypes, and case studies.

Exhibitors use digital posters, video kiosks, live demos, and spatial annotations to spark dialogue and crowdsourced ideation. Roleplay elements, such as expert avatars hosting Q&A sessions or scenario workshops, deepen engagement. Participants can vote on emerging ideas and form ad-hoc focus groups for deeper exploration. Ideal for large-scale VW co-creation, Knowledge Fair democratizes expertise and accelerates innovative service diffusion.

'''How to use?'''

# Gather participants in a shared collaborative setting.
# Define relevant topics of discussion.
# Divide participants in groups and ask each group to identify a reporter of the insights.
# Ask groups to build a personalized virtual/digital space for each topic.
# Ask reporters to stay in the space and discuss the topic with visitors.
# Ask other participants to move and discuss the topics freely in the space.
# When discussions are finished, confront notes of the reporters and gather useful information.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2482&t=jRTjE5JDjxvV23M4-4 Open Space] ====
[[File:Open Space.png|alt=Open Space|thumb|364x364px|Open Space - CC BY-NC-SA 4.0]]
Open Space is a participant-driven agenda creation method that harnesses the self-organizing capacity of virtual-world attendees. In a shared 3D plaza or VR amphitheater, avatars propose topics by posting spatial markers, then gather around interest hubs to co-create content and agendas. Participants dynamically form breakout circles, author session titles, and schedule discussions in real time, shaping learning objectives and collaborative outcomes.

The informal, flexible format empowers autonomy and emergent insights, while facilitators capture key outcomes on virtual whiteboards. Ideal for large-scale VW events, Open Space fosters deep engagement, immersive networked learning, and co-creation by blurring roles between organizers and participants.

'''How to use it?'''

# Gather participants in a shared collaborative setting.
# Define relevant topics of discussion.
# Allow participants to discuss in a free and untstructured space the topics.
# Ask groups to build a project agenda on the next steps
# When discussions are finished, gather useful informations

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2807&t=jRTjE5JDjxvV23M4-4 Problem Framing] ====
[[File:Problem Framing.png|alt=Problem Framing|thumb|374x374px|Problem Framing - CC BY-NC-SA 4.0]]
Problem Framing is a visual synthesis method that defines and structures ambiguous or complex challenges. Teams collaborate in a 3D canvas to externalize problem elements—constraints, assumptions, stakeholders, and unknowns—as digital nodes or clusters. Participants drag and group digital sticky notes, icons, and shapes to represent pain points, policy constraints, technical uncertainties, and user needs.

Over iterative sessions, they refine connections, annotate dependencies, and expose gaps in understanding. By framing a structured problem frame, teams reduce ambiguity, align on research focus, and establish a clear foundation for design. Ideal for early-stage co-creation workshops, Problem Framing guides planning and stakeholder consensus.

'''How to use it?'''

* ''''''Identify the specific problem you want to answer with the project.
* Identify one or two types of audience affected by the project
* Identify the long-term impact of the problem, and its general goals
* Identify the physical or abstract space in which the problem manifests and which kind of affordances and interactions does it allow

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2832&t=jRTjE5JDjxvV23M4-4 Service Safari] ====
[[File:Service Safari.png|alt=Service Safari|thumb|373x373px|Service Safari - CC BY-NC-SA 4.0]]
Service Safari immerses designers in first-person explorations of a service using avatar-led autoethnography within virtual worlds. Participants navigate key touchpoints—booking, service delivery, support—experiencing each interaction exactly as a customer would. As they move through the environment, they capture contextual insights via spatial annotations, voice memos, and reflective prompts triggered at meaningful moments.

This method uncovers hidden pain points, emotional reactions, and design opportunities with authentic “lived” perspective. Ideal for VR headsets or 3D platforms, Service Safari combines deep empathy and active roleplay to generate rich qualitative data, inspire creative solutions, and guide user-centered service innovation.

'''How to use it?'''

* Identify strong suits of the project.
* Identify pain points of the project
* Identify miscellaneous aspects of the project
* Place in the different temporal columns the identified aspects.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2880&t=jRTjE5JDjxvV23M4-4 Social Network Analysis] ====
[[File:Social Network Analysis.png|alt=Social Network Analysis|thumb|366x366px|Social Network Analysis - CC BY-NC-SA 4.0]]
Social Network Analysis visualizes the web of relationships and knowledge flows among individuals, teams, and organizations within a service ecosystem. In a virtual world, nodes—avatars representing people or groups—are positioned in 3D space, with linkages animating communication channels, collaboration ties, and information exchanges.

Participants can navigate the network, inspect connection strengths, and simulate changes (e.g., adding new roles or breaking silos) to observe systemic impacts. This method uncovers hidden influencers, bottlenecks, and expertise hubs, guiding targeted interventions. Ideal for VR or immersive 3D platforms, Social Network Analysis enhances stakeholder alignment by making invisible social structures visible and tunable for optimized service co-creation.

'''How to use it?'''

* Identify a meaningful stakeholder to analyze.
* Identify other relevant stakeholders to include in the social network.
* Place in the map the different stakeholders and visualize the ecosystem.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-2952&t=jRTjE5JDjxvV23M4-4 Sociometrics] ====
[[File:Sociometrics.png|alt=Sociometrics|thumb|359x359px|Sociometrics - CC BY-NC-SA 4.0]]
Sociometrics uses embodied spatial modelling in virtual worlds to map social dynamics, influence patterns, and group interactions. Participants assume avatar roles and position themselves within 3D spaces to represent relationships—cooperation, authority, trust—connecting with lines or proximity triggers that reveal network density and communication pathways.

By externalizing interpersonal ties and emergent power structures, Sociometrics surfaces hidden influencers, friction points, and collaboration opportunities. Ideal for VR or desktop-based immersive platforms, this method enhances team alignment, deepens social insight, and supports targeted interventions in service ecosystem co-creation.

Košir, K., & Pečjak, S. (2005). Sociometry as a method for investigating peer relationships: What does it actually measure? Educational Research, 47(1), 127–144. <nowiki>https://doi.org/10.1080/0013188042000337604</nowiki>

'''How to use it?'''

* Identify relevant social dynamics, influence patterns, and social interactions as well as relevant stakeholders.
* Create clusters (Group 1, Group 2...).
* Map the notes in the canvas, ranging from low to high social rejection and from low to high social acceptance.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3017&t=jRTjE5JDjxvV23M4-4 Stakeholder Map] ====
[[File:Stakeholder Map.png|alt=Stakeholder Map|thumb|360x360px|Stakeholder Map - CC BY-NC-SA 4.0]]
Stakeholder Map visually arranges all actors in a service ecosystem by plotting individuals, groups, and organizations on axes of influence and interest within a shared virtual canvas. Designers place avatar tokens or 3D icons to represent each stakeholder, then draw animated links to illustrate relationships, dependencies, and communication channels.

Participants can filter by attributes, inspect persona profiles, and simulate scenario overlays to see how policy changes or market shifts affect power dynamics. Suitable for VR workshops or desktop co-creation sessions, Stakeholder Map clarifies project scope, aligns cross-functional teams, and surfaces key partners or friction points for targeted engagement.

'''How to use it?'''

* Identify all relevant stakeholders.
* Create categories and cluster the stakeholders.
* Map stakeholders in the canvas, ranging from low to high agency and from low to high impact.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3074&t=jRTjE5JDjxvV23M4-0 Stakeholder Value Map] ====
[[File:Stakeholder Value Map.png|alt=Stakeholder Value Map|thumb|359x359px|Stakeholder Value Map - CC BY-NC-SA 4.0]]
A Stakeholder Value Map distills the core motivations and needs of each stakeholder within a service ecosystem by plotting practical, social, and higher personal values on a shared virtual canvas. Participants assume avatar roles representing users, partners, regulators, or employees and annotate a 3D map with value attributes—basic necessities, relational priorities, and dignity-driven aspirations.

Through interactive dialogues, avatars voice their value-driven perspectives at key journey phases, while collaborators cluster and compare value patterns to uncover emerging tensions or alignments. Ideal for VR or 3D workshops, this immersive method enhances empathy, grounds decision-making in stakeholder priorities, and supports narrative-driven co-creation to optimize value exchange.

'''How to use it?'''

* Identify meaningful stakeholders to analyze.
* For the cluster of Personal Needs, add note(s) describing what your user desires to do.
* For the cluster of Practical Needs, add note(s) describing what your user should be able to practically do while interacting with the virtual world.
* For the cluster of Social Needs, add note(s) describing how does your user expect to interact with others in the virtual world.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Discover // Define ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3108&t=jRTjE5JDjxvV23M4-4 Ecosystem Loops] ====
[[File:Ecosystem Loops.png|alt=Ecosystem Loops|thumb|356x356px|Ecosystem Loops - CC BY-NC-SA 4.0]]
Ecosystem Loops is an immersive mapping tool that visualizes complex service ecosystems across multiple scales—users, stakeholders, partner networks, objects, and environments—within virtual worlds. Participants arrange and connect 3D tokens or avatars to represent entities and draw animated flows that trace value exchanges, information transfers, and dependencies.

By toggling between micro-interactions and macro-system overviews, teams uncover feedback loops, bottlenecks, and leverage points in real time. Ideal for VR or spatial 3D platforms, Ecosystem Loops fosters high collaboration as stakeholders co-create and manipulate the living system model together. This method drives holistic insight, aligns diverse perspectives, and informs resilient, scalable service design strategies.

'''How to use it?'''

* Identify the main areas of interest and related topics as sub-areas, if needed.
* Identify relevant stakeholders and potential users and place them in the map.
* Define connections of different types between them to create an ecosystem.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Define ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-11&t=jRTjE5JDjxvV23M4-4 Co-creating Journey Maps] ====
[[File:Co-creating Journey Maps.png|alt=Co-creating Journey Maps|thumb|352x352px|Co-creating Journey Maps - CC BY-NC-SA 4.0]]
Co-creating Journey Maps harnesses the collective expertise of invited participants to collaboratively construct detailed customer journeys within immersive virtual environments. Participants embody avatars representing diverse user roles and pool first-hand insights, documenting touchpoints, pain points, emotional states, and backstage processes along a shared 3D timeline. As contributors add and cluster digital sticky notes, icons, and sketches, the group iterates on journey phases, pauses to explore branching scenarios, and surfaces opportunities for innovation.

Live annotation, voting, and role-swapping ensure diverse perspectives shape the narrative. Ideal for VR or spatial collaboration platforms, Co-creating Journey Maps fosters deep empathy, aligns stakeholder understanding, and accelerates co-design of optimized end-to-end service experiences.

'''How to use it?'''

# Break down the user Journey of the project in steps and list them in the purple slots.
# Define dimensions such as Physical/digital Touchpoints, Negative/Positive Experience etc... and list them in the slots on the left
# Place relevant User acticities across the canvas, mapping the journey of the user with a conenction line.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-57&t=jRTjE5JDjxvV23M4-4 Co-creating Personas] ====
[[File:Co-creating Personas.png|alt=Co-creating Personas|thumb|345x345px|Co-creating Personas - CC BY-NC-SA 4.0]]
Co-creating Personas is a collaborative method that leverages the collective expertise of invited participants to develop rich, context-driven user archetypes and associated journey maps or service blueprints in virtual worlds. Workshop attendees assume avatar roles representing target segments and co-design persona profiles by contributing real-world insights, behaviors, motivations, and pain points.

As personas crystallize, teams animate them through scenario enactments, roleplay, and narrative sessions to validate assumptions and uncover hidden needs. This immersive approach fosters shared ownership, aligns diverse stakeholders, and embeds empathy throughout the design process. Flexible for VR or 3D desktop platforms, Co-creating Personas drives depth, nuance, and stakeholder buy-in.

'''How to use it?'''

# Identify relevant stakeholders to analyze and meaningful personas.
# Define an archetype for your persona.
# Describe the motivations that move the user.
# Describe the pain points the persona could encounter.
# Decorate with emojis/images the picture of the persona to better define its profile.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-115&t=jRTjE5JDjxvV23M4-4 Co-Creative Workshops] ====
[[File:Co-Creative Workshops.png|alt=Co-Creative Workshops|thumb|343x343px|Co-Creative Workshops - CC BY-NC-SA 4.0]]
Co-creative Workshops leverage the expertise of invited stakeholders to jointly develop rich personas and service artifacts within virtual worlds. Participants adopt avatar identities aligned with target segments and contribute real-world observations, motivations, behaviors, and pain points through interactive exercises.

As the group clusters and refines characteristics, they animate personas in scenario enactments to validate assumptions and reveal hidden needs. Facilitators guide collaborative storytelling, encourage role-swapping, and capture emergent themes on 3D canvases. Ideal for VR or desktop 3D platforms, Co-creative Workshops foster shared ownership, deepen empathy, build consensus, and deliver nuanced personas that inform subsequent journey mapping, prototyping, and co-design activities.

'''How to use it?'''

# Select a topic of discussion
# Assign to each participant a role from the archetype wheel and list it in the boxes.
# Identify a reporter of the discussion.
# Start the discussion and make sure every participant is interpreting the point of view of their archetype.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-242&t=jRTjE5JDjxvV23M4-4 Emotional Journey Map] ====
[[File:Emotional Journey Map.png|alt=Emotional Journey Map|thumb|340x340px|Emotional Journey Map - CC BY-NC-SA 4.0]]
Emotional Journey maps shifts in user perception and emotional valence across a service experience in a virtual world. Designers plot rising and falling emotional states along a spatial timeline using 3D curves or color-coded overlays. During scenario enactments, avatars display real-time emotional cues—gestures, facial animations, environmental feedback—which observers annotate to pinpoint stress peaks, delight moments, or ambivalence.

Through iterative replay, teams co-design interventions to smooth pain points and amplify positive highlights. Ideal for VR or immersive 3D platforms, Emotional Journey fosters deep empathy by externalizing subjective experience, aligning stakeholders around shared emotional insights, and driving targeted, affective service improvements.

'''How to use it?'''

# Break down the user Journey of the project in steps and represent them in the slots.
# Following the User Journey above, represent with a line the emotions the user feels while going through its journey.
# For every significant emotional step, note down which opportunities emerge.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-293&t=jRTjE5JDjxvV23M4-4 Impact Journey] ====
[[File:Impact Journey.png|alt=Impact Journey|thumb|340x340px|Impact Journey - CC BY-NC-SA 4.0]]
Impact Journey is a foresight tool that models and evaluates effects of a service experience across environmental, social, and economic dimensions in an interactive virtual world. Participants enact key touchpoints as avatars—customers, service personnel, suppliers—while indicators trace resource consumption, waste streams, community benefits, and carbon footprints along the timeline.

Observers pause and propose sustainable alternatives—material substitutions, process optimizations, circular loops—and visualize their impact using dynamic overlays. By embedding sustainability metrics into storytelling and roleplay, Impact Journey fosters empathy, uncovers unintended consequences, and generates actionable creative ideas for sustainable, resilient service ecosystems. Ideal for VR workshops on sustainable innovation.

'''How to use it?'''

# Break down the System Phases of the project in steps and list them in the slots on the left.
# Define meaningful areas of impact for the project such as environment, society, economy etc... and list them.
# For every area, define metrics of evaluation such as resource consumption, waste streams, community benefits, carbon footprints etc... and list them.
# Crossing the system phases of your project and the areas of impact, define (when necessary) relevant sustainable alternatives for the current solutions.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-356&t=jRTjE5JDjxvV23M4-4 Mapping Journeys] ====
[[File:Mapping Journeys.png|alt=Mapping Journeys|thumb|338x338px|Mapping Journeys - CC BY-NC-SA 4.0]]
Mapping Journeys visualizes the service ecosystem around physical and digital products by creating spatial, interactive maps in VR or 3D platforms. Participants drag and connect avatars, 3D tokens, or digital artifacts to represent users, touchpoints, channels, and product interactions across layered environments. As teams assemble and reposition elements, they surface dependencies, information flows, and ecosystem boundaries, running “what-if” experiments by introducing new nodes or rerouting connections.

Observers and co-creators annotate live, revealing optimization opportunities and integration points. While it offers limited narrative depth on its own, Mapping Journeys excels at immersive spatial analytics, fostering collaborative sense-making and aligning cross-functional teams around holistic service landscapes.

'''How to use it?'''

# Identify relevant actors to analyze (Users, Industries...).
# Identify relevant actions to analyze (Purchase, Log-in...).
# Identify relevant connections to analyze (Personal relationship, wi-fi connection...).
# Create as many user journeys as necessary for comparison and gather relevant insights from it.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-465&t=jRTjE5JDjxvV23M4-4 System Map] ====
[[File:System Map.png|alt=System Map|thumb|347x347px|System Map - CC BY-NC-SA 4.0]]
System Map is an immersive spatial tool for visualizing all actors and components involved in service delivery within virtual worlds. Designers create a shared 3D canvas where avatars or tokens represent users, frontline staff, support systems, digital platforms, and environmental elements.

Participants drag, position, and link these modules to trace information flows, handoffs, and boundaries between subsystems. Observers could filter layers, highlight dependencies, and annotate friction points in real time.

While direct roleplay is minimal, teams can embed scenarios by triggering animations or path simulations. Ideal for VR or desktop-based 3D workshops, System Map fosters clarity of complex architectures, aligns cross-functional understanding, and informs optimization strategies.

'''How to use it?'''

# Identify relevant actors to analyze (Users, Industries...).
# Identify relevant touchpoints to analyze (Social media engagement, in-person interactions...).
# Identify relevant connections to analyze (Personal relationship, wi-fi connection...).
# Add all the element in the map and profile a comprehensive system.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-565&t=jRTjE5JDjxvV23M4-4 System Scenario] ====
[[File:System Scenario.png|alt=System Scenario|thumb|349x349px|System Scenario - CC BY-NC-SA 4.0]]
System Scenario is a dynamic simulation tool that models how a service ecosystem adapts and evolves under specific conditions. In a virtual 3D or VR environment, participants configure scenario parameters—seasonal demand spikes, regulatory shifts, tech failures—and watch animated system components (avatars, processes, data flows) respond in real time.

Observers can pause, tweak variables, and branch into alternative futures to test resilience and spot emergent behaviors.

Ideal for avatar-driven storytelling and scenario planning in immersive platforms, System Scenarios deepen understanding of systemic dynamics, foster collaborative “what-if” exploration, and surface strategic interventions before real-world rollout.

'''How to use it?'''

# Define a scenario and express it with a What-if formula
# Give a title to the scenario.
# Define and prioritize relevant actors.
# Place them in the map and define their connections.
# Identify emerging pain points and opportunities.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-636&t=jRTjE5JDjxvV23M4-4 Transition Journey] ====
[[File:Transition Journey.png|alt=Transition Journey|thumb|339x339px|Transition Journey - CC BY-NC-SA 4.0]]
Transition Journey is a dynamic tool that maps and analyzes how user behavior and roles evolve over time within a service ecosystem. In virtual worlds, participants embody avatars that transition through sequential personas—novice to expert, customer to advocate—navigating branching scenarios that illustrate changing motivations, skills, and expectations.

Teams simulate multiple horizons and tweak transition triggers (feature rollouts, policy shifts, social influences) in real time, uncovering new experience archetypes and potential friction points. Observers pause, annotate, and co-design adaptive interventions on the fly.

Ideal for immersive VR workshops, Transition Journey combines narrative forecasting with spatial roleplay to drive strategic foresight and align stakeholders around future-ready service roadmaps.

'''How to use it?'''

# Define the target user.
# Identify their motivations and pain points.
# Define multiple possible user journeys.
# Use transition arrows to explore where the journeys could transit, in order to discover pain points and opportunities.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Develop ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3164&t=jRTjE5JDjxvV23M4-4 AI Functionalities Cards] ====
[[File:AI Functionalities Cards.png|alt=AI Functionalities Cards|thumb|335x335px|AI Functionalities Cards - CC BY-NC-SA 4.0]]
AI Functionalities Cards are a spatial ideation tool designed to spark innovation by showcasing modular AI capabilities—natural language processing, computer vision, recommendation engines, anomaly detection, and more—as tangible cards in virtual environments. Participants navigate VR or 3D workspaces where avatars draw from a digital deck of functionality cards, combining and placing them along service journeys or ecosystem maps.

Through iterative play, teams discover novel applications, align technical possibilities with user needs, and generate creative service enhancements. Ideal for immersive brainstorming sessions, AI Functionalities Cards democratize AI knowledge, foster cross-disciplinary collaboration, and accelerate the translation of emerging technologies into practical, user-centered service concepts.

'''How to use it?'''

# After defining your project, identify which category of AI could be implemented among the four.
# Use the AI functionalities cards to gain knowledge and inspiration for AI integration.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3250&t=jRTjE5JDjxvV23M4-4 Concept Walkthrough] ====
[[File:Concept Walkthrough.png|alt=Concept Walkthrough|thumb|335x335px|Concept Walkthrough - CC BY-NC-SA 4.0]]
Concept Walkthrough is a guided, immersive, step-by-step 3D or VR tour that presents a service concept through sequential stages, enabling stakeholders to experience proposed features and flows in context. Creators animate avatars or interactive hotspots to demonstrate each touchpoint—from discovery to service completion—while participants observe, comment, and suggest ongoing improvements in real time.

By visualizing the envisioned journey step by step, teams gain early user feedback, validate assumptions, and align on requirements before heavy investment. Ideal for VR-enabled workshops or desktop co-creation sessions, Concept Walkthroughs offer moderate immersion, clarity of vision, and structured, seamless collaboration to refine service concepts collaboratively.

'''How to use it?'''

# Define the user journey of your project.
# Use text to define every step of the journey.
# Use drawing/images to add details to every step, paying attention to the crucial steps of the journey.
# Note down pain point and opportunities emerging.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3299&t=jRTjE5JDjxvV23M4-4 Ecosystem Map] ====
[[File:Ecosystem Map .png|alt=Ecosystem Map|thumb|335x335px|Ecosystem Map - CC BY-NC-SA 4.0]]
The Ecosystem Map is an immersive, synthetic visualization that captures all stakeholders and value exchanges within a service ecosystem. Participants arrange avatars or 3D tokens to represent individuals, organizations, technological components, and environmental elements in a looping network, then animate flows to trace information, resource, or interaction exchanges.

In VR or 3D platforms, collaborators navigate the spatial model, simulate adding or removing nodes, and observe systemic impacts in real time. Observers annotate insights and co-design strategic interventions on the fly. Perfect for high-collaboration workshops, the Ecosystem Map aligns diverse perspectives, uncovers hidden relationships, and drives holistic service strategy through richly immersive co-creation.

'''How to use it?'''

# Define a central user and put it at the center of the canvas.
# Describe relevant players and associate to each a different shape.
# Place shapes in the map.
# Central players should be placed close to the center, secondary players peripherically.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3340&t=jRTjE5JDjxvV23M4-4 Future Backcasting] ====
[[File:Future Backcasting.png|alt=Future Backcasting|thumb|332x332px|Future Backcasting - CC BY-NC-SA 4.0]]
Future Backcasting is a foresight tool that reverses time to identify pathways from desired future outcomes back to present-day actions within virtual worlds. Participants embody avatars representing future stakeholders to enact scenarios in 3D or VR environments, dramatizing how emerging trends and innovations influence service evolution.

By simulating and discussing milestones—policy shifts, technological breakthroughs, user behaviors—teams map backward through decision points, uncovering present-day interventions and design inspirations. This method fosters long-term thinking, anticipates challenges, and aligns organizational vision by translating futures into actionable roadmaps. Ideal for co-creative workshops in VR or virtual platforms, Future Backcasting drives foresight and strategic innovation.

'''How to use it?'''

# Identify a relevant topic or a relevant industry.
# Define a year in the future to set the backcasting.
# Decide in which category of future (Possible, Plausible, Probable, Preferred) the backcasting will be set.
# Describe the foresight.
# Describe which steps are needed to achieve the foresight.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3391&t=jRTjE5JDjxvV23M4-4 System UX Map Human Agent Journey] ====
[[File:System UX Map Human Agent Journey.png|alt=System UX Map Human Agent Journey|thumb|335x335px|System UX Map Human Agent Journey - CC BY-NC-SA 4.0]]
Human Agent Journey visualizes the step-by-step path a person takes to achieve a goal, illustrating agent, scenario, expectations, phases, actions, and insights in an immersive virtual environment. Participants embody an avatar representing the human agent and progress through journey stages—awareness, exploration, decision, fulfillment, and reflection—within a shared 3D or VR space.

Observers annotate key touchpoints, emotional states, and backstage processes in real time, then pause to highlight pain points or design opportunities. By spatializing each phase and mapping opportunities directly onto the journey, this method fosters empathy, aligns stakeholders around human motivations, and accelerates co-creation of service experiences shaped by real user needs.

'''How to use it?'''

# Define a human agent (user)
# Identify a scenario and expectations
# Break down the user journey in phases and list them.
# Define which actions (High-level behaviors and steps taken by users. They have a narrative scope, they're not meant to be a step-by-step log of every discrete interaction) the human agent will perform.
# Identify emerging opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3444&t=jRTjE5JDjxvV23M4-4 Future-State Journey] ====
[[File:Future-State Journey.png|alt=Future-State Journey|thumb|332x332px|Future-State Journey - CC BY-NC-SA 4.0]]
Future-State Journey uses narrative structures to guide co-creative exploration of envisioned service experiences. Participants apply the classic dramatic arc—exposition, rising action, climax, falling action, resolution—to a future-state customer journey mapped three to five years ahead. In virtual 3D or VR environments, collaborators embody avatars to spatialize journey stages, enact critical moments, and iterate plot-driven touchpoints.

By dramatizing emotional peaks and challenges, teams spark innovative ideas, uncover pivotal design opportunities, and maintain focus on strategic objectives. Ideal for immersive workshops, this method balances storytelling, spatial roleplay, and moderate collaboration, facilitating cohesive stakeholder alignment and rapidly accelerating future-focused ideation.

'''How to use it?'''

# Define a user journey or, if present, consider an existing one for this exercise. Focus on the emotional peaks and challenges arising from the experience.
# Identify where there is room for Jobs To Be Done (JTBD) and highlight it on the map .
# Now, rework the user journey imagining the experience in the future. How can JTBD be addressed by future developments?
# Identify which are the emerging opportunities.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3625&t=jRTjE5JDjxvV23M4-4 Innovative Brainstorming] ====
[[File:Innovative Brainstorming.png|alt=Innovative Brainstorming|thumb|334x334px|Innovative Brainstorming - CC BY-NC-SA 4.0]]
Innovative Brainstorming is an inclusive, fast-paced ideation technique that stimulates spontaneous thought by leveraging spatialized virtual tools and avatar-led interaction. In a VW workshop, participants converge on a shared digital whiteboard or 3D canvas, where facilitators introduce provocations, constraints, or stimulus cards.

Avatars then rapidly generate, cluster, and remix ideas through drawing, tagging, and connecting virtual sticky notes, while voice or gesture commands add energy and variety. Real-time voting and theme-based breakout areas help surface promising concepts. By combining classic free-form brainstorming with immersive, gamified mechanics, Innovative Brainstorming boosts engagement, taps collective creativity, and fuels a rich pipeline of breakthrough service innovations.

'''How to use it?'''

# Define a topic to brainstorm.
# Brainstorm any idea related to the topic in question in the warming up section.
# Select ideas within close personal or obvious contexts and list them in the braindump section.
# Use braindump ideas to inspire new ideas going in different . directions and list them in the divergent thinking section.
# Use the most promising ideas from the divergent thinking section to create new creative ideas in the creative ideation section.

<blockquote>Inspired by the toolkit: Share, learn, innovate! Publisher: United Nations

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3646&t=jRTjE5JDjxvV23M4-4 Integrated Journey] ====
[[File:Integrated Journey.png|alt=Integrated Journey|thumb|329x329px|Integrated Journey - CC BY-NC-SA 4.0]]
Integrated Journey extends traditional journey mapping into a comprehensive service blueprint within virtual worlds, visualizing customer touchpoints alongside backstage processes, technology systems, and stakeholder roles. In an immersive 3D environment, designers arrange avatars, swimlanes, and interactive nodes on a shared timeline to show how front-stage interactions trigger behind-the-scenes support functions and data flows.

Participants witness real-time animations of handoffs, decision points, and policy enforcements, pausing to annotate inefficiencies or propose enhancements. Avatars can enact role-specific perspectives—agent, IT, logistics—adding realism. Perfect for VR-enabled co-creation workshops, Integrated Journey aligns multidisciplinary teams, uncovers interdependencies, and accelerates holistic service innovation.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Define, for each phase, the technical journey (Steps and activities that the technical artifact performs behind the scenes to support interactions with/between human agents.)
# Define, for each phase, the provider journey (Steps, choices, activities, and interactions that providers perform while offering a service to reach a particular goal, they can be visible to users or performed in the back-end / asynchronously).
# Identify emerging opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3712&t=jRTjE5JDjxvV23M4-4 Journey Ideation with Dramatic Arcs] ====
[[File:Journey Ideation with Dramatic Arcs.png|alt=Journey Ideation with Dramatic Arcs|thumb|330x330px|Journey Ideation with Dramatic Arcs - CC BY-NC-SA 4.0]]
Journey Ideation with Dramatic Arcs is a co-creation method that applies narrative structures to service design in virtual worlds. Teams leverage classic dramatic arcs to outline user journeys, mapping emotional peaks and transitions across touchpoints.

In immersive 3D or VR environments, participants embody avatars to spatialize journey stages, visually enact pivotal moments, and explore plotlines. Observers refine service concepts by injecting unexpected challenges, resolving friction, and imagining future scenarios.

This approach deepens empathy, sparks insights, and aligns stakeholders around rich narratives. Ideal for future-focused workshops, it transforms abstract journeys into engaging storyworlds for iterative ideation.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Color the numbers ranking the customer engagement levels of every step of your journey from 1 (Low) to 6 (High).
# Reflect on the shape and rhythm of the whole arc. Is it overloaded? Frontloaded? Are the periods of low engagement or high engagement too long?
# Must a highlight be added, or - this is often more practical - should a less engaging step be spotlighted to increase engagement and show value more clearly?

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing
Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3856&t=jRTjE5JDjxvV23M4-4 Service Image] ====
[[File:Service Image.png|alt=Service Image|thumb|329x329px|Service Image - CC BY-NC-SA 4.0]]
Service Image distills the essence of a service experience into a single, impactful visual snapshot within a virtual world. Designers stage a 3D scene with avatars, environmental cues, and animated highlights to convey core touchpoints and emotional tone at a glance. This diorama-style frame employs perspective, lighting, and symbolic elements to communicate user motivations, pain points, and moments of delight cohesively.

By presenting an evocative north-star vision, Service Image aligns stakeholders around the narrative, sparks creative ideation, and guides subsequent design iterations. Ideal for kickoff sessions, pitches, and virtual galleries, it crystallizes complex experiences into an instantly sharable form.

'''How to use it?'''

# Create a service image, it can be a montage of different photos and scenes, or a post-produced photo realized ad hoc, focused on a hero moment that is able to encapsulate the core value of the service experience.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3868&t=jRTjE5JDjxvV23M4-4 System UX Map Artificial Agent Journey] ====
[[File:System UX Map Artificial Agent Journey.png|alt=System UX Map Artificial Agent Journey|thumb|326x326px|System UX Map Artificial Agent Journey - CC BY-NC-SA 4.0]]
System UX Map Agent Journey visualizes AI/ML system interactions and human collaboration within virtual worlds. Participants guide avatars representing data pipelines, models, and human operators across a spatial timeline that highlights when core AI elements—data ingestion, feature engineering, model training, inference—are generated and required.

Relationships between automated agents and human stakeholders are dynamically mapped, enabling stakeholders to pause, annotate, and adjust nodal connections in real time. Ideal for VR or 3D workshops with multidisciplinary teams, this tool clarifies technical workflows, uncovers integration bottlenecks, and fosters shared understanding. By combining agent-driven storytelling with immersive simulation, teams co-design robust, human-centered AI services.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Define, for each phase, the technical journey (Steps and activities that the technical artifact performs behind the scenes to support interactions with/between human agents).
# Define, for each phase, the artificial journey (Internal processes and interactions that support service delivery through the technical artifact. They involve the agency of Al systems).
# Identify emerging opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3935&t=jRTjE5JDjxvV23M4-4 User Scenario] ====
[[File:User Scenario.png|alt=User Scenario|thumb|335x335px|User Scenario - CC BY-NC-SA 4.0]]
User Scenarios bring envisioned service experiences to life through compelling narratives that follow a user’s journey in context. In a virtual 3D or VR environment, avatars embody personas and enact stories that illustrate goals, motivations, and pain points at each stage of interaction—discovery, decision, execution, and reflection.

Observers and co-designers watch, annotate, and pause the action to probe underlying assumptions, explore alternative paths, or inject new ideas. By weaving storytelling with spatial simulation, User Scenarios deepen empathy, align stakeholder mental models, and reveal hidden requirements. Ideal for co-creative workshops in immersive platforms, User Scenarios seamlessly integrate simulation, roleplay, and narrative ideation into service design.

'''How to use it?'''

# Define a context for each scenario.
# Define the characters (e.g. users, providers...) involved in the scenario.
# Identify the needs involved.
# Writing a story, define a user scenario in a narrative manner, focusing in describing how the user is going to interact with the service during a specific situation of everyday life.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Develop // Deliver ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-3996&t=jRTjE5JDjxvV23M4-4 Rough Prototyping] ====
[[File:Rough Prototyping.png|alt=Rough Prototyping|thumb|330x330px|Rough Prototyping - CC BY-NC-SA 4.0]]
Rough Prototyping is a rapid, low-fidelity method for mocking up service ideas using simple virtual assets available on demand in VR or 3D platforms. Teams embody avatars that assemble, rearrange, and annotate digital placeholders—such as basic shapes, sketch overlays, or interactive widgets—to explore concepts in real time.

By minimizing production effort, participants test multiple variations, iterate service touchpoints, and gather immediate feedback without heavy technical overhead. Although roleplay depth is limited compared to immersive simulations, Rough Prototyping excels at fostering spontaneous creativity, aligning stakeholder understanding, and validating design assumptions. This high-velocity approach empowers teams to quickly brainstorm and converge collaboratively.

'''How to use it?'''

# Define, which are the main touchpoints (Devices, places, tools, perceivable clues that users interact with) involved in the project.
# For each touchpoint, define the technical requirements.
# Create paper/digital mockups for all the touchpoints and start experimenting/testing the user journey.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-4026&t=jRTjE5JDjxvV23M4-4 Experience Prototypes] ====
[[File:Experience Prototypes.png|alt=Experience Prototypes|thumb|322x322px|Experience Prototypes - CC BY-NC-SA 4.0]]
Experience Prototypes are interactive simulations of key service touchpoints within virtual worlds. They let teams rapidly prototype and test specific moments in a journey—such as checkout kiosks, support chatbots, or onboarding flows—by building high-fidelity mock-ups in VR or 3D spaces.

Participants embodied as avatars interact with digital artifacts, providing real-time feedback on usability, emotional resonance, and process efficiency. Through iterative cycles, designs are refined on the fly, uncovering hidden pain points and validating solutions before development. Ideal for virtual co-design workshops, Experience Prototypes enhance immersion, align stakeholders around tangible interactions, and accelerate service innovation within a holistic end-to-end context.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Prototype, for each phase, the user journey and start experimenting/testing the touchpoints.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-4074&t=jRTjE5JDjxvV23M4-4 Role Playing] ====
[[File:Role Playing.png|alt=Role Playing|thumb|320x320px|Role Playing - CC BY-NC-SA 4.0]]
Role Playing brings a hypothetical service to life through avatar enactment in virtual worlds. Users assume persona roles—customers, frontline staff, or partners—and act out journey scenarios in immersive VR or 3D environments. As avatars, participants navigate scripted or spontaneous interactions, responding to prompts, making decisions, and adapting to system feedback.

Observers can pause, annotate, and adjust scenarios on the fly to explore alternative behaviors, emotional responses, and process variations. This high-engagement method fosters deep empathy, surfaces usability issues, and validates service flows before development. Ideal for remote co-creation workshops, Role Playing aligns multidisciplinary teams around user perspectives and informs iterative design improvements.

'''How to use it?'''

# Create a scenario: define the context, the characters and the needs involved and narrate through a story the scene.
# Define some roles (e.g. the user, the service employee, etc.) and assign them to the participants.
# If needed, prepare rough prototypes or other materials that can facilitate the performance.
# While a team is acting out their story, the rest of the audience learn about the idea, understand the high-level sequence of actions required and get to know the hero moments.
# List the hero moment(s).

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

=== Deliver ===

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-821&t=jRTjE5JDjxvV23M4-4 Desktop System Mapping] ====
[[File:Desktop System Mapping.png|alt=Desktop System Mapping|thumb|322x322px|Desktop System Mapping - CC BY-NC-SA 4.0]]
Desktop System Mapping, known as Business Origami, is a tactile method for visualizing complex value networks by arranging simple paper cutouts—or, in virtual worlds, draggable avatars and 3D tokens—on a shared collaborative workspace. Participants represent key people, locations, channels, and touchpoints with standardized symbols, connecting elements to reveal relationships, dependencies, and information flows.

In VR or immersive 3D platforms, collaborators reposition tokens, annotate linkages, and simulate network changes in real time. This approach clarifies service ecosystems, aligns stakeholder mental models, and fosters collective sense-making. Desktop System Mapping excels at uncovering structural insights, driving collaborative strategy, and achieving strategic alignment.

'''How to use it?'''

# Define the main scope of your prototype
# Define the level of detail of the prototype
# Create paper/digital cutouts of the prototype and start testing/simulate talking points using the models on the table.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-854&t=jRTjE5JDjxvV23M4-4 Desktop Walkthrough] ====
[[File:Desktop Walkthrough.png|alt=Desktop Walkthrough|thumb|320x320px|Desktop Walkthrough - CC BY-NC-SA 4.0]]
Desktop Walkthrough is a low-fidelity prototyping tool that brings teams together around a shared simulation of a service journey in a virtual world. Participants embody avatars to step through each critical touchpoint—sign-up, payment, support—while observers annotate pain points, decision triggers, and contextual cues.

By projecting simple mock-ups of screens, environments, and process steps into a 3D or VR space, teams quickly gain a unified understanding of end-to-end experiences and surface hidden issues. Iterative “play-throughs” enable real-time adjustments to sequences, handoffs, and interface layouts. Ideal for early-stage co-creation workshops, Desktop Walkthrough accelerates alignment, empathy, and rapid identification of critical journey enhancements.

'''How to use it?'''

# Define the user journey of your project and create a visual representation of it using emojis/imported images

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1021&t=jRTjE5JDjxvV23M4-4 Emotional Journey Feedback] ====
[[File:Emotional Journey Feedback.png|alt=Emotional Journey Feedback|thumb|317x317px|Emotional Journey Feedback - CC BY-NC-SA 4.0]]
Emotional Journey Feedback extends the System UX Map by overlaying users’ emotional states across every phase of their experience in virtual worlds. A continuous “emotion line” traces peaks and valleys—signaling stress points, moments of delight, and transitional shifts—plotted along a spatialized service timeline.

In VR or 3D environments, avatars convey real-time emotional cues through gestures, facial expressions, or ambient lighting changes that correspond to the graph. Participants can pause, annotate, and iterate scenarios to smooth pain points or amplify positive highlights. Ideal for immersive co-design workshops, this tool deepens empathy, enhances feedback loops, and strengthens narrative-driven storytelling in service innovation.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, for each phase which are the touchpoints (Devices, places, tools, perceivable clues that users interact with) involved.
# Define, for each phase, the technical journey (Steps and activities that the technical artifact performs behind the scenes to support interactions with/between human agents.)
# For each step, consider the emotional feedback of the user and keep track of it in the canvas.
# Identify emerging pain points and opportunities.

<blockquote>Inspired by the toolkit: AI4Gov Toolkit Publisher: AI4Gov

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1081&t=jRTjE5JDjxvV23M4-4 Investigative Rehearsal] ====
[[File:Investigative Rehearsal.png|alt=Investigative Rehearsal|thumb|316x316px|Investigative Rehearsal - CC BY-NC-SA 4.0]]
Investigative Rehearsal is a theatrical tool that uses iterative roleplay to uncover and refine service behaviors within virtual worlds. Participants embody avatars to act out scenarios—customer interactions, back-end workflows, decision points—while observers note emergent patterns and friction points.

Through multiple rehearsal loops, teams adjust roles, scripts, and environment affordances in real time, testing alternative responses and process variations. This method fosters deep empathy, reveals implicit knowledge, and surfaces systemic issues that workshops might miss. Ideal for VR or richly immersive 3D platforms, Investigative Rehearsal accelerates behavioral insight, aligns stakeholder mental models, and co-designs optimized service experiences grounded in lived enactment.

'''How to use it?'''

# Define the scene and research question.
# Assign actors with roles and scenario details.
# Observers watch a brief scene enactment.
# Observers reflect on current knowledge and feelings.
# Replay the scene, pausing to suggest changes and improvements.
# Document observations and insights throughout.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1136&t=jRTjE5JDjxvV23M4-4 Rehearsing Digital Services] ====
[[File:Rehearsing Digital Services.png|alt=Rehearsing Digital Services|thumb|319x319px|Rehearsing Digital Services - CC BY-NC-SA 4.0]]
Rehearsing Digital Services is a variant of Investigative Rehearsal that prototypes digital interfaces through embodied, actor-led simulations in virtual worlds. Participants—represented as avatars—take on customer, agent, or system roles and act out conversational and transactional flows: chatbot dialogs, voice assistants, form interactions, and error recoveries.

Facilitators guide scenarios in VR or 3D platforms, narrating screen states and system prompts aloud as avatars interact with on-screen elements. Iterative enactments expose usability gaps, friction points, and emotional reactions, enabling real-time script tweaks, UI refinements, and branching-logic tests. Ideal for immersive co-creation workshops, Rehearsing Digital Services drives shared understanding, empathy, and alignment around seamless digital service experiences.

'''How to use this?'''

# Define the scene and research question.
# Assign roles and outline the scenario.
# Have teams act out the scene briefly to observe.
# Observe, understand feelings and current dynamics.
# Iterate by pausing and suggesting changes focused on service digitalization.
# Reflect on how to digitally transform and enact the service experience.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1193&t=jRTjE5JDjxvV23M4-4 Service Blueprint] ====
[[File:Service Blueprint.png|alt=Service Blueprint|thumb|316x316px|Service Blueprint - CC BY-NC-SA 4.0]]
Service Blueprint is a comprehensive mapping technique that visualizes every stage of service delivery—front-stage interactions, backstage processes, support systems, and physical or digital touchpoints—in a unified blueprint. In virtual environments, designers arrange swim-lane structures on a 3D canvas, deploying avatars to simulate customer and staff roles and animating process flows in real time.

Participants annotate decision gateways, handoffs, and dependencies while observing both visible and hidden service elements. This immersive representation reveals systemic inefficiencies, clarifies ownership, and guides co-design of seamless experiences. Ideal for VR or desktop-based co-creation workshops, Service Blueprint accelerates alignment, optimizes workflows, and de-risks implementation through collective visualization and iteration.

'''How to use it?'''

# Break down the user journey in phases and, for each phase define its steps.
# Define, a main user and secondary users and place them in the other areas.
# Consider the Interaction Area and place other entities the main user interacts with and the Visibility Area and place players, functionalities invisible to the user.
# Map connection between the users and define the project ecosystem.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1226&t=jRTjE5JDjxvV23M4-4 Service Prototype] ====
[[File:Service Prototype.png|alt=Service Prototype|thumb|312x312px|Service Prototype - CC BY-NC-SA 4.0]]
Service Prototype simulates real user interactions with service touchpoints in virtual environments. Designers create interactive mock-ups—digital kiosks, chatbots, mobile interfaces—and deploy them in VR or 3D worlds.

Participants embody avatars to engage with prototypes as they would in real life: querying a virtual assistant, placing an order through a mock interface, or interacting with augmented customer support. Real-time feedback sessions record usability metrics, emotional reactions, and friction points. Iterative cycles refine prototypes, ensuring functionality, aesthetics, and experience quality align with user expectations. Perfect for immersive co-creation workshops, Service Prototypes accelerate validation, enhance stakeholder feedback, and de-risk service launch.

'''How to use it?'''

# Define a precise User Journey and describe it in steps.
# Assign roles to participants.
# Choose touchpoints to be prototyped.
# Reenact the service using the prototypes. This tool has the objective of replicating, as much as possible, the final experience of interacting with the service, in order to test and validate all the design choices.

<blockquote>Inspired by the toolkit: Servicedesigntools Publisher: oblo.design

Toolkit License: CC BY-NC-SA 4.0</blockquote>

==== [https://www.figma.com/board/zXsNUSOj1H0wzurjMedMAP/OpenVerse_Toolkit?node-id=3-1300&t=jRTjE5JDjxvV23M4-4 Subtext] ====
[[File:Subtext.png|alt=Subtext|thumb|316x316px|Subtext - CC BY-NC-SA 4.0]]
Subtext is a theatrical method that can reveal deeper motivations and needs by focusing on unspoken thoughts in a rehearsal session.

Perfect for exploring non-verbal communication and emotions in VW rehearsals; enhances depth of co-creative exploration.

'''How to use it?'''

# Choose a key scene you want to understand more deeply
# Select and assign roles of actors, who will play the key scene once.
# Select and assign roles of subtext actors for each actor.
# The character actors will play the scene as usual – or perhaps a little slower – and the subtext actors will simply speak what they believe their characters are thinking at any moment, using “I” or “me” statements when possible. For example, the character actor might say, “Can you prioritize that?” and his subtext actor might rage, “For f*ck’s sake! Help me before I lose my job, you idiot!”
# Iterate.

<blockquote>Inspired by the toolkit: This is Service Design Doing Publisher: This is Service Design Doing

Toolkit License: CC BY-NC-SA 4.0</blockquote>

B-prepared

2026-09-01T14:53:33Z

CollectiveIntelligenceAdmin:

=== B-prepared Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101121134 || 01/10/2023 || 30/09/2026 || HUN-REN SZAMITASTECHNIKAI ES AUTOMATIZALASI KUTATOINTEZET / Hungary
|}
=== Project description ===
In case of a disaster, 'plan A' is that first responders arrive and save everyone. Until then, everyone needs a 'plan B'. Despite existing learning materials and disaster alert apps available to the public, neither those solutions nor traditional information campaigns significantly increased citizen preparedness, and live drills are extremely expensive. The EU-funded B-prepared project aims to teach disaster survival skills to European citizens. To that end, it will create a collaborative co-creation platform to collect learning materials, formulate curricula, perform cross-platform learning progress tracking, and deliver the learning content using virtual reality and gamification via the medium of a mobile app. The platform is open for content and game developers, projects, and other stakeholders via application programming interfaces.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || Incremental Learning Through Fusion of Discrete Anomaly Models from Odometry Signals in Autonomous Agent Navigation || https://doi.org/10.1109/SIPS62058.2024.00023
|-
| AI, Machine Learning & Data Science || Conference proceedings || Integrated Learning and Decision Making for Autonomous Agents through Energy based Bayesian Models || https://doi.org/10.23919/FUSION59988.2024.10706431
|-
| Education, Training & Serious Games || Other || KI-gestützte Dialogsysteme in Serious Games als Trainingsumgebung für den Umgang mit Naturkatastrophen || https://doi.org/10.5281/ZENODO.15434476
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Optimizing QoE for Virtual Reality Games on Mobile Edge Networks || https://doi.org/10.5281/ZENODO.15397069
|-
| Robotics, Manufacturing & Industry 4.0 || Conference proceedings || Self-Supervised Path Planning in UAV-aided Wireless Networks based on Active Inference || https://doi.org/10.1109/ICASSP48485.2024.10446575
|}

AVATAR

2026-09-01T14:53:27Z

CollectiveIntelligenceAdmin:

"=== AVATAR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/190147557 || 01/06/2023 || 31/05/2025 || AVATAR MEDICA / France
|}
=== Project description ===
Surgeons rely on medical images to make critical decisions. Poorly interpreted MRIs and CT scans can result in unnecessary surgeries, more invasive procedures and slower recoveries. The ERC-funded AVATAR project introduces a revolutionary surgical solution as a highly effective productivity tool for medical specialists and surgeons. It features the first-ever photorealistic XR viewer of 3D medical images, powered by advanced machine learning algorithms and data visualisation techniques. The project aims to improve medical decision-making without investing in new equipment or personnel. Thanks to high-fidelity local or cloud-based rendering, the solution is the first to seamlessly integrate preoperative and intraoperative data, while clinical applications guide surgeons in planning and implementing specific procedures."

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Education, Training & Serious Games || Peer reviewed articles || Using virtual reality to enhance anatomy education for pre-matriculation medical students: an assessment of learning outcomes using a new teaching modality || https://doi.org/10.1007/S44186-025-00345-X
|-
| Healthcare, Medicine & Accessibility || Other || Benefit of virtual reality during visceral artery aneurysms open and endovascular surgery planning || https://doi.org/10.1016/J.JVSCIT.2025.02.279
|-
| Healthcare, Medicine & Accessibility || Other || Surgeon perspectives on a virtual reality platform for preoperative planning in complex bone sarcomas || https://doi.org/10.1016/S0972-978X(24)00340-4
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Three-dimensional virtual reality in surgical planning for breast cancer with reconstruction || https://doi.org/10.1177/2050313X231179299
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Fast-track virtual reality software to facilitate 3-dimensional reconstruction in congenital heart disease || https://doi.org/10.1093/ICVTS/IVAD087
|}

ASP-belong

2026-09-01T14:53:18Z

CollectiveIntelligenceAdmin:

=== ASP-belong Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101080665 || 01/09/2023 || 31/08/2027 || Masarykova univerzita / Czech Republic
|}
=== Project description ===
Poor mental health and social isolation are on the rise among young people, exacerbated by the pandemic. Supportive relationships play a crucial role in mental health and addressing loneliness. Schools currently lack evidence-based interventions to foster a sense of belonging. The EU-funded ASP-belong project has developed Augmented Social Play (ASP), a digital mental health intervention that utilises smartphones to facilitate group experiences. ASP incorporates elements of storytelling, augmented reality, gameplay and psychotherapeutic techniques to enhance mental well-being and foster a sense of group belonging. The project will engage stakeholders in the creation of ASP #1 and its implementation in schools located in Czechia, Portugal and the United Kingdom. This can encourage adoption by policymakers, practitioners and the media.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Exploring the Fit: Analysing Material Selection for Interactive Markers in MAR Games through Co-Design || https://doi.org/10.17605/OSF.IO/BRW98
|-
| Education, Training & Serious Games || Conference proceedings || Making A Real Connection: Pro-Social Collaborative Play in Extended Realities – Trends, Challenges and Potentials || https://doi.org/10.1145/3626705.3626708
|-
| Education, Training & Serious Games || Peer reviewed articles || Challenges and Potentials of Pro-Social Collaborative Play in Extended Realities || https://doi.org/10.1145/3716164
|-
| Ethics, Society, Arts & Culture || Conference proceedings || Navigating through the jungle of international collaborative grants: Lessons learned from ASP-belong project and beyond || https://doi.org/10.17605/OSF.IO/BRW98
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || Integrating ethics in digital mental healthcare technologies: a principle-based empirically grounded roadmap approach || https://doi.org/10.17605/OSF.IO/BRW98
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Gamified Digital Mental Health Interventions for Young People: Scoping Review of Ethical Aspects During Development and Implementation || https://doi.org/10.2196/64488
|}

AI4WORK

2026-09-01T14:53:04Z

CollectiveIntelligenceAdmin:

=== AI4WORK Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135990 || 01/01/2024 || 31/12/2026 || INSTITUT FÜR ANGEWANDTE SYSTEMTECHNIK BREMEN GMBH / Germany
|}
=== Project description ===
In a rapidly evolving technological landscape, the collaboration between humans and machines poses a pressing challenge to the modern workforce. As artificial intelligence (AI) and robotics become integral to various industries, striking the right balance between human ingenuity and machine efficiency remains elusive. The need for optimal work-sharing methods becomes paramount, spanning from manual labour to intricate decision-making processes. In this context, the EU-funded AI4Work project aims to explore and implement practical solutions for the seamless collaboration between humans and AI/robots. The key challenge lies in developing versatile tools like the sliding work sharing (SWS) approach, adapting the balance between human and machine activities based on situational context and interactions.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || Manufacturing workers fatigue: an exploratory study on predictive machine learning and cross-subject generalization with implications for work design || https://doi.org/10.1016/J.IFACOL.2024.09.271
|-
| AI, Machine Learning & Data Science || Conference proceedings || Exploration of core concepts required for mid- and domain-level ontology development to facilitate explainable-AI-readiness of data and models || https://doi.org/10.5281/ZENODO.13148630
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || AI4WORK Project: Human Centric Digital Twin Approaches to Trustworthy AI and Robotics for Improved Working Conditions in Healthcare and Education Sectors || https://doi.org/10.3233/SHTI240581
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Students' Burnout Symptoms Detection Using Smartwatch Wearable Devices: A Systematic Literature Review || https://doi.org/10.3390/AISENS1010002
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || An Overview of Tools and Technologies for Anxiety and Depression Management Using AI || https://doi.org/10.3390/APP14199068
|-
| Robotics, Manufacturing & Industry 4.0 || Book chapters || A Meta-Engine Framework for Interleaved Task and Motion Planning using Topological Refinements || https://doi.org/10.48550/ARXIV.2408.05795
|-
| Robotics, Manufacturing & Industry 4.0 || Conference proceedings || Adaptive Human-Robot Collaborative Missions using Hybrid Task Planning || https://doi.org/10.5281/ZENODO.17074178
|-
| Robotics, Manufacturing & Industry 4.0 || Conference proceedings || Temporal Task and Motion Planning with Metric Time for Multiple Object Navigation || https://doi.org/10.1609/AAAI.V39I25.34874
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Core concepts for mid- and domain-level ontology development || Ontology / Framework || https://doi.org/10.5281/ZENODO.13148630 || Ontologies required to facilitate explainable-AI-readiness of data and models.
|}

ADVHANDTURE

2026-09-01T14:52:58Z

CollectiveIntelligenceAdmin:

=== ADVHANDTURE Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101088708 || 01/10/2023 || 30/09/2028 || INSTITUT NATIONAL DES SCIENCES APPLIQUEES DE RENNES / FRANCE
|}
=== Project description ===
In recent years, there has been a surge in tactile technologies offering a range of haptic sensory experiences. However, virtual reality systems still struggle to deliver convincing tactile sensations for 3D interaction. They fall short in three critical aspects: rendering multiple haptic stimuli coherently in space, achieving temporal integration compatible with interactive framerates, and preserving user immersion in virtual worlds. Funded by the European Research Council, the ADVHANDTURE project introduces an innovative computational approach to enhance multimodal tactile feedback in immersive environments. Its methodology incorporates perceptual data throughout the design of computational models for immersive tactile haptics. The project will develop physics-based models, efficient algorithms and 3D interaction paradigms, offering realistic multi-sensory feedback and enriching interaction with virtual worlds.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Education, Training & Serious Games || Monographic books || Robotics Goes MOOC || https://doi.org/10.1007/978-3-319-77270-7
|-
| Extended Reality (VR/AR/MR) & HCI || Book chapters || Multi-actuator Haptic Handle Using Soft Material for Vibration Isolation || https://doi.org/10.1007/978-3-031-70061-3_21
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Studying the Perception of Vibrotactile Stimulation on the Arm via a Modular Wearable Sleeve || https://doi.org/10.1109/WHC64065.2025.11123226
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || In-Hand Haptic Representation of User's Surroundings in Virtual Reality || https://doi.org/10.1109/WHC64065.2025.11123356
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || FresnelDeformable: A Softness Presentation Technique Combining Fingertip Plane Tilt Manipulation and Pseudo-Stiffness || https://doi.org/10.1145/3706599.3719778
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Enhancing Visuo-Haptic Coherency by Manipulating Fingertip Contact Tilt || https://doi.org/10.1109/VRW66409.2025.00300
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Augmenting the Texture Perception of Tangible Surfaces in Augmented Reality Using Vibrotactile Haptics || https://doi.org/10.1007/978-3-031-70061-3_39
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Designing 3D Object Rendering Techniques for Ultrasound Mid-Air Haptics using Intersection Strategies || https://doi.org/10.1145/3675231.3675235
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || How Different Is the Perception of Vibrotactile Texture Roughness in Augmented versus Virtual Reality? || https://doi.org/10.1145/3641825.3687738
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Does Multi-Actuator Vibrotactile Feedback Within Tangible Objects Enrich VR Manipulation? || https://doi.org/10.1109/TVCG.2023.3279398
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Bimanual Ultrasound Mid-Air Haptics for Virtual Reality Manipulation || https://doi.org/10.1109/TVCG.2024.3417343
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Visuo-Haptic Rendering of the Hand during 3D Manipulation in Augmented Reality || https://doi.org/10.1109/TOH.2024.3358910
|}

AccessVR

2026-09-01T14:52:51Z

CollectiveIntelligenceAdmin:

=== AccessVR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101115807 || 01/01/2024 || 31/12/2028 || KARLSRUHER INSTITUT FUER TECHNOLOGIE / Germany
|}
=== Project description ===
AccessVR will fill the gap in the scientific knowledge on how people with physical disability – particularly people with limited upper- and lower body mobility – access and experience Virtual Reality (VR) technology. Many of the several million physically disabled people in the EU cannot tap into the huge potential of the technology for leisure, education, and work: VR systems are commonly designed for non-disabled human bodies, but as a result of the complexity of VR technology, fundamental accessibility barriers for physically disabled users remain unaddressed. AccessVR addresses this issue through development of an experience-centric framework for accessible VR technology. The framework will build on technology case studies and a modular VR application that address physical and digital access barriers to VR, and will be constructed against disability studies as theoretical backdrop. The first phase of the research will examine preferences and needs of disabled people regarding user interfaces and representation of disability in VR through co-creation of individually tailored VR prototypes. In a second phase, the project will synthesize outcomes into a middleware layer, and develop an adaptive VR platform featuring entertainment and workplace scenarios. In the third phase, the VR platform will be leveraged to evaluate the experience of physically disabled people in VR to refine the framework based on empirical data. The goal of AccessVR is to further our understanding of how to create engaging VR experiences for people with physical disability that combine the removal of physical, digital, and experiential access barriers. Results are expected to have significant impact on the design of body-centric technology and the inclusion of physically disabled people. Ultimately, AccessVR will enable future research on disability and VR, contribute to the accessible design of the technology, and lay the foundation for more inclusive technological futures.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || aVRness: Leveraging Augmented Virtuality to Increase Real-World Awareness in VR for People with Physical Disabilities || https://doi.org/10.5445/IR/1000184810
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Understanding Accessibility for Physically Disabled Users in VR: Interplay of Physical, Digital, and Experiential Layers || https://doi.org/10.5445/IR/1000184808
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || An Initial Exploration of Low-Cost VR for People With Mobility Disability || https://doi.org/10.1145/3663547.3762152
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || An Equitable Experience? How HCI Research Conceptualizes Accessibility of Virtual Reality in the Context of Disability || https://doi.org/10.5445/IR/1000189614
|}

6G-XR

2026-09-01T14:52:45Z

CollectiveIntelligenceAdmin:

=== 6G-XR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101096838 || 01/01/2023 || 31/12/2025 || OULUN YLIOPISTO / Finland
|}
=== Project description ===
Extended reality (XR) includes virtual reality, augmented reality and mixed reality. These immersive technologies merging the physical with the virtual are now upon us, thanks largely to beyond 5G (B5G) and 6G technologies. The EU-funded 6G-XR project will develop an experimental research infrastructure enabling the demonstration and validation of numerous B5G and 6G technologies/architectures. The initiative includes: a B5G architecture (and eventually 6G) with end-to-end service provisioning and cloud implementation; multi-access edge computing scenarios and their integration into a complete cloud continuum; and demanding, immersive 6G applications such as holographics and so-called digital twins. In addition to technical outcomes, the project will contribute to standards development and energy reduction.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Affection-Centric Metaverse in 6G: Initiative Learning Based In-Network Human-Like Sentimental Analysis || https://doi.org/10.1109/MCOM.001.2300378
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Addressing 3D Digital Twin in Xr Remote Fab Lab Over Sliced 5G Networks || https://doi.org/10.1109/EUCNC/6GSUMMIT63408.2025.11036986
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Energy consumption assessment of a Virtual Reality Remote Rendering application over 5G networks || https://doi.org/10.48550/ARXIV.2510.25357
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Inter-Stream Dependencies in Time-Sensitive Networking || https://doi.org/10.1109/ICIN64016.2025.10943101
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || 6G OTA Measurements at Sub-THz Band Using a Compact Robotic System || https://doi.org/10.23919/EUCAP63536.2025.10999503
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Power calibration methods for frequency extenders aided modulated measurements at sub-THz/THz || https://doi.org/10.23919/GEMIC64734.2025.10979049
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Leveraging 5G Physical Layer Monitoring for Adaptive Remote Rendering in XR Applications || https://doi.org/10.48550/ARXIV.2505.22123
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Remote Rendering for Virtual Reality: Performance Comparison of Multimedia Frameworks and Protocols || https://doi.org/10.48550/ARXIV.2507.00623
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Streaming Remote rendering services: Comparison of QUIC-based and WebRTC Protocols || https://doi.org/10.48550/ARXIV.2505.22132
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || A Hybrid Frequency Offset Estimation Combining Data-Driven Method and Model-Driven Method for 6G OFDMA Systems || https://doi.org/10.1109/AIOT63253.2024.00014
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Towards Energy-Aware Video Streaming in 5G/B5G - Application Perspective || https://doi.org/10.1109/EUCNC/6GSUMMIT63408.2025.11036886
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Formation and Assertion of Data Unit Groups in 3GPP Networks with TSN and PDU Set Support || https://doi.org/10.1109/WCNC57260.2024.10570842
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Characterisation of a D-Band Horn Antenna: Comparison of Near-Field and OTA Measurements || https://doi.org/10.23919/EuCAP60739.2024.10501356
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Addressing Scalability for Real-time Multiuser Holo-portation: Introducing and Assessing a Multipoint Control Unit (MCU) for Volumetric Video || https://doi.org/10.1145/3581783.3613777
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Edge Rendering Architecture for multiuser XR Experiences and E2E Performance Assessment || https://doi.org/10.48550/arXiv.2406.07087
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Multi-Layer Monitoring at the Edge for Vehicular Video Streaming: Field Trials || https://doi.org/10.48550/arXiv.2311.07391
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Context-Aware Adaptive Prefetching for DASH Streaming over 5G Networks || https://doi.org/10.48550/arXiv.2311.07399
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Channel Estimation and Equalization of Zero-Padded Waveforms in Doubly-Dispersive Channels || https://doi.org/10.1109/TCOMM.2025.3582018
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Optimized K-means routing protocol with black-winged kite algorithm for sustainable 5G/6G sensor networks || https://doi.org/10.1016/J.IOT.2025.101792
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Resource Allocation for Double IRSs Assisted Wireless Powered NOMA Networks || https://doi.org/10.1109/LWC.2023.3244997
|}

XTREME

2026-09-01T14:52:38Z

CollectiveIntelligenceAdmin:

=== XTREME Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101136006 || 01/01/2024 || 31/12/2026 || IT-UNIVERSITETET I KOBENHAVN / Denmark
|}
=== Project description ===
Engaging with art and music has a positive effect on health, but limitations such as venue location, personal constraints, scheduling conflicts, and costs often hinder access to these experiences. With this in mind, the EU-funded XTREME project aims to develop a human-centred mixed reality (MR) solution that transports concerts and performances to remote locations, removing physical constraints. This MR technology integrates real and virtual content, where users can share the experience virtually with selected social circles, promoting inclusivity. Eliminating travel requirements, XTREME provides a greener alternative. This groundbreaking project provides virtual access to immersive art and music experiences breaking down traditional barriers.

=== Project outputs ===
==== Publications ====
Domain Type of output Title DOI URL
AI, Machine Learning & Data Science Conference proceedings "AI enhances our performance, I have no doubt this one will do the same: The Placebo effect is robust to negative descriptions of AI" https://doi.org/10.1145/3613904.3642633
Audio, Speech & NLP Peer reviewed articles Into the Here and Now: Explorations within a New Acoustic Virtual Reality https://doi.org/10.1162/LEON_A_02651
Audio, Speech & NLP Peer reviewed articles Interfacing with history: curating with audio augmented objects https://doi.org/10.1080/09647775.2024.2431899
Computer Vision, 3D Modeling & Rendering Conference proceedings Utilizing Uncertainty in 2D Pose Detectors for Probabilistic 3D Human Mesh Recovery https://doi.org/10.1109/WACV61041.2025.00571
Computer Vision, 3D Modeling & Rendering Peer reviewed articles Attribute-Centric Compositional Text-to-Image Generation https://doi.org/10.1007/S11263-025-02371-0
Computer Vision, 3D Modeling & Rendering Peer reviewed articles Scale-wise Bidirectional Alignment Network for referring remote sensing image segmentation https://doi.org/10.1016/J.ISPRSJPRS.2025.05.014
Extended Reality (VR/AR/MR) & HCI Conference proceedings Navigating the Virtual Gaze: Social Anxiety's Role in VR Proxemics https://doi.org/10.1145/3613904.3642359
Extended Reality (VR/AR/MR) & HCI Peer reviewed articles Don't They Really Hear Us? A Design Space for Private Conversations in Social Virtual Reality https://doi.org/10.1109/TVCG.2025.3549844
Robotics, Manufacturing & Industry 4.0 Conference proceedings Multi-Flow: Multi-View-Enriched Normalizing Flows for Industrial Anomaly Detection https://doi.org/10.48550/ARXIV.2504.03306

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Multi-Flow: Multi-View-Enriched Normalizing Flows || AI Model || https://doi.org/10.48550/ARXIV.2504.03306 || Advanced deep learning framework created for industrial anomaly detection.
|}

XReco

2026-09-01T14:52:31Z

CollectiveIntelligenceAdmin:

=== XReco Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101070250 || 01/09/2022 || 31/08/2025 || DEUTSCHE WELLE / Germany
|}
=== Project description ===
While media organisations increasingly support non-linear experiences for the consumer, those are still limited to single channels and media domains. Although several media organisations have recently succeeded in breaking data silos, data sharing is mostly limited to the organisation. Thus, there are challenges for producing content feeding multiple channels with different granularities and structures, mainly related to data discovery, management and (re-)use. XRECO will create a new data-driven ecosystem for the media industry, focusing on facilitating data sharing, search and discovery and supporting creation of news and entertainment content, in particular, the creation and (re-)use of location-related 2D and 3D assets and the creation of XR experiences. The ecosystem core, represented by a Neural Media Repository (NMR), will foster inter-organisation content sharing and provide increased access to content for media creators, considering novel data monetization and rights management policies. A set of AI-based media transformation services are built around the NMR to produce novel media- and XR experiences, including 3D neural reconstructions, neural based device localisation, image stitching, de-/re-lighting and holoportation. The developed technology will be validated in use case scenarios for (i) the news media for XR-based broadcasting and automatic and customized multitarget news publishing, and for (ii) location-based information and entertainment content, with applications in tourism and the automotive industry.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || Efficient Few-Shot Incremental Training for Landmark Recognition || https://doi.org/10.1145/3672406.3672414
|-
| Computer Vision, 3D Modeling & Rendering || Book chapters || Image Valuation in NeRF-Based 3D Reconstruction || https://doi.org/10.1007/978-3-032-04968-1_32
|-
| Computer Vision, 3D Modeling & Rendering || Book chapters || Complete Convolutional Neural Networks Environment for Computer Vision Problems With Nvidia Drive AGX Xavier || https://doi.org/10.1007/978-3-031-70248-8_7
|-
| Computer Vision, 3D Modeling & Rendering || Book chapters || Synthetic Football Sprite Animations Learned Across the Pitch || https://doi.org/10.1007/978-3-031-41774-0_48
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Descriptor Impact on Multimodal 3D Retrieval || https://doi.org/10.5281/ZENODO.11942398
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || A Dataset and Metric for Textual Video Content Description || https://doi.org/10.1145/3746027.3758224
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Urban Scene Removal and Completion || https://doi.org/10.3233/FAIA250603
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Analysis of Objective 3D Mesh Quality Metrics for Cultural Heritage || https://doi.org/10.1109/QOMEX65720.2025.11219903
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Untethered Real-Time Immersive Free Viewpoint Video || https://doi.org/10.1145/3652212.3652214
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Multimodal Understanding: Investigating the Capabilities of Large Multimodal Models for Object Detection in XR Applications || https://doi.org/10.1145/3688866.3689126
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Volumetric Video Reconstruction and Communications: Toward a New Era of Interactive and Immersive Social Virtual Reality (VR) Experiences || https://doi.org/10.1145/3672406.3672421
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Semi -Automated Digital Human Production for Enhanced Media Broadcasting || https://doi.org/10.1109/GEM61861.2024.10585601
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Multimedia Information Retrieval in XR || https://doi.org/10.1145/3664647.3689176
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || 3DMSE: An Interactive 3D Media Search Engine || https://doi.org/10.1145/3652583.3657593
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Is Real-time Deep Learning-based Monocular Depth Estimation accurate for Multi-Camera Setups? || https://doi.org/10.1109/ICCT-EUROPE63283.2025.11157669
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Analysis and Development of Deep Learning Depth Estimation Techniques for Volumetric Capture and Free Viewpoint Video || https://doi.org/10.1145/3625468.3652913
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Real-Time Free Viewpoint Video for Immersive Videoconferencing || https://doi.org/10.1109/QOMEX61742.2024.10598259
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Multimodality in Media Retrieval || https://doi.org/10.1145/3652583.3657583
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Exploring Image Search on Quantum Computing Systems || https://doi.org/10.5220/0013562200004525
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Towards a Universal Query Representation for Multimodal Information Retreival || https://doi.org/10.1145/3746027.3758155
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Multimedia Retrieval in and for XR || https://doi.org/10.1145/3652583.3658421
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Enabling Domain Experts to Train Efficient Few-Shot Incremental Landmark Recognition || https://doi.org/10.1109/CBMI62980.2024.10859238
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || XReco Platform and RAI News Media Demonstrator || https://doi.org/10.1145/3746027.3761840
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Open-Source Multimedia Retrieval with vitrivr-engine || https://doi.org/10.1145/3746027.3756874
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Ubervvald: Advanced Object Detection Library for Optimizing Complex Convolutional Neural Networks (CNNs) || https://doi.org/10.1007/978-981-96-5887-9_14
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Nostrils and Mouth Detection for Drivers Using Convolutional Neural Networks with Automatically Generated Ground Truth Data || https://doi.org/10.1109/CSCI58124.2022.00265
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Ground Truth Data Generator in Automotive Infrared Sensor Vision Problems Using a Minimum Set of Operations || https://doi.org/10.1109/SYNASC61333.2023.00039
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || A new Retrieval Engine for vitrivr || https://doi.org/10.1007/978-3-031-53302-0_28
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Improving Query and Assessment Quality in Text-Based Video Retrieval Evaluation || https://doi.org/10.1145/3591106.3592281
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Real-Time Layered View Synthesis for Free-Viewpoint Video from Unreliable Depth Information || https://doi.org/10.1145/3592834.3592881
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Free-form Multi-Modal Multimedia Retrieval (4MR) || https://doi.org/10.1007/978-3-031-27077-2_58
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Multimedia Retrieval in Mixed Reality: Leveraging Live Queries for Immersive Experiences || https://doi.org/10.1109/AIxVR59861.2024.00048
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Mining Landmark Images for Scene Reconstruction from Weakly Annotated Video Collections || https://doi.org/10.1007/978-3-031-53302-0_12
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Synthetic Football Sprite Animations Learned Across the Pitch. || https://doi.org/10.1007/978-3-031-41774-0_48
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Subjective Evaluation of Dynamic Point Clouds: Impact of Compression and Exploration Behavior || https://doi.org/10.23919/EUSIPCO58844.2023.10290086
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Multimodal 3D Object Retrieval || https://doi.org/10.5281/zenodo.10226588
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Interactive Multimodal Video Search: An Extended Post-Evaluation for the VBS 2022 Competition || https://doi.org/10.1007/s13735-024-00325-9
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Multimedia Systems || https://doi.org/10.5167/uzh-236035
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || An Assessment of the Stereo and Near-Infrared Camera Calibration Technique Using a Novel Real-Time Approach in the Context of Resource Efficiency || https://doi.org/10.3390/PR13041198
|-
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Data as Remuneration in Digital Copyright Licensing: Some Reflections on the Concept of ‘Appropriate and Proportionate Remuneration’ Under Art. 18 EU Directive 2019/790 in the Data Era || https://doi.org/10.5281/ZENODO.18482948
|-
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Secure, Dynamic and Uncomplicated Licensing of Movies on a Blockchain Infrastructure || https://doi.org/10.1109/ICOIN56518.2023.10049017
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || IEEE Access || https://doi.org/10.5167/UZH-261490
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Delay Threshold for Social Interaction in Volumetric eXtended Reality Communication || https://doi.org/10.1145/3651164
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || VERGE in CBMI2024 || https://doi.org/10.5281/ZENODO.10652893
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || VERGE in VBS 2024 || https://doi.org/10.5281/zenodo.10652893
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| XR and Media Transformation APIs and Authoring Tools || APIs / Tools || https://xreco.eu/deliverables/#toc_D41_XR_and_Media_Transformation_Services_API_and || APIs integrating vertical technologies for XR media transformation and content creation.
|-
| Textual Video Content Dataset || Dataset / Metric || https://doi.org/10.1145/3746027.3758224 || A dataset and corresponding metric created specifically for textual video content description.
|-
| vitrivr-engine || Open-Source Engine || https://doi.org/10.1145/3746027.3756874 || An open-source multimedia retrieval engine for content and similarity searches.
|}

XR5.0

2026-09-01T14:52:23Z

CollectiveIntelligenceAdmin:

=== XR5.0 Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135209 || 01/01/2024 || 31/12/2026 || GFT ITALIA SRL / Milano, Italy
|}
=== Project description ===
XR5.0 will build, demonstrate, and validate a novel Person-Centric and AI-based XR paradigm that will be tailored to the requirements and nature of I5.0 applications. In this direction, the project will specify structuring principles and blueprints for using XR in I5.0 applications with emphasis on the development of innovative “XR-made-in-Europe” technology that blends with human-centric manufacturing technologies and adheres to European values. The XR5.0 applications will consider the characteristics and context of the worker based on the integration of human-centred digital twins (DTs) that comprise the “digital image” of the worker. At the same time, XR5.0 will design and implement a unique blending of XR technology and advanced AI paradigms, including AI technologies that foster the interplay between humans and AI such as explainable AI (XAI), Active Learning (AL), Generative AI (GenAI), and neurosymbolic learning. The XR5.0 technologies will be coupled with a cloud-based XR training platform for Operator 5.0 applications, which will enable ergonomic and personalized training of industrial workers on popular processes. The XR5.0 paradigm will empower the development of six (6) novel high-TRL pilot applications spanning the areas of AI-based product design, remote and intelligent maintenance of assets, workers’ training, support in product assembly, as well as guidance and instructions for troubleshooting. These applications will be demonstrated in realistic manufacturing environments. Moreover, they will be integrated to the EU XR platform to be developed as part of the call. Most importantly, XR5.0 will build a vibrant community of interested stakeholders around the project’s outcomes. This community will provide a basis for the sustainability and wider uptake of the project’s results towards maximising the impact of the project’s use cases. In this direction, all XR5.0 technologies will be high TRL>=7-8 and ready for immediate commercialisation.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || A Scalable Data-Driven Methodology for Human Intention Prediction in Diverse Collaborative Scenarios. || https://doi.org/10.5281/ZENODO.15720280
|-
| AI, Machine Learning & Data Science || Conference proceedings || A Protocol for Human-Centric Adaptive User Interfaces: From Static Interaction to Behaviour-Driven Adaptation. || https://doi.org/10.5281/ZENODO.15720235
|-
| AI, Machine Learning & Data Science || Conference proceedings || Bridging Industrial Expertise and XR with LLM-Powered Conversational Agents || https://doi.org/10.48550/ARXIV.2504.05527
|-
| AI, Machine Learning & Data Science || Conference proceedings || Integrating Asset Administration Shell with an IIoT Platform for Human-centric Digital Twins || https://doi.org/10.5281/ZENODO.16283191
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Bias in Machine Learning: A Literature Review || https://doi.org/10.3390/APP14198860
|-
| Ethics, Society, Arts & Culture || Conference proceedings || UI/UX Sustainable Design: Best Practices for Applications CO2 Emissions Reduction || https://doi.org/10.23919/SPLITECH61897.2024.10612495
|-
| Robotics, Manufacturing & Industry 4.0 || Book chapters || Improving Collaborative Robotics: Insights on the Impact of Human Intention Prediction || https://doi.org/10.1007/978-3-031-81688-8_1
|-
| Robotics, Manufacturing & Industry 4.0 || Book chapters || Impact of Collaborative Robots on Human Trust, Anxiety, and Workload: Experiment Findings || https://doi.org/10.1007/978-3-031-65894-5_28STYLE
|-
| Robotics, Manufacturing & Industry 4.0 || Conference proceedings || XR5.0: Human-Centric AI-Enabled Extended Reality Applications for Industry 5.0 || https://doi.org/10.23919/FRUCT64283.2024.10749931
|}

XR4Human

2026-09-01T14:52:16Z

CollectiveIntelligenceAdmin:

=== XR4Human Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101070155 || 01/11/2022 || 31/10/2025 || UNIVERSITETET I SOROST-NORGE / Norway
|}
=== Project description ===
Extended reality (XR) is defined as technology that can merge the physical and virtual worlds. It covers virtual reality, augmented reality and mixed reality. As with any technology, XR faces certain challenges, particularly regarding privacy, security, ethics and associated safety, amongst others. The EU-funded XR4Human project aims to establish living guidelines on ethical and related policy, regulatory, governance and interoperability issues of XR technologies within a European community of practice. Project work will pave the way towards a strong and competitive ecosystem led by European companies for the wider deployment, adoption and acceptance of XR technologies.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Ethics, Society, Arts & Culture || Book chapters || The moral programming of XR, and what we can learn from the AI experience || https://doi.org/10.3920/9789004730779_006
|-
| Ethics, Society, Arts & Culture || Other || Article on mapping of challenges and presentation of ethical, legal, regulatory, and technical interoperability solutions || https://doi.org/10.5281/ZENODO.16793259
|-
| Ethics, Society, Arts & Culture || Other || D2.2.Mapping of risks and harms of eXtended reality (XR) technologies || https://doi.org/10.5281/ZENODO.14044988
|-
| Ethics, Society, Arts & Culture || Other || Regulatory gap analysis || https://doi.org/10.5281/ZENODO.14045412
|-
| Ethics, Society, Arts & Culture || Other || D4.2: Report on the Interoperability Guide || https://doi.org/10.5281/ZENODO.14046081
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || From principles to practice: A code of conduct for the human-centered and ethical development of immersive technologies || https://doi.org/10.12688/OPENRESEUROPE.22230.1
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || A scoping review of the ethics frameworks describing issues related to the use of extended reality || https://doi.org/10.12688/openreseurope.17283.1
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || XR4Human: The Equitable, Inclusive, and Human-Centered XR Project || https://doi.org/10.32040/2242-122X.2024.T432
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Online Rating Repository || Repository || https://doi.org/10.5281/ZENODO.17896488 || Digital repository functioning as a rating and evaluation tool for human-centered XR frameworks.
|}

XR4ED

2026-09-01T14:52:08Z

CollectiveIntelligenceAdmin:

=== XR4ED Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101093159 || 01/01/2023 || 31/12/2025 || CYENS CENTRE OF EXCELLENCE / Cyprus
|}
=== Project description ===
The pandemic forced many changes in education at every level. Lockdowns designed to curb the spread of coronavirus accelerated the adoption of digital technology. This was a boost for Europe’s EdTech sector, which continues to grow. The EU-funded XR4ED project will explore the use of the extended reality (XR) industry, which has evolved and maintained a leading role globally in software and content production. Specifically, it will investigate learning resources and advantages of learning using XR. The project will also set up a one-stop-shop and open marketplace for XR applications for learning, training and education. The findings will enable digital start-ups, SMEs, and industry active in the EdTech sector to further advance early prototypes, of digital learning solutions/apps using XR.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Education, Training & Serious Games || Conference proceedings || The Reel Deal: Designing and Evaluating LLM-Generated Short-Form Educational Videos || https://doi.org/10.1145/3749012.3749048
|-
| Education, Training & Serious Games || Conference proceedings || Perceptions and Challenges of Implementing XR Technologies in Education: A Survey-Based Study || https://doi.org/10.1007/978-3-031-56075-0_28
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || Ethical Considerations of Extended Reality in the Workplace || https://doi.org/10.1109/MPRV.2025.3602230
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || VR as a “Drop-In” Well-Being Tool for Knowledge Workers || https://doi.org/10.1109/ISMAR67309.2025.00127
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Increasing Meditation Efficiency with Virtual Reality || https://doi.org/10.1145/3613905.3651003
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Stretch your reach: Studying Self-Avatar and Controller Misalignment in Virtual Reality Interaction || https://doi.org/10.1145/3613904.364226
|}

XR2Learn

2026-09-01T14:52:01Z

CollectiveIntelligenceAdmin:

=== XR2Learn Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101092851 || 01/01/2023 || 30/06/2026 || CONSORZIO NAZIONALE INTERUNIVERSITARIO PER LE TELECOMUNICAZIONI / Parma, Italy
|}
=== Project description ===
Virtual, augmented or mixed reality (VR/AR/MR) – in general extended reality (XR) – provides numerous benefits in education. XR increases the knowledge area, offers active experience rather than just passive information, helps to understand complex concepts, subjects or theories, prevents distractions during the study, boosts creativity and expands learners’ efficiency in gaining knowledge. By leveraging the European XR industry technologies to empower immersive learning and training, the EU-funded XR2Learn project will bring together XR technology providers, application designers and developers, education experts, end-users and decision makers to collaborate and pair interests with a focus on technical training, upskilling and reskilling in advanced manufacturing. The project will provide equity-free funding through an FSTP mechanism to support innovation activities, piloting and user testing, and promote the reuse and sharing of learning materials/XR applications.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Audio, Speech & NLP || Conference proceedings || Exploring Self-Supervised Multi-view Contrastive Learning for Speech Emotion Recognition with Limited Annotations || https://doi.org/10.21437/INTERSPEECH.2024-860
|-
| Education, Training & Serious Games || Conference proceedings || INTERACT: An authoring tool that facilitates the creation of human centric interaction with 3d objects in virtual reality || https://doi.org/10.1145/3565066.3608250
|-
| Education, Training & Serious Games || Conference proceedings || The V-Lab VR Educational Application Framework: A Beacon Application of the XR2Learn Project || https://doi.org/10.1145/3565066.3608246
|-
| Healthcare, Medicine & Accessibility || Conference proceedings || The Magic XRoom: A Flexible VR Platform for Controlled Emotion Elicitation and Recognition || https://doi.org/10.1145/3565066.3608247
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || XR-Driven Robotic System Training for Occupational Health, Safety, and Maintenance || https://doi.org/10.1109/ACCESS.2025.3556699
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Smart Detection System of Safety Hazards in Industry 5.0 || https://doi.org/10.3390/telecom5010001
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| V-Lab || Application Framework || https://doi.org/10.1145/3565066.3608246 || A VR educational application framework acting as a beacon application for immersive learning.
|-
| INTERACT || Authoring Tool || https://doi.org/10.1145/3565066.3608250 || An authoring tool facilitating the creation of human-centric interaction with 3D objects in VR.
|-
| XR2Learn platform || Online tool || https://xr2learn.eu/platform/ || The software code structure of the XR marketplace, including the on-demand components and IPR tools.
|}

XR2Industry

2026-09-01T14:51:46Z

CollectiveIntelligenceAdmin:

=== XR2Industry Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135547 || 01/12/2023 || 30/11/2026 || UNIVERSITAT POLITECNICA DE VALENCIA / Spain
|}
=== Project description ===
In a tech landscape echoing Johannes Gutenberg’s transformative impact on printing (with the movable-type printing press around 1440), the EU-funded XR2Industry project emerges as the extended reality (XR) pioneer. Focused on data privacy, empowerment and industrial relevance, XR2Industry envisions an open platform. Lynx, the hardware platform carrier, unites key researchers and legal experts, ensuring GDPR compliance. The collaboration extends to content developers, virtual reality/XR solutions experts and end users. Overall, the project strives for a holistic approach, embracing the entire XR value chain. As it unites nine partners, supports 12 third parties and spans Europe, XR2Industry anticipates a substantial economic impact, ushering in the XR industrial era.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Type of output !! Title !! DOI URL
|-
| Other || Passerelle platform documentation || https://doi.org/10.5281/ZENODO.15672606
|-
| Conference proceedings || XR2INDUSTRY: Transforming European Industry with Extended Reality || https://doi.org/10.5281/zenodo.15173670
|}

WATERLINE

2026-09-01T14:51:40Z

CollectiveIntelligenceAdmin:

=== WATERLINE Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101071306 || 01/10/2022 || 30/09/2025 || MALTA COLLEGE OF ARTS SCIENCE AND TECHNOLOGY
|}
=== Project description ===
Capacity building to strengthen networks of higher education institutions and their cooperation with surrounding ecosystems is one of the goals of the EU. In this context, the EU-funded WATERLINE project aims to create a European Digital Water Higher Education Institution Alliance based on the quadruple helix model of innovation, which recognises four major actors in the innovation system: science, policy, industry and society. This approach will lead to the development of the Alliance's research, educational and entrepreneurship capacities. To achieve its goals, the project will co-create a common governance framework and a portfolio of water components that will support in the setting up of emulative centres through assisted and virtual reality, amongst other actions.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Towards a smart city: a smart dam initiative in Nis (WATERLINE Project related publication, RP2) || https://doi.org/10.62683/SINARG2025.105
|-
| Earth Observation, Environment & Smart Cities || Peer reviewed articles || Stakeholder analysis in the application of cutting-edge digital visualisation technologies for urban flood risk management: A critical review (WATERLINE project related publication, RP1) || https://doi.org/10.1016/j.eswa.2023.121426
|-
| Education, Training & Serious Games || Conference proceedings || Introducing the digital water in higher education (WATERLINE Project related publication, RP2) || https://doi.org/10.5281/ZENODO.17152914
|-
| Education, Training & Serious Games || Conference proceedings || Virtual reality in water education: Losses in pipes case study (WATERLINE Project related publication, RP2) || https://doi.org/10.5281/ZENODO.17152973
|-
| Education, Training & Serious Games || Conference proceedings || Water Hammer VR: Immersive Learning Environment for Hydraulic Transient Analysis in Water Distribution Systems (WATERLINE Project related publication, RP2) || https://doi.org/10.5281/ZENODO.17517277
|}

VERGE

2026-09-01T14:51:32Z

CollectiveIntelligenceAdmin:

=== VERGE Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101096034 || 01/01/2023 || 30/06/2025 || UNIVERSITAT POLITECNICA DE CATALUNYA / Spain
|}
=== Project description ===
Edge computing involves an ecosystem of highly heterogeneous computing elements, which may be located practically everywhere across the path between the end-devices, the access network and the central cloud. In this context, the EU-funded VERGE project will design a flexible, modular and converged edge platform to support distributed AI at the edge. Focusing on security, privacy and trustworthiness, VERGE will carry out two use cases. The first will cover mixed reality driven edge-enabled industrial Beyond 5G applications in Turkey. The second will study edge-assisted autonomous tram operations in Italy. Results will be disseminated to academia, industry and the wider stakeholder community.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || On the Deployment of an AI-driven Power Control Mechanism for D-MIMO in Beyond 5G Scenarios || https://doi.org/10.1109/CSCN63874.2024.10849691
|-
| AI, Machine Learning & Data Science || Conference proceedings || A Flexible, Efficient and Robust Method for AI-driven Power Control in D-MIMO || https://doi.org/10.1109/MeditCom58224.2023.10266651
|-
| AI, Machine Learning & Data Science || Other || AI/ML as a Key Enabler of 6G Networks: Methodology, Approach and AI-Mechanisms in SNS JU || https://doi.org/10.5281/ZENODO.14623106
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || A Transfer Reinforcement Learning Approach for Capacity Sharing in Beyond 5G Networks || https://doi.org/10.3390/FI16120434
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Space and time user distribution measurements dataset in a university campus || https://doi.org/10.1016/J.COMNET.2024.110329
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Adaptive Federated Pruning in Hierarchical Wireless Networks || https://doi.org/10.1109/TWC.2023.3329450
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Forecasting Trends in Cloud-Edge Computing: Unleashing the Power of Attention Mechanisms || https://doi.org/10.1109/MCOM.001.2300583
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || AERO: Adaptive Edge-Cloud Orchestration With a Sub-1K-Parameter Forecasting Model || https://doi.org/10.1109/TMLCN.2025.3553100
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Knowledge Transfer for Collaborative Misbehavior Detection in Untrusted Vehicular Environments || https://doi.org/10.1109/TVT.2024.3461837
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Attention-Driven AI Model Generalization for Workload Forecasting in the Compute Continuum || https://doi.org/10.1109/TMLCN.2025.3584009
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Enhancing Open RAN Operations: The Role of Probabilistic Forecasting in Network Analysis || https://doi.org/10.1109/TNSM.2025.3565268
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Federated Learning and Meta-Learning: Approaches, Applications, and Directions || https://doi.org/10.1109/COMST.2023.3330910
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || TENET: a new hybrid network architecture for adversarial defense || https://doi.org/10.1007/s10207-023-00675-1
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Goal-Oriented Semantic Communications for Avatar-Centric Augmented Reality || https://doi.org/10.1109/TCOMM.2024.3420708
|-
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Threat Modeling of AI-as-a-Service Framework || https://doi.org/10.1109/WIMOB61911.2024.10770432
|-
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Deep Reinforcement Learning-Based Adversarial Defense in Vehicular Communication Systems || https://doi.org/10.1109/ICC51166.2024.10622762
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Task-oriented and Semantics-aware Communications for Augmented Reality || https://doi.org/10.1109/GLOBECOM54140.2023.10437075
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Enhancing Cloud-Native Resource Allocation with Probabilistic Forecasting Techniques in O-RAN || https://doi.org/10.1109/EUCNC/6GSUMMIT60053.2024.10597068
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Asynchronous Federated Learning via Over-the-Air Computation || https://doi.org/10.1109/GLOBECOM54140.2023.10437951
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Emergent Communication Protocol Learning for Task Offloading in Industrial Internet of Things || https://doi.org/10.1109/GLOBECOM54140.2023.10437954
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Optimization of Distinct Time-Series Neural Architectures for Cloud-Edge Workload Prediction || https://doi.org/10.1109/ICMLCN64995.2025.11140432
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Federated Learning Games for Reconfigurable Intelligent Surfaces via Causal Representations || https://doi.org/10.1109/GLOBECOM54140.2023.10437657
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Edge4AI: Enabling intelligent edge automation and AI lifecycle management for Beyond 5G networks || https://doi.org/10.5281/ZENODO.15878533
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Deep Neural Network Model for Dynamic Functional Split Management in Beyond 5G || https://doi.org/10.1109/ICMLCN64995.2025.11140468
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Joint UPF and Application Placement in Multi-Slice Edge Networks: A Reinforcement Learning Strategy || https://doi.org/10.1109/WCNC61545.2025.10978828
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Digital Twin as a Service for 6G Radio Access Networks: Functional Model and Key Challenges || https://doi.org/10.1109/ICT65093.2025.11046305
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Advancing Orchestration: Leveraging Distance Functions to Meet Application Intents || https://doi.org/10.1109/UCC63386.2024.00020
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || 5G/6G Technology Capabilities Designed for Secure Edge Network: Smart City Use Cases of Turkcell || https://doi.org/10.1109/BCCA62388.2024.10844409
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Advanced Edge Computing Architecture for AI-Driven Automation and Slicing in Beyond 5G || https://doi.org/10.1109/UCC63386.2024.00052
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Joint Model Pruning and Resource Allocation for Wireless Time-triggered Federated Learning || https://doi.org/10.1109/GLOBECOM52923.2024.10901166
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Low Layer Functional Split Management in 5G and Beyond: Architecture and Self-adaptation || https://doi.org/10.1109/ISWCS61526.2024.10639176
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Towards Trustworthy Reinforcement Learning-based Resource Management in Beyond 5G || https://doi.org/10.1109/EuCNC/6GSummit60053.2024.10597001
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || On the Impact of PRB Load Uncertainty Forecasting for Sustainable Open RAN || https://doi.org/10.1109/PIMRC59610.2024.10817286
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Resource Optimization for Tail-Based Control in Wireless Networked Control Systems || https://doi.org/10.1109/PIMRC59610.2024.10817284
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Micro-Orchestration of RAN Functions Accelerated in FPGA SoC Devices || https://doi.org/10.1109/6GNET63182.2024.10765691
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || ReLVaaS: Verification-as-a-Service to Analyze Trustworthiness of RL-based Solutions in 6G Networks || https://doi.org/10.1109/COMSNETS63942.2025.10885660
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || An Evolutionary Edge Computing Architecture for Beyond 5G Era || https://doi.org/10.1109/CAMAD59638.2023.10478426
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || AI-Powered Edge Computing Evolution for Beyond 5G Communication Networks || https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188371
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Sample-Efficient Blockage Prediction and Handover Using Causal Reinforcement Learning || https://doi.org/10.1109/CONECCT62155.2024.10677092
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || XAI-driven Model Design for Resource Utilization Forecasting in Cloud-native 6G Networks || https://doi.org/10.1109/MeditCom61057.2024.10621360
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Causal Policy Gradient for End-to-End Communication Systems || https://doi.org/10.1109/COMSNETS59351.2024.10426936
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || The Use Case of Beyond-5G and Edge Computing for XR-driven Collaborative Design || https://doi.org/10.5281/ZENODO.14712404
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Expanding Edge Computing deeper into Beyond 5G Radio Access Networks || https://doi.org/10.1109/NetSoft57336.2023.10175479
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Wireless Time-Triggered Federated Learning with Adaptive Local Training Optimization || https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10226087
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || On the use of Probabilistic Forecasting for Network Analysis in Open RAN || https://doi.org/10.1109/MeditCom58224.2023.10266607
|-
| Networks, Cloud & Telecommunications (5G/6G) || Other || European Vision for the 6G Network Ecosystem || https://doi.org/10.5281/ZENODO.14230482
|-
| Networks, Cloud & Telecommunications (5G/6G) || Other || Network & Service Management Advancements - Key frameworks and Interfaces towards open, Intelligent and reliable 6G networks || https://doi.org/10.5281/ZENODO.15011613
|-
| Networks, Cloud & Telecommunications (5G/6G) || Other || Sustainability in SNS JU Projects - Targets, Methodologies, Trade-offs and Implementation Considerations Towards 6G Systems || https://doi.org/10.5281/ZENODO.15555292
|-
| Networks, Cloud & Telecommunications (5G/6G) || Other || Emerging 5G and Beyond Ecosystem Business Models || https://doi.org/10.5281/ZENODO.14756404
|-
| Networks, Cloud & Telecommunications (5G/6G) || Other || Towards 6G Architecture: Key Concepts, Challenges, and Building Blocks || https://doi.org/10.5281/ZENODO.15001377
|-
| Networks, Cloud & Telecommunications (5G/6G) || Other || Network & Service Management Advancements - Key frameworks and Interfaces towards open, Intelligent and reliable 6G networks || https://doi.org/10.5281/ZENODO.14234898
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Relay-empowered beyond 5G radio access networks with edge computing capabilities || https://doi.org/10.1016/J.COMNET.2024.110287
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || On Exploiting User Equipment Relaying Capabilities in Beyond 5G Networks: Opportunities, Challenges, and Road Map || https://doi.org/10.1109/MVT.2024.3477848
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Agile FPGA Computing at the 5G Edge: Joint Management of Accelerated and Software Functions for Open Radio Access Technologies || https://doi.org/10.3390/electronics13040701
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || An Edge-Enabled Wireless Split Learning Testbed: Design and Implementation || https://doi.org/10.1109/LCOMM.2024.3390843
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Security of AI-Driven Beam Selection for Distributed MIMO in an Adversarial Setting || https://doi.org/10.1109/ACCESS.2024.3378263
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || A New Methodology for User Equipment Trajectory Prediction in Cellular Networks || https://doi.org/10.1109/TVT.2024.3388554
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Deep Learning-based Algorithm for Optimizing Relay User Equipment Activation in 5G Cellular Networks || https://doi.org/10.1109/TVT.2023.3328057
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || On the Design of a Network Digital Twin for the Radio Access Network in 5G and Beyond || https://doi.org/10.3390/s23031197
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || A Tutorial on the Characterisation and Modelling of Low Layer Functional Splits for Flexible Radio Access Networks in 5G and Beyond || https://doi.org/10.1109/COMST.2023.3296821
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Space and Time User Distribution in a University Campus || Dataset || https://doi.org/10.1016/J.COMNET.2024.110329 || Measurement dataset containing spatiotemporal distributions of users.
|-
| Edge4AI || Software Framework || https://doi.org/10.5281/ZENODO.15878533 || A framework enabling intelligent edge automation and AI lifecycle management for Beyond 5G networks.
|}

TrustChain

2026-09-01T14:51:25Z

CollectiveIntelligenceAdmin:

=== TrustChain Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101093274 || 01/01/2023 || 31/12/2025 || EUROPEAN DYNAMICS LUXEMBOURG SA
|}
=== Project description ===
Wireless communication systems have made rapid progress over the years. With the 5G mobile network rolling out worldwide as the new standard for broadband cellular networks, Beyond 5G and the next generation 6G networking technologies are promising to break new ground in terms of digital technologies reach throughout our private and work lives. This reach and the vast amounts of data collected from people, operations and more create a critical need for safety, privacy and fair use of data. The EU-funded TrustChain project aims to help build a future where the internet is based on the highest levels of ethics, standards and rights established by the United Nations. The project will collaborate with internet innovators to develop solutions to challenges regarding issues of security, trust, efficiency and privacy that plague current data ecosystems and the internet.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || SURE: A New Privacy and Utility Assessment Library for Synthetic Data || https://doi.org/10.5281/ZENODO.13843053
|-
| AI, Machine Learning & Data Science || Conference proceedings || User-Empowered Federated Learning in the Automotive Domain || https://doi.org/10.1109/BLOCKCHAIN62396.2024.00098
|-
| Cybersecurity, Privacy & Blockchain || Conference proceedings || A Systematisation of Knowledge: Connecting European Digital Identities with Web3. || https://doi.org/10.1109/BLOCKCHAIN62396.2024.00089
|-
| Cybersecurity, Privacy & Blockchain || Conference proceedings || A blockchain identity privacy management framework for a healthcare application || https://doi.org/10.1109/BLOCKCHAIN62396.2024.00088
|-
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Towards a Blockchain-Enabled Trustworthy Market Framework || https://doi.org/10.5281/ZENODO.13618925
|-
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Efficient and Budget-Balanced Decentralized Management of Federated Cloud and Edge Providers || https://doi.org/10.5281/ZENODO.10785252
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Decentralized Management of Federated Cloud and Edge Providers || Software Framework || https://doi.org/10.5281/ZENODO.10785252 || A management framework for the efficient and budget-balanced handling of federated cloud and edge platforms.
|-
| SURE: Privacy and Utility Assessment Library || Software Library || https://doi.org/10.5281/ZENODO.13843053 || A new library designed to assess privacy and utility for synthetic data.
|}

TransMIXR

2026-09-01T14:51:17Z

CollectiveIntelligenceAdmin:

=== TransMIXR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101070109 || 01/10/2022 || 30/09/2025 || Technological University of the Shannon: Midlands Midwest
|}
=== Project description ===
The advancement of extended reality (XR) and artificial intelligence (AI) has given the European creative and cultural sector (CCS) the opportunity to revolutionise digital co-creation, interaction and engagement. The EU-funded TRANSMIXR project will develop human-centred tools for collaborative co-creation and consumption of multi-modal immersive media through social XR. Using the Living Labs methodology, the project will bring together the necessary interdisciplinary skills and domain expertise to design and develop such human-centric tools and immersive media experiences. TRANSMIXR will pilot the technology in news media and broadcasting, performing arts and cultural heritage. It will also establish collaborations to demonstrate the transferability of these experiences to new domains outside the news media, arts and cultural sectors.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || Enhancing User Control in AI-Based Video Summarization for Social Media || https://doi.org/10.1007/978-981-96-2074-6_12
|-
| AI, Machine Learning & Data Science || Conference proceedings || An Experimental Study on Generating Plausible Textual Explanations for Video Summarization || https://doi.org/10.5281/ZENODO.17650009
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || ACM Transactions on Multimedia Computing, Communications and Applications || https://doi.org/10.5281/ZENODO.13343545
|-
| Audio, Speech & NLP || Conference proceedings || A Comparison of Gender Differences and Performance Metrics in a VR-Based Auditory || https://doi.org/10.5281/ZENODO.13347685
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Gaussian Splatting vs. Classical Photogrammetry: A Comparison for Virtual Backdrops || https://doi.org/10.1109/QOMEX65720.2025.11219987
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Enhancing Immersive Experiences through 3D Point Cloud Analysis: A Novel Framework for Applying 2D Visual Saliency Models to 3D Point Clouds || https://doi.org/10.1109/QOMEX61742.2024.10598254
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Exploiting LMM-based knowledge for image classification tasks || https://doi.org/10.48550/ARXIV.2406.03071
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || TSalV360: A Method and Dataset for Text-driven Saliency Detection in 360-Degrees Videos || https://doi.org/10.5281/ZENODO.17649129
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Disturbing Image Detection Using LMM-Elicited Emotion Embeddings || https://doi.org/10.48550/ARXIV.2406.12668
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Video Shot Discovery Through Text2Video Embeddings in a News Analytics Dashboard || https://doi.org/10.1109/CBMI62980.2024.10859251
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || UVG-CWI-DQPC: Dual-Quality Point Cloud Dataset for Volumetric Video Applications || https://doi.org/10.1145/3746027.3758263
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || MLLM Frame Subset Ensembling for Audio-Visual Video QA and MLLM-based Reranking for Ad-hoc Video Search in TRECVID 2025 || https://doi.org/10.5281/ZENODO.18346563
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Subjective Qality Evaluation of Point Clouds using Remote Testing || https://doi.org/10.1145/3607546.3616803
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || VidCtx: Context-aware Video Question Answering with Image Models || https://doi.org/10.5281/ZENODO.17198741
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || VERGE in VBS 2026 || https://doi.org/10.5281/ZENODO.18268841
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Online Anchor-based Training for Image Classification Tasks || https://doi.org/10.1109/ICIP51287.2024.10648148
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Auto-summarization of Human Volumetric Videos || https://doi.org/10.1145/3672406.3672416
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Visual-Saliency Guided Multi-modal Learning for No Reference Point Cloud Quality Assessment || https://doi.org/10.1145/3689093.3689183
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || An LLM Framework for Long-Form Video Retrieval and Audio-Visual Question Answering Using Qwen2/2.5 || https://doi.org/10.1109/CVPRW67362.2025.00358
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || A Human-Annotated Video Dataset for Training and Evaluation of 360-Degree Video Summarization Methods || https://doi.org/10.1145/3672406.3672417
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || LMM-Regularized CLIP Embeddings for Image Classification || https://doi.org/10.48550/ARXIV.2412.11663
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Prototype Anchoring for Image Classification Tasks || https://doi.org/10.23919/EUSIPCO63174.2024.10715272
|-
| Computer Vision, 3D Modeling & Rendering || Other || TSV360: A dataset for training and objective evaluation of text-driven 360-degrees video saliency detection methods || https://doi.org/10.5281/ZENODO.16991178
|-
| Computer Vision, 3D Modeling & Rendering || Other || Gaussian Splatting vs. Classical Photogrammetry: Input Data || https://doi.org/10.5281/ZENODO.17185795
|-
| Computer Vision, 3D Modeling & Rendering || Other || Gaussian Splatting vs. Classical Photogrammetry: 3D Models || https://doi.org/10.5281/ZENODO.17143763
|-
| Computer Vision, 3D Modeling & Rendering || Other || Feel the Music!—Audience Experiences of Audio–Tactile Feedback in a Novel Virtual Reality Volumetric Music Video || https://doi.org/10.3390/arts12040156
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || PointPCA+: A full-reference Point Cloud Quality Assessment metric with PCA-based features || https://doi.org/10.1016/J.IMAGE.2025.117262
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || PointPCA: Point Cloud Objective Quality Assessment Using PCA-Based Descriptors || https://doi.org/10.1186/S13640-024-00626-3
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Subjective and Objective Quality Assessment for Dynamic Point Cloud with Visual Attention in 6 DoF || https://doi.org/10.1145/3731759
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Delay threshold for social interaction in volumetric eXtended Reality communication || https://doi.org/10.1145/3651164
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Comparison of Visual Saliency for Dynamic Point Clouds: Task-free vs. Task-dependent || https://doi.org/10.1109/TVCG.2025.3549863
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || A QoE and Visual Attention Evaluation for 360° videos with non-spatial and spatial audio || https://doi.org/10.1145/3650208
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || UVG-CWI-DQPC: Dual-Quality Point Cloud Dataset for Volumetric Video Applications || https://doi.org/10.1145/3746027.3758263
|-
| Education, Training & Serious Games || Peer reviewed articles || The potential of extended reality in Rural Education’s future–perspectives from rural educators. Education and Information Technologies || https://doi.org/10.1007/S10639-023-12169-7
|-
| Education, Training & Serious Games || Peer reviewed articles || Utilizing virtual reality to assist social competence education and social support for children from under-represented backgrounds || https://doi.org/10.1016/J.COMPEDU.2023.104815
|-
| Ethics, Society, Arts & Culture || Conference proceedings || Social Density and its Impact on Behaviour in Virtual Environments || https://doi.org/10.1145/3746269.3760421
|-
| Ethics, Society, Arts & Culture || Conference proceedings || Ethical Considerations in the Production and Consumption of Music in the Metaverse || https://doi.org/10.1109/IS262782.2024.10704197
|-
| Ethics, Society, Arts & Culture || Conference proceedings || Finding Video Shots for Immersive Journalism Through Text-to-Video Search || https://doi.org/10.1109/CBMI62980.2024.10859220
|-
| Ethics, Society, Arts & Culture || Conference proceedings || VR Planica: Gaussian Splatting Workflows for Immersive Storytelling || https://doi.org/10.5753/IMXW.2025.8141
|-
| Ethics, Society, Arts & Culture || Conference proceedings || Exploring engagement dynamics between journalists and news consumers in Social XR || https://doi.org/10.1145/3672406.3672420
|-
| Ethics, Society, Arts & Culture || Conference proceedings || Communication Challenges between Clients and Producers of Immersive Media Applications: can Social XR help? || https://doi.org/10.1145/3639701.3656307
|-
| Ethics, Society, Arts & Culture || Other || Physiological Synchrony: A Novel Approach to Evaluating User Quality of Experience in Collaborative Distributed Virtual Reality Environments || https://doi.org/10.5281/zenodo.8224881
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || Designing and Evaluating a VR Lobby for a socially enriching remote Opera watching experience || https://doi.org/10.1109/TVCG.2024.3372081
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || Cognitive Representations and Personal Experiences of COVID-19 Using Social Virtual Reality || https://doi.org/10.1162/PRES_A_00429
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || Designing the Space Archivists: A Metadata-Driven VR Game Concept for Children to Engage with Cultural Heritage || https://doi.org/10.3390/HERITAGE8070238
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || Designing the Space Archivists: A Metadata-Driven VR Game Concept for Children to Engage with Cultural Heritage || https://doi.org/10.3390/HERITAGE8070238
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Voices Unveiled: Quality of Experience in Collaborative VR via AssemblyAI and NASA-TLX Analysis || https://doi.org/10.5281/ZENODO.13343703
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Exploring the impact of volumetric graphics on the engagement of broadcast media professionals || https://doi.org/10.21203/RS.3.RS-3994643/V1
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Voices Unveiled: Quality of Experience in Collaborative VR via AssemblyAI and NASA-TLX Analysis || https://doi.org/10.5281/ZENODO.13343703
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Exploring user feedback in VR: the added value of qualitative evaluation methods || https://doi.org/10.5753/IMXW.2025.4030
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Extending 3-DoF Metrics to Model User Behaviour Similarity in 6-DoF Immersive Applications || https://doi.org/10.1145/3587819.3590976
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || From Individual QoE to Shared Mental Models: A Novel Evaluation Paradigm for Collaborative XR || https://doi.org/10.1109/QOMEX65720.2025.11219992
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Tangible Authoring of Embedded-Object Visualizations in Mixed Reality || https://doi.org/10.1145/3678698.3687187
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Emerging Telepresence Technologies for Hybrid Meetings: Experiences and Lessons Learned from an Interactive Workshop || https://doi.org/10.1145/3712677.3720464
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || ComPEQ-MR: Compressed Point Cloud Dataset with Eye Tracking and Quality Assessment in Mixed Reality || https://doi.org/10.1145/3625468.3652182
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Correlation between Entropy and Prediction Error in VR Head Motion Trajectories || https://doi.org/10.1145/3607546.3616805
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || A Volumetric Video Application to Enhance Museum Experiences || https://doi.org/10.1145/3641825.3689695
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Open-Sourcing VR2Gather: A Collaborative Social VR System for Adaptive Multi-Party Real Time Communication || https://doi.org/10.1145/3664647.3685515
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Directed Views in Virtual Reality: A Semantic Approach to Volumetric Video Storytelling || https://doi.org/10.1145/3675231.3678872
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Back to the Virtual Future: Presence in Cinematic Virtual Reality || https://doi.org/10.1145/3672406.3672418
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Exploring entropy-based solutions for trajectory prediction in virtual reality || https://doi.org/10.1145/3712677.3720460
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || IXR '25: 3rd International Workshop on Interactive eXtended Reality || https://doi.org/10.1145/3746027.3762385
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || A Platform for Collecting User Behaviour Data during Social VR Experiments Using Mozilla Hubs || https://doi.org/10.1145/3652212.3652225
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Spatial Media Controller: Exploring the Potential of Augmented Reality, Virtual Reality, Volumetric Capture and 360 Videos for News Broadcasting || https://doi.org/10.1145/3706370.3727868
|-
| Extended Reality (VR/AR/MR) & HCI || Other || TangibleMRCreate: Intuitive Authoring of Mixed Reality Content || https://doi.org/10.2312/EGVE.20231339
|-
| Extended Reality (VR/AR/MR) & HCI || Other || RCQoEA-360VR: Real-time Continuous QoE Scores for HMD-based 360° VR Dataset || https://doi.org/10.1145/3746027.3758259
|-
| Extended Reality (VR/AR/MR) & HCI || Other || Avatar Customization, Personality, and the Perception of Work Group Inclusion in Immersive Virtual Reality || https://doi.org/10.1145/3584931.3606992
|-
| Healthcare, Medicine & Accessibility || Conference proceedings || QoE Evaluation of Remote Physiotherapy in Volumetric Video and Video-Based Real-Time Communication || https://doi.org/10.1109/ICME59968.2025.11209852
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Predicting Quality of Multimedia Experience Using Electrocardiogram and Respiration Signals || https://doi.org/10.1109/ACCESS.2024.3420103
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || VVGLTF: Efficient Streaming of Volumetric Video with GLTF || https://doi.org/10.5281/ZENODO.17651190
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || VVGLTF: Efficient Streaming of Volumetric Video with GLTF || https://doi.org/10.5594/JMI.2025/GLNG7938
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| UVG-CWI-DQPC: Dual-Quality Point Cloud Dataset || Dataset || https://doi.org/10.1145/3746027.3758263 || Point cloud dataset optimized for volumetric video applications.
|-
| ComPEQ-MR || Dataset || https://doi.org/10.1145/3625468.3652182 || A compressed point cloud dataset featuring eye tracking and quality assessment in mixed reality.
|-
| TSalV360: Text-driven Saliency Detection || Dataset / Method || https://doi.org/10.5281/ZENODO.17649129 || Method and dataset tailored for saliency detection within 360-degree videos.
|-
| VR2Gather || Open-Source System || https://doi.org/10.1145/3664647.3685515 || A collaborative social VR system open-sourced for adaptive multi-party real-time communication.
|-
| TangibleMRCreate || Software Tool || https://doi.org/10.2312/EGVE.20231339 || An intuitive authoring tool created to facilitate the development of mixed reality content.
|}

TIMELAPSE

2026-09-01T14:51:10Z

CollectiveIntelligenceAdmin:

=== TIMELAPSE Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101137707 || 01/06/2024 || 30/11/2025 || UNIVERSITA DEGLI STUDI DI MILANO
|}
=== Project description ===
Chemotherapy can involve lengthy treatment sessions, lasting up to several hours. Such a duration, spent in an overly medicalized setting, can induce in the patients a monopolizing focus on their pathology, which leads to a substantial decrease in their mental well-being. One way to alleviate the impact of long chemotherapy sessions would be accelerating subjective time passage as perceived by the patients, therefore making the treatment seemingly end more quickly. Stemming from the ERC Advanced Grant AN-ICON, the TIMELAPSE project proposes to prototype, test, and launch on the market a virtual reality (VR) application that will accelerate subjective time passage during chemotherapy. The idea, whose singular aspects were the object of previous scientific evidence, was so far not implemented comprehensively. TIMELAPSE will fill this R&D gap with unprecedented methods and targets, adopting a patient-centred approach to innovatively incorporate in the conception of the VR application the irreplaceable perspective of its end-users: the oncologic patients. TIMELAPSE will take this idea to proof of concept by means of five subsequent phases: 1. Theoretical elaboration, to shape a theoretical hypothesis concerning what types of VR content might accelerate subjective time passage during chemotherapy; 2. Participatory design, to refine this hypothesis by incorporating the users’ perspective; 3. Production, to develop the content for the VR application, to obtain a prototype ready to be tested. 4. Assessment, to demonstrate the tolerability and effectiveness of the VR application; and 5. Pre-commercialization, to prepare the launch of the VR application on the market. To ensure appropriate methodological tools for each phase, TIMELAPSE will rely on a collaboration between three actors: a core research group (part of the AN-ICON team); an industrial partner expert in VR applications (Khora); and a clinical partner with substantial expertise in cancer treatment (Fondazione IRCCS San Gerardo dei Tintori).

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Aesthetics Meets Oncology: A Participatory Design Project to Speed Up Time Passage in Chemotherapy Through Virtual Reality || https://doi.org/10.7413/2035-8466068
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || The perception of time in digital environments: a patient-centred approach to using Virtual Reality to enhance well-being during chemotherapy || https://doi.org/10.32043/JIMTLT.V5I4
|}

THEIA-XR

2026-09-01T14:51:04Z

CollectiveIntelligenceAdmin:

=== THEIA-XR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator !! Project website
|-
| https://cordis.europa.eu/project/id/101092861 || 01/01/2023 || 31/12/2025 || TTCONTROL GMBH / Austria || https://www.theia-xr.eu/
|}
=== Project description ===
Even though extended reality (XR) technologies are not being fully implemented, they have the potential to offer substantial advantages to various sectors if further researched and advanced. The EU-funded THEIA-XR project will develop a set of XR technologies to expand workplace, workload and operation visibility for machinery operators. The technologies will improve worker-machine cooperation efficiency while also improving safety. The project approach will be validated by tests in three different sectors: snow grooming, construction and logistics. Finally, the project will work alongside stakeholders and researchers to develop a strategy for improved implementation of the proposed technologies in the workplace.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || Spotlight Control for Real-Time Targeting || https://doi.org/10.5281/ZENODO.12658308
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Spotlight Control for Real-Time Targeting || https://doi.org/10.5281/ZENODO.12658307
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Thermochromic Temperature Measurement: Towards an Alternative to Thermal Cameras || https://doi.org/10.1109/SAS65169.2025.11105166
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || PanoTherm: Panoramic Thermal Imaging for Object Detection and Tracking || https://doi.org/10.5220/0012330400003660
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Instant Segmentation and Fitting of Excavations in Subsurface Utility Engineering || https://doi.org/10.1109/TVCG.2024.3372064
|-
| Extended Reality (VR/AR/MR) & HCI || Book chapters || Making the Invisible Visible - AR supported situation awareness in the snow groomer operations || https://doi.org/10.32040/2242-122X.2025.T440
|-
| Extended Reality (VR/AR/MR) & HCI || Book chapters || Extended Reality simulator to evaluate remote control interactions for reach stackers || https://doi.org/10.5281/ZENODO.18338766
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Assisted Trailer Parking using a Reverse Camera System and Inverse Kinematics || https://doi.org/10.1109/IV64158.2025.11097420
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || 3D Depth Experience in VR from Monocular Video || https://doi.org/10.1109/VRW66409.2025.00086
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Making the invisible visible for off-highway machinery by conveying extended reality technologies || https://doi.org/10.32040/2242-122X-2023.T422
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || International Journal of Human Computer Studies || https://doi.org/10.5220/0012393100003648
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Computers and Graphics || https://doi.org/10.1109/VRW62533.2024.00047
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || International Journal of Human Computer Studies || https://doi.org/10.24406/PUBLICA-5669
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Bag of World Anchors for Instant Large-Scale Localization || https://doi.org/10.1109/TVCG.2023.3320264
|-
| Robotics, Manufacturing & Industry 4.0 || Conference proceedings || Spatial Augmented Reality for Heavy Machinery Using Laser Projections || https://doi.org/10.2139/ssrn.4942184
|-
| Robotics, Manufacturing & Industry 4.0 || Conference proceedings || Early-stage user experience design of the remote operation concept of the harbour's reachstacker by expoiting eXtended Reality || https://doi.org/10.54941/ahfe1005411
|-
| Robotics, Manufacturing & Industry 4.0 || Other || Entwicklung und Evaluation eines Extended-Reality-Bedieninterfaces für Baumaschinen zur Interaktion mit digitalen Baugrubendaten im Kontext BIM || https://doi.org/10.5281/ZENODO.18377690
|}

SUN

2026-09-01T14:50:54Z

CollectiveIntelligenceAdmin:

=== SUN Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator !! Project website
|-
| https://cordis.europa.eu/project/id/101092612 || 01/12/2022 || 30/11/2025 || CNR Rome || https://www.sun-xr-project.eu/
|}
=== Project description ===
Extended reality (XR) is an emerging technology with promising potential in many fields including health, communication and safety. However, overcoming XR’s limitations in providing authentic interactive social environments is key to further developing its applications. The EU-funded SUN project aims to advance the social interactivity of XR technology by establishing scalable models with sustained and convincing virtual environments. The project will also improve the data-processing capability of wearable devices and develop wearable sensors and tactile interfaces to improve user experience. SUN will validate these models in three real-life situations: rehabilitation therapy, improved safety and social interaction among workers, and facilitate interaction for disabled users.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || Information Dissimilarity Measures in Decentralized Knowledge Distillation: A Comparative Analysis || https://doi.org/10.1007/978-3-031-75823-2_12
|-
| AI, Machine Learning & Data Science || Conference proceedings || VISIONE 5.0: Enhanced User Interface and AI Models for VBS2024 || https://doi.org/10.1007/978-3-031-53302-0_29
|-
| AI, Machine Learning & Data Science || Conference proceedings || Impact of generative artificial intelligence on workload, efficiency and labour productivity || https://doi.org/10.1016/J.IFACOL.2025.09.237
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || A survey on class-agnostic counting: Advancements from reference-based to open-world text-guided approaches || https://doi.org/10.1016/J.CVIU.2026.104703
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || The State-of-the-Art in Lifelog Retrieval: A Review of Progress at the ACM Lifelog Search Challenge Workshop 2022-2024 || https://doi.org/10.1109/ACCESS.2025.3644952
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Training-free sparse representations of dense vectors for scalable information retrieval || https://doi.org/10.1016/J.IS.2025.102567
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || The Devil is in the Fine-Grained Details: Evaluating open-Vocabulary Object Detectors for Fine-Grained Understanding || https://doi.org/10.5281/ZENODO.13269555
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || In the Wild Video Violence Detection: An Unsupervised Domain Adaptation Approach || https://doi.org/10.1007/S42979-024-03126-3
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Evaluating Performance and Trends in Interactive Video Retrieval: Insights From the 12th VBS Competition || https://doi.org/10.1109/ACCESS.2024.3405638
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || nSimplex Zen : A Novel Dimensionality Reduction for Euclidean and Hilbert Spaces || https://doi.org/10.1145/3647642
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Computer-Supported Strategic Decision Making for Ecosystems Creation || https://doi.org/10.3390/COMPUTERS13120322
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Geometric deep learning for statics-aware grid shells || https://doi.org/10.1016/J.COMPSTRUC.2023.107238
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || A Learnheuristic Algorithm for the Capacitated Dispersion Problem under Dynamic Conditions || https://doi.org/10.3390/A16120532
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Tokenized Markets Using Blockchain Technology: Exploring Recent Developments and Opportunities || https://doi.org/10.3390/info14060347
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Algorithms || https://doi.org/10.3390/A17050200
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Mind the Prompt: A Novel Benchmark for Prompt-Based Class-Agnostic Counting || https://doi.org/10.1109/WACV61041.2025.00774
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Beyond human imagination: The art of creating prompt-driven 3D scenes with Generative AI || https://doi.org/10.32040/2242-122X.2024.T432
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || A Comparative Demonstration of Relevance Feedback Methods for Image Retrieval || https://doi.org/10.1007/978-3-032-06069-3_30
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || 3D Visualization of Biological Data in Ultra High Definition Virtual Reality || https://doi.org/10.1109/VRW66409.2025.00104
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Breaking the 2D Dependency: What Limits 3D-Only Open-Vocabulary Scene Understanding || https://doi.org/10.1109/CBMI66578.2025.11339286
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Is CLIP the main roadblock for fine-grained open-world perception? || https://doi.org/10.48550/ARXIV.2404.03539
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Skipping Spheres: SDF Scaling & Early Ray Termination for Fast Sphere Tracing || https://doi.org/10.2312/CGVC.20241219
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Comparative Analysis of Relevance Feedback Techniques for Image Retrieval || https://doi.org/10.1007/978-981-96-2054-8_16
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Spatio-Temporal 3D Reconstruction from Frame Sequences and Feature Points || https://doi.org/10.1145/3672406.3672415
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Enhanced real-time motion transfer to 3D avatars using RGB-based human 3D pose estimation || https://doi.org/10.1145/3672406.3672427
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || The Emotions of the Crowd: Learning Image Sentiment from Tweets via Cross-Modal Distillation || https://doi.org/10.3233/FAIA230503
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || ViSketch-GPT: Collaborative Multi-scale Feature Extraction For Hand-Drawn Sketch Retrieval || https://doi.org/10.1007/978-3-032-06069-3_1
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || AI-Driven Specular Removal for 3D Asset Creation || https://doi.org/10.1109/DSP65409.2025.11075117
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Multimedia Information Retrieval in XR || https://doi.org/10.1145/3664647.3689176
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Text-to-Motion Retrieval: Towards Joint Understanding of Human Motion Data and Natural Language || https://doi.org/10.48550/arxiv.2305.15842
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || SegmentCodeList: Unsupervised Representation Learning for Human Skeleton Data Retrieval || https://doi.org/10.1007/978-3-031-28238-6_8
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Vec2Doc: Transforming Dense Vectors into Sparse Representations for Efficient Information Retrieval || https://doi.org/10.1007/978-3-031-46994-7_18
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || MC-GTA: A Synthetic Benchmark for Multi-Camera Vehicle Tracking || https://doi.org/10.5281/zenodo.8335396
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || An Optimized Pipeline for Image-Based Localization in Museums from Egocentric Images || https://doi.org/10.1007/978-3-031-43148-7_43
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Vi-SketchGPT: A Novel Multi-Scale and Context-Aware Representation for Sketch Generation and Classification || https://doi.org/10.1109/ACCESS.2026.3659732
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Joint-Dataset Learning and Cross-Consistent Regularization for Text-to-Motion Retrieval || https://doi.org/10.1145/3744565
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || ACM Transactions on Graphics || https://doi.org/10.1145/3687898
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Multimodal fusion of inertial sensors and single RGB camera data for 3D human pose estimation based on a hybrid LSTM-Random forest fusion network || https://doi.org/10.1016/J.IOT.2024.101465
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Creating High-quality 3D Assets for Realistic xR Solutions || https://doi.org/10.5281/zenodo.17522038
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Texture Inpainting for Photogrammetric Models || https://doi.org/10.1111/cgf.14735
|-
| Earth Observation, Environment & Smart Cities || Peer reviewed articles || A discrete-event simheuristic for enhancing urban mobility || https://doi.org/10.1016/J.SIMPAT.2025.103084
|-
| Earth Observation, Environment & Smart Cities || Peer reviewed articles || Modeling and Optimization of NO2 Stations in the Smart City of Barcelona || https://doi.org/10.3390/APP142210355
|-
| Education, Training & Serious Games || Conference proceedings || METAVERSE IN HIGHER EDUCATION || https://doi.org/10.21125/INTED.2025.1760
|-
| Education, Training & Serious Games || Peer reviewed articles || The Wizard Apprentice: A Serious Games System in Immersive VR as a Feasible Rehabilitation Approach in Children With Cerebral Palsy || https://doi.org/10.1109/TNSRE.2025.3595420
|-
| Education, Training & Serious Games || Peer reviewed articles || Procedural generation of geometric patterns for thin shell fabrication || https://doi.org/10.1016/J.CAG.2024.103958
|-
| Education, Training & Serious Games || Peer reviewed articles || Extended reality and metaverse technologies for industrial training, safety and social interaction || https://doi.org/10.1016/J.IFACOL.2024.09.274
|-
| Ethics, Society, Arts & Culture || Book chapters || Bridging the Digital Divide: A Human Rights-Based Approach to Digital Literacy and Equity in the EU || https://doi.org/10.5772/INTECHOPEN.1011614
|-
| Ethics, Society, Arts & Culture || Conference proceedings || MusiCityX: Conceptual Tools for Urban Architectural Design through Music Composition || https://doi.org/10.1145/3749012.3749068
|-
| Ethics, Society, Arts & Culture || Monographic books || SUN: Social and hUman ceNtered XR - A Horizon Europe Project Paving the Way for the Widespread Adoption of Extended and Virtual Worlds || https://doi.org/10.32079/ISTI-BOOK-2025/001
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || A biased-randomised iterated local search for the team orienteering arc routing problem allowing different origin and destination || https://doi.org/10.1007/S10732-025-09559-0
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || A Learnheuristic Algorithm Based on Thompson Sampling for the Heterogeneous and Dynamic Team Orienteering Problem || https://doi.org/10.3390/MATH12111758
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || Using Reinforcement Learning to Solve a Dynamic Orienteering Problem with Random Rewards Affected by the Battery Status || https://doi.org/10.3390/batteries9080416
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || CONTEXT-GAD: A Context-Aware Gaze Adaptive Dwell model for Gaze-based Selections in XR Environments || https://doi.org/10.1145/3756884.3766048
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || A Direct-Drive, Wearable Armband Device to Experiment Combined Continuous and Vibrotactile Haptic Feedback for Guidance in Motor Tasks || https://doi.org/10.1007/978-3-031-70061-3_18
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Effect of Gaze Visualization on Task Efficiency and User Behavior for Guidance Scenarios in Co-Located AR Collaboration || https://doi.org/10.1109/VRW66409.2025.00120
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || The Social and hUman CeNtered XR: SUN XR Project || https://doi.org/10.1007/978-3-031-43401-3_15
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || A Gaze Prediction Model for Task-Oriented Virtual Reality || https://doi.org/10.2312/EGP.20251020
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || A Lightweight Haptic Feedback Glove Employing Normal Indentation, Lateral Skin Stretch and both Softness and Hardness Rendering || https://doi.org/10.1109/ISMAR-ADJUNCT60411.2023.00113
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || A Miniature Direct-Drive Hydraulic Actuator for Wearable Haptic Devices based on Ferrofluid Magnetohydrodynamic Levitation || https://doi.org/10.1109/WHC56415.2023.10224414
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Social and hUman ceNtered XR || https://doi.org/10.5281/zenodo.7907108
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Rendering Fine Tactile Feedback With a Novel Hydraulic Actuation Method for Wearable Haptic Devices || https://doi.org/10.1109/ACCESS.2024.3448368
|-
| Healthcare, Medicine & Accessibility || Conference proceedings || Hardware-Efficient EMG Decoding for Next-Generation Hand Prostheses || https://doi.org/10.48550/ARXIV.2405.20052
|-
| Healthcare, Medicine & Accessibility || Conference proceedings || SUN Accessibility Pilot: Extended reality for people with serious mobility and verbal communication diseases || https://doi.org/10.1016/J.IFACOL.2024.09.273
|-
| Healthcare, Medicine & Accessibility || Conference proceedings || Enhancing EEG Classification for Motor Imagery Control of a VR Game based on Deep Learning Techniques on Small Datasets || https://doi.org/10.1109/EMBC58623.2025.11251707
|-
| Healthcare, Medicine & Accessibility || Conference proceedings || Embodied Augmented Reality for Lower Limb Rehabilitation || https://doi.org/10.2312/CL.20241050
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Optimization frameworks for bespoke sensory encoding in neuroprosthetics || https://doi.org/10.1063/5.0249434
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || The expanding horizon of neurotechnology: Is multimodal neuromodulation the future? || https://doi.org/10.1371/JOURNAL.PBIO.3002885
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Replacing Attention with Modality-wise Convolution for Energy-Efficient PPG-based Heart Rate Estimation using Knowledge Distillation || https://doi.org/10.1109/JBHI.2025.3580474
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Bridging Bench to Bedside for Brain Health: Non-Invasive Brain Stimulation for Neurodegenerative Diseases || https://doi.org/10.3390/CTN9030043
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Our research path toward the restoration of natural sensations in hand prostheses || https://doi.org/10.1111/AOR.14823
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills || https://doi.org/10.1038/S41562-024-01901-Z
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || A Knee Rehabilitation Exercises Dataset for Postural Assessment using Wearable Devices || https://doi.org/10.1038/S41597-025-04963-4
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Remapping Wetness Perception in Upper Limb Amputees || https://doi.org/10.1002/AISY.202300512
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Safety, tolerability and blinding efficiency of non-invasive deep transcranial temporal interference stimulation: first experience from more than 250 sessions || https://doi.org/10.1088/1741-2552/AD2D32
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || A sensory-motor hand prosthesis with integrated thermal feedback || https://doi.org/10.1016/J.MEDJ.2023.12.006
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || A Framework for Modeling, Optimization, and Musculoskeletal Simulation of an Elbow–Wrist Exosuit || https://doi.org/10.3390/ROBOTICS13040060
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Restoration of natural thermal sensation in upper-limb amputees || https://doi.org/10.1126/SCIENCE.ADF6121
|-
| Robotics, Manufacturing & Industry 4.0 || Conference proceedings || Bibliometric Analysis of Immersive Technologies in Supply Chain Strategy: Knowledge-Based Systems Case || https://doi.org/10.1007/978-3-031-71739-0_18
|-
| Robotics, Manufacturing & Industry 4.0 || Conference proceedings || A Framework for Vision-Based 3D Inspections for Maintenance Activities and Digital Twin Integration || https://doi.org/10.1109/CBMI62980.2024.10859253
|-
| Robotics, Manufacturing & Industry 4.0 || Conference proceedings || Wireless Haptic Glove using Nitinol as a Force Feedback Actuator || https://doi.org/10.1145/3715071.3750433
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Hand Teleoperation with Combined Kinaesthetic and Tactile Feedback: A Full Upper Limb Exoskeleton Interface Enhanced by Tactile Linear Actuators || https://doi.org/10.3390/ROBOTICS13080119
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || A Biased-Randomized Discrete Event Algorithm to Improve the Productivity of Automated Storage and Retrieval Systems in the Steel Industry || https://doi.org/10.3390/A17010046
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || A Hybrid Simulation and Reinforcement Learning Algorithm for Enhancing Efficiency in Warehouse Operations || https://doi.org/10.3390/A16090408
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Simulation of Heuristics for Automated Guided Vehicle Task Sequencing with Resource Sharing and Dynamic Queues || https://doi.org/10.3390/MATH12020271
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Simulation of Heuristics for AGV Task Sequencing || Dataset || https://doi.org/10.3390/MATH12020271 || Replication data utilizing dynamic queues and resource sharing.
|-
| Knee Rehabilitation Dataset || Dataset || https://doi.org/10.1038/S41597-025-04963-4 || A specialized dataset of knee rehabilitation exercises for postural assessment utilizing wearable devices.
|-
| MC-GTA || Dataset / Benchmark || https://doi.org/10.5281/zenodo.8335396 || A synthetic benchmark dataset aimed at advancing multi-camera vehicle tracking capabilities.
|-
| Ubervvald || Software Library || https://doi.org/10.1007/978-981-96-5887-9_14 || An advanced object detection library created to optimize complex Convolutional Neural Networks (CNNs).
|}

SPIRIT

2026-09-01T14:50:40Z

CollectiveIntelligenceAdmin:

=== SPIRIT Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101070672 || 01/10/2022 || 30/09/2025 || INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM / Belgium
|}
=== Project description ===
Immersive telepresence technologies will have groundbreaking impacts on interactions amongst individuals and machines in cyberspace in several vertical sectors, including education and training, healthcare, the manufacturing industry, etc. However, these technologies face critical limitations concerning the application platform and the underlying network support to achieve seamless presentation, processing and delivery of immersive telepresence content on a large scale. The EU-funded SPIRIT project will build on the existing TRL4 application platforms and network infrastructures developed by the project partners to address technical challenges and further develop all significant aspects of telepresence technologies to achieve targeted TRL7. The project will focus on network-layer, transport-layer, application/content-layer techniques, security and privacy mechanisms.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || GreenWise: Intelligent Application Migration for Containerized Machine Learning Services in the Computing Continuum || https://doi.org/10.1145/3773274.3774275
|-
| AI, Machine Learning & Data Science || Conference proceedings || Enabling Generative AI based Multi-sensory XR Applications with Mobile Edge Computing || https://doi.org/10.1109/INFOCOMWKSHPS65812.2025.11152969
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Immersive and Interactive Subjective Quality Assessment of Dynamic Volumetric Meshes || https://doi.org/10.1109/qomex58391.2023.10178610
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || A Platform for Subjective Quality Assessment in Mixed Reality Environments || https://doi.org/10.1109/qomex58391.2023.10178443
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Quality of Experience Modelling and Analysis for Live Holographic Teleportation || https://doi.org/10.1109/ICNC59896.2024.10556032
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || No-Reference Quality of Experience Model for Dynamic Point Clouds in Augmented Reality || https://doi.org/10.1145/3638036.3640248
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Impact of Quality and Distance on the Perception of Point Clouds in Mixed Reality || https://doi.org/10.1109/qomex58391.2023.10178491
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Video-Driven Animation of Neural Head Avatars || https://doi.org/10.2312/vmv.20231237
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Eye-Tracking, Quality Assessment, and QoE Prediction Models for Point Cloud Videos: Extended Analysis of the ComPEQ-MR Dataset || https://doi.org/10.1109/ACCESS.2025.3635789
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Animatable Virtual Humans: Learning Pose-Dependent Human Representations in UV Space for Interactive Performance Synthesis || https://doi.org/10.1109/TVCG.2024.3372117
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || A Multidimensional Media Adaptation Framework for Live Holographic Communication || https://doi.org/10.1109/TMM.2025.3623505
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Scalable MDC-Based WebRTC Streaming for One-to-Many Volumetric Video Conferencing || https://doi.org/10.1145/3768314
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Characterization of the Quality of Experience and Immersion of Point Cloud Videos in Augmented Reality Through a Subjective Study || https://doi.org/10.1109/ACCESS.2023.3326374
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Demonstrating Adaptive Many-to-Many Immersive Teleconferencing for Volumetric Video || https://doi.org/10.1145/3625468.3652192
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Enabling User Intent-based Network Path Adaptation for Live Volumetric Streaming || https://doi.org/10.23919/IFIPNetworking62109.2024.10619068
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || ComPEQ-MR || https://doi.org/10.1145/3625468.3652182
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Scalable MDC-Based Volumetric Video Delivery for Real-Time One-to-Many WebRTC Conferencing || https://doi.org/10.1145/3625468.3647617
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || IEEE Transactions on Visualization and Computer Graphics || https://doi.org/10.48550/arxiv.2310.03615
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Demonstration of Viewport-Aware Hybrid Broadcast-Unicast Streaming for Volumetric Video || https://doi.org/10.1109/NOF66640.2025.11223293
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Enabling Haptic-Integrated Interactive Holographic Video Streaming Powered by 5G Edge Computing || https://doi.org/10.1109/ICME59968.2025.11209485
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Enabling eBPF-based packet duplication for robust volumetric video streaming || https://doi.org/10.1109/ISCC61673.2024.10733617
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || User-Intent Aware Transport-Layer Intelligence for Frame Synchronisation in Multi-Party XR Application || https://doi.org/10.1109/GEM61861.2024.10585795
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| GreenWise || Software / Algorithm || https://doi.org/10.1145/3773274.3774275 || An intelligent application migration framework for containerized machine learning services.
|-
| STEP-MR || Testing Platform || https://athena.itec.aau.at/2025/11/step-mr-a-subjective-testing-and-eye-tracking-platform-for-dynamic-point-clouds-in-mixed-reality/ || A subjective testing and eye-tracking platform built specifically for dynamic point clouds in mixed reality.
|}

SONICOM

2026-09-01T14:50:34Z

CollectiveIntelligenceAdmin:

=== SONICOM Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101017743 || 01/01/2021 || 30/06/2026 || IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE / UK
|}
=== Project description ===
Sound is an integral part of the human experience. As one of the most important ways of sensing and interacting with our environment, sound plays a major role in shaping how the world is perceived. In virtual or augmented reality (VR/AR), simulating spatially correct audio is of vital importance to delivering an immersive virtual experience. However, acoustic VR/AR presents many challenges. Using the power of artificial intelligence, the EU-funded SONICOM project aims to deliver the next milestone in immersive audio simulation. The goal is to design the next generation of 3D audio technologies, provide tailored audio solutions and significantly improve how we interact with the virtual world.

=== Project outputs ===
==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| The SONICOM HRTF Dataset || Dataset || https://doi.org/10.17743/jaes.2022.0066 || Dataset of Head-Related Transfer Functions for artificial intelligence-driven immersive audio.
|-
| PAN-AR || Dataset || https://doi.org/10.1145/3678299.3678332 || A multimodal dataset featuring higher-order ambisonics room impulse responses and spherical pictures.
|-
| NumCalc || Open-Source Software || https://doi.org/10.1016/j.enganabound.2024.01.008 || An open-source Boundary Element Method (BEM) code for solving acoustic scattering problems.
|-
| Auditory modelling toolbox (AMT) || Software || https://ecosystem.sonicom.eu/tools/1 || Toolbox to facilitate reproducible research in auditory modeling.
|-
| Frambi || Software Framework || https://doi.org/10.61782/fa.2023.0494 || A flexible software framework tailored for auditory modeling based on Bayesian inference.
|}

SHARESPACE

2026-09-01T14:50:28Z

CollectiveIntelligenceAdmin:

=== SHARESPACE Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator !! Project website
|-
| https://cordis.europa.eu/project/id/101092889 || 01/01/2023 || 31/12/2025 || DFKI || https://sharespace.eu/
|}
=== Project description ===
Extended reality (XR) is an emerging technology with promising potential in many areas, but several limitations must be overcome to enrich the interactive experience for users. The EU-funded SHARESPACE project aims to establish a novel prototype for a socially interactive avatar and/or agent based on human sensorimotor communication. It will capture natural body movements, facial expressions and hand gestures to compile an array of sensorimotor primitives: these will aid the design of AI-based architecture of a fully mobile human rendering with customisable characteristics. SHARESPACE will validate the prototype in three real-life situations of shared hybrid spaces involving human and artificial agents in the fields of health, sport and art

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || The Unfaithful Copy: Performed AI ‘Personhood’in Mixed Reality Platforms || https://doi.org/10.32040/2242-122X.2024.T432
|-
| AI, Machine Learning & Data Science || Conference proceedings || Demonstrating the effectiveness of combining heuristic and data-driven methods to achieve scalable and adaptive motion styles || https://doi.org/10.1109/VRW66409.2025.00144
|-
| AI, Machine Learning & Data Science || Conference proceedings || Rendering Togetherness: Embodied Social Synchronization in Multi-User VR || https://doi.org/10.1109/ISMAR67309.2025.00079
|-
| AI, Machine Learning & Data Science || Conference proceedings || Learning-based cognitive architecture for enhancing coordination in human groups || https://doi.org/10.48550/arXiv.2406.06297
|-
| AI, Machine Learning & Data Science || Conference proceedings || Control- Tutored Deep Reinforcement Learning || https://doi.org/10.48550/arXiv.2212.01343
|-
| AI, Machine Learning & Data Science || Other || Continuification Control of Large-Scale Multiagent Systems Under Limited Sensing and Structural Perturbations || https://doi.org/10.48550/arxiv.2303.13246
|-
| AI, Machine Learning & Data Science || Other || Data-driven design of complex network structures to promote synchronization || https://doi.org/10.48550/arxiv.2309.10941
|-
| AI, Machine Learning & Data Science || Other || Local convergence of multi-agent systems towards triangular patterns || https://doi.org/10.48550/arxiv.2303.11865
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Local Convergence of Multi-Agent Systems Toward Rigid Lattices || https://doi.org/10.1109/lcsys.2023.3289060
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning || https://doi.org/10.48550/arxiv.2311.10026
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Kinematic priming of action predictions || https://doi.org/10.1016/j.cub.2023.05.055
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Action prediction in psychosis || https://doi.org/10.1038/s41537-023-00429-x.
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Improving Image Reconstruction using Incremental PCA-Embedded Convolutional Variational Auto- Encoder || https://doi.org/10.24132/10.24132/CSRN.3401.12
|-
| Ethics, Society, Arts & Culture || Book chapters || Five Reality Types: The Embedded Ethicist in VR and Mixed-Reality Platforms || https://doi.org/10.1007/978-981-96-1154-6_9
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Multi - Modal Signal Processing for Avatar Motion Adaptation || https://doi.org/10.1109/DSP65409.2025.11075085
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || The emerging role of virtual reality as an adjunct to procedural sedation and anesthesia || https://doi.org/10.3390/jcm12030843
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Data-driven architecture to encode information in the kinematics of robots and artificial avatars || https://doi.org/10.48550/arXiv.2403.06557
|-
| Robotics, Manufacturing & Industry 4.0 || Other || eXtended Reality of socio-motor interactions: Current Trends and Ethical Considerations for Mixed Reality Environments Design || https://doi.org/10.1145/3610661.361798
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Distributed control for geometric pattern formation of large-scale multirobot systems || https://doi.org/10.48550/arXiv.2207.14567
|}
==== Technological assets ====
{| class="wikitable sortable"
! Domain !! Title !! Type of Asset !! Link / DOI !! Description
|-
| Digital, Industry & Space || CT-DQN: Control-Tutored Deep Reinforcement Learning || AI Model / Software || https://doi.org/10.48550/arXiv.2212.01343 || Code base and model architecture for a control-tutored deep reinforcement learning methodology.
|-
| Digital, Industry & Space || Deep Space Starter Kit || Software || https://github.com/ArsElectronicaFuturelab/UE-DeepSpace-Starter || The Deep Space Starter Kit is an Unreal Engine template includes all configurations to quickly start a new project for this specific space. This plug-in is compatible with Unreal Engine 5.7.
|-
| Culture, creativity || pharus || Plug-in || https://github.com/ArsElectronicaFuturelab/UE-DeepSpace-PharusLasertracking || The pharus tracking system is developed by researcher and artist Otto Naderer from the Ars Electronica Futurelab. This tracking system allows for the locations of objects, people, or groups to be tracked on the Deep Space floor.
|-
| Culture, creativity || Deep Sync Infrastructure || Plug-in || https://github.com/ArsElectronicaFuturelab/UE-DeepSpace-DeepSync https://github.com/ArsElectronicaFuturelab/DeepSync-Wearable-Server https://github.com/ArsElectronicaFuturelab/DeepSync-Wearable-Firmware || The Deep Sync Infrastructure brings biodata to the co-immersive Deep Space 8K. It includes the development of custom-made wearables and an Unreal Engine plug-in.
|-
| Culture, creativity || Cognitive Architectures || Plug-ins || https://sharespace.eu/cognitive-architectures/ || Within SHARESPACE, cognitive architectures were designed, developed, and validated by SHARESPACE partner CRdC to drive the movement of virtual characters with different levels of autonomization.
|-
| Culture, creativity || Pixel Streaming Service || Plug-in || https://github.com/ALE-Rainbow/sharespace-pixel-streaming-infrastructure || WebRTC enables direct peer-to-peer audio connections that avoid the mixing delays inherent in centralized voice systems. A mesh network architecture allows multiple P2P connections between emitters and receivers, minimizing latency while maintaining audio quality.
|-
| Culture, creativity || Web Client-Server Bundle || Plug-in || https://github.com/ALE-Rainbow/sharespace-pixel-streaming-cpp-service || The project delivered a web client-server bundle that could be hosted either locally or in ALE cloud with connectors for direct connection with XR applications.
|-
| Culture, creativity || Avatar Replication in Shared Environments || Plug-in || https://github.com/CYENS/virtual-share-space || A unified multi-user platform was developed in Unreal Engine 5 by the team of Cyens, allowing distributed clients to connect and interact within shared virtual environments.
|}

PRESENCE

2026-09-01T14:50:20Z

CollectiveIntelligenceAdmin:

=== PRESENCE Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135025 || 01/01/2024 || 31/12/2026 || FUNDACIO PRIVADA I2CAT, INTERNET I INNOVACIO DIGITAL A CATALUNYA / Spain
|}
=== Project description ===
The concept of presence can be understood as a synthesis of interrelated psychophysical ingredients where multiple perceptual dimensions intervene. A better understanding on how specific aspects, such as plausibility (the illusion that virtual events are really happening), co-presence (the illusion of being with others), or place illusion (the feeling of being there) impact XR experiences is key to improve their quality. The availability and performance of current technologies do not reach high levels of presence in XR, which is essential to get us closer than ever to the perennial VR dream: to be anywhere, doing anything, together with others, from any place. PRESENCE will impact multiple dimensions of presence in physical-digital worlds, addressing three main challenges: i) how to create realistic visual interactions among remote humans, delivering high-end holoportation based on live volumetric capturing, compression and optimization techniques, under heterogeneous computation and network conditions; ii) how to provide realistic touch among remote users and synthetic objects, developing novel haptic systems and enabling spatial multi device synchronisation in multi user scenarios; iii) how to produce realistic social interactions among avatars and agents, generating AI virtual humans, representing actual users or AI agents. PRESENCE will ensure the future uptake of research results following a threefold evaluation method: 1) each technology will be independently evaluated to understand its impact on the illusion of presence; 2) each component will be evaluated by the integration team, providing scientific and technical feedback in order to facilitate their use in each project iteration as well as beyond the project scope, towards technology transfer and exploitation; 3) all components will be integrated in two demonstrators (professional and social setups), following a human-centred design approach and ultimately evaluating the user experience.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || I Hear, See, Speak & Do: Bringing Multimodal Information Processing to Intelligent Virtual Agents for Natural Human-AI Communication || https://doi.org/10.1109/VRW66409.2025.00469
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || A flexible toolkit for real-time action recognition of virtual humans in XR/AR environments || https://doi.org/10.5281/ZENODO.15974094
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || LiveSkeleton: High-Quality Real-Time Human Tracking and Pose Estimation || https://doi.org/10.1109/ISM63611.2024.00054
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || Immersive documentary journalism: exploring the impact of 360° virtual reality compared with a 2D screen display on the responses of people toward undocumented young migrants to Spain || https://doi.org/10.3389/FCOMM.2024.1474524
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Methodological Reflections on Early-Stage Requirement Gathering and Prioritization For Immersive Extended Reality Applications || https://doi.org/10.5753/IMXW.2025.7940
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || A Toolkit for Creating Intelligent Virtual Humans in Extended Reality || https://doi.org/10.1109/VRW66409.2025.00149
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Confusing virtual reality with reality – An experimental study || https://doi.org/10.1016/J.ISCI.2025.112655
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || The Role of Sensorimotor Contingencies and Eye Scanpath Entropy in Presence in Virtual Reality: a Reinforcement Learning Paradigm || https://doi.org/10.1109/TVCG.2025.3547241
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| LiveSkeleton || Software / Algorithm || https://doi.org/10.1109/ISM63611.2024.00054 || A system providing high-quality real-time human tracking and pose estimation.
|-
| Flexible toolkit for real-time action recognition || Toolkit / Software || https://doi.org/10.5281/ZENODO.15974094 || A flexible, reusable toolkit for the real-time action recognition of virtual humans in XR/AR environments.
|}

=== POPULAR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135770 || 01/01/2024 || 31/12/2026 || ESSILOR INTERNATIONAL / France
|}
=== Project description ===
The Augmented Reality Eyewear (ARE) market is experiencing significant growth in Europe. Considering the strong research and development (R&D) capabilities of the European eyewear industry, it can emerge as a global market leader. In this context, the EU-funded POPULAR project will develop the first generic platform for ARE for a wide range of users and purposes. The eyewear will be designed to offer visual, wearable, vestibular, and social comfort, making it suitable for all-day use. POPULAR will focus on developing components like an ultra-low power micro-display, an innovative holographic lens mirror, and application software. It will also conduct end-user tests in outdoor sports, healthcare, and logistics use-case scenarios to ensure the effectiveness and usability of the developed prototypes.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Holographic mirror-based approach in augmented reality glasses || https://doi.org/10.1117/12.3029958
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Simulation tool for holographic-based augmented reality eyewear || https://doi.org/10.1117/12.3042612
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Augmented Reality Eyewear with ophthalmic correction for mainstream applications, overcoming acceptance barriers through Human Factors Plan || https://doi.org/10.54941/AHFE1005068
|-
| Healthcare, Medicine & Accessibility || Conference proceedings || Smart Glasses and Augmented Reality to Support Healthcare || https://doi.org/10.54941/AHFE1006205
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| AR Eyewear Simulation Tool || Simulation Tool || https://doi.org/10.1117/12.3042612 || A software simulation tool explicitly developed for holographic-based augmented reality eyewear.
|}

NEPTUN

2026-09-01T14:50:07Z

CollectiveIntelligenceAdmin:

=== NEPTUN Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101079398 || 01/11/2022 || 31/10/2025 || POLITECHNIKA GDANSKA / Poland
|}
=== Project description ===
Innovation is crucial for any and every industry. In the EU, innovation has driven the implementation of novel solutions. Unfortunately, some EU countries, like Poland, have not been completely successful at accelerating innovation and introducing new ideas. The EU-funded NEPTUN project, in cooperation with KTH Stockholm, TU Berlin and NTU Athens, will offer a solution. It utilises their experience in subjects like innovations in additive manufacturing, VR technology, and others, as well as their connections with multiple universities. They will help Poland and other EU countries to achieve innovative industrial sectors with research and production excellence.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Comparison of different optical measurement methods in the evaluation of the wear of SLS-fabricated tool used for free abrasive machining || https://doi.org/10.2139/SSRN.4844842
|-
| Robotics, Manufacturing & Industry 4.0 || Book chapters || UWB-Based Indoor Navigation in a Flexible Manufacturing System Using a Custom Quadrotor UAV || https://doi.org/10.1007/978-3-031-38241-3_11
|-
| Robotics, Manufacturing & Industry 4.0 || Book chapters || Project-Based Collaborative Research and Training Roadmap for Manufacturing Based on Industry 4.0 || https://doi.org/10.1007/978-3-031-38241-3_79
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || High performance eco-friendly free abrasive machining using an additively fabricated tool and PCD based slurry || https://doi.org/10.1038/S41598-025-16363-0
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Cyclic behaviour modelling of additively manufactured Ti-6Al-4V lattice structures || https://doi.org/10.1016/J.IJMECSCI.2024.109219
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Influence of the three-body abrasion kinematics on the surface characteristics of an SLS-fabricated tool during machining of ceramics || https://doi.org/10.1038/S41598-025-02692-7
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || An investigation of simple neural network models using smartphone signals for recognition of manual industrial tasks || https://doi.org/10.1038/S41598-025-06726-Y
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Application of 3D scanning and computer simulation techniques to assess the shape accuracy of welded components || https://doi.org/10.1007/S00170-024-14498-4
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Quality Evaluation of Small Features Fabricated by Fused Filament Fabrication Method || https://doi.org/10.3390/MA18030507
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || A Comparative Study of Precision Surface Grinding Using Additively Fabricated Acrylonitrile–Butadiene–Styrene (ABS) Wheels with Continuous and Serrated Working Surfaces || https://doi.org/10.3390/MA17235867
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Recent Research Progress in the Abrasive Machining and Finishing of Additively Manufactured Metal Parts || https://doi.org/10.3390/MA18061249
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || Robot digital twin systems in manufacturing: Technologies, applications, trends and challenges || https://doi.org/10.1016/J.RCIM.2025.103103
|-
| Robotics, Manufacturing & Industry 4.0 || Peer reviewed articles || The study on the appearance of deformation defects in the yacht lamination process using an ai algorithm and expert knowledge || https://doi.org/10.1038/S41598-024-56410-W
|}

NANOVR

2026-09-01T14:50:01Z

CollectiveIntelligenceAdmin:

=== NANOVR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/866559 || 01/05/2022 || 30/04/2027 || UNIVERSIDAD DE SANTIAGO DE COMPOSTELA / Spain
|}
=== Project description ===
As scientists have made progress engineering the structures of molecular systems at the nano-scale, a new fundamental challenge has emerged: namely, our ability to understand and engineer molecular dynamics and flexibility. Drawing on the state-of-the-art in high performance computing [HPC] and virtual reality [VR], the EU-funded NANOVR project will develop a new paradigm for nano-scale design, engineering, and simulation. The project team will develop an intuitive open-source framework which enables scientists to use VR-enabled interactive simulations for understanding complex molecular systems, which they will apply to understand important problems – for example the protein-ligand interactions required to tackle emerging strains of influenza. In so doing, we will obtain new insight into molecular flexibility, and accelerate molecular design across important domains spanning biochemistry, materials chemistry, & catalysis.

=== Project outputs ===
==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Martinize2 and Vermouth || Software Framework || https://doi.org/10.48550/arxiv.2212.01191 || A unified framework utilized for molecular topology generation.
|-
| NanoVer Server || Software Package || https://doi.org/10.21105/joss.08118 || A Python package for serving real-time multi-user interactive molecular dynamics in VR.
|}

MOTIVATE XR

2026-09-01T14:49:55Z

CollectiveIntelligenceAdmin:

=== MOTIVATE XR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135963 || 01/06/2024 || 31/05/2027 || MAGGIOLI SPA / Italy
|}
=== Project description ===
XR has the potential to revolutionize various industrial sectors by offering more engaging, secure, and inclusive training and assistance for complex tasks thus enabling more people to acquire the skills required to perform such tasks. However, the creation of such XR experiences is still overly complex, time consuming, and expensive thus blocking their wide adoption in industrial sectors that do not have the necessary expertise nor the resources to create and deploy them.The main objective of MOTIVATE XR is to create a world’s leading XR collaborative authoring, publishing, and experiencing tool suite for training and assistance to industrial operations such as the assembly, manufacturing, maintenance, and dismantlement, of industrial goods. This ground-breaking, open, tightly integrated, and highly interoperable solution will be designed for, and usable by a wide range of users without programming skills, from the largest European industrials to handywomen/handymen, without requiring software development skills. It will offer an end-to-end solution to streamline the whole authoring and experiencing workflow thanks to novel portable 3D scanning and digital twin modelling solutions, No-Code authoring approaches and ground-breaking XR experiencing tools, including a next-gen European XR smart headset, all assisted by the latest advances in Artificial Intelligence (AI). It will then evaluate its result in five complementary and ambitious pilots in different industrial sectors including aerospace, home appliance, aluminium, electric distribution, and hybrid human-robot industries. For this purpose, our project will involve a complementary group of the best-in-class European experts and leading industries adopting a user-centric methodology coordinated by an SSH expert to ensure proper consideration of societal, ethical, and legal issues and ethical use of XR and AI technologies.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Monocular RGB 6D object pose estimation for augmented reality: a survey || https://doi.org/10.1007/S10055-026-01315-4
|}

MEMENTOES

2026-09-01T14:49:48Z

CollectiveIntelligenceAdmin:

=== MEMENTOES Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101061496 || 01/10/2022 || 30/09/2025 || ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS / GREECE
|}
=== Project description ===
Harnessing technologies such as virtual and mixed reality to provide highly personal experiences that demonstrate empathy is becoming more widespread. The EU-funded MEMENTOES project will design three immersive video games each intended for a real (rather than virtual) museum. The museums are recognised internationally as Sites of Conscience – places of memory that remember and preserve even the most traumatic memories to allow visitors to make connections between the past and its power to create positive change. The games will address visitors’ demands and instil in the general public a greater appreciation for museums engaged in memorialisation – the process of creating public memorials – and transitional justice.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || AI Services for Generating Customizable Game Assets || https://doi.org/10.1109/ICIR64558.2024.10976973
|-
| Education, Training & Serious Games || Conference proceedings || Understanding User Experience in Serious Games: The Role of Narratives, Game Design and Player Background || https://doi.org/10.2312/DH.20253297
|-
| Education, Training & Serious Games || Conference proceedings || Serious Games Beyond Entertainment and Learning: An Evaluation Methodology for Assessing Awareness Raising, Empathy, and Social Change || https://doi.org/10.1007/978-3-031-76821-7_11
|-
| Education, Training & Serious Games || Conference proceedings || Promoting Positive Attitudes Through Narrative-Driven Digital Heritage Games || https://doi.org/10.2312/DH.20253327
|-
| Education, Training & Serious Games || Peer reviewed articles || Museum-Inspired Video Games as a Symbolic Transitional Justice Policy: Overview, Concepts, and Research Direction || https://doi.org/10.1145/365127
|-
| Education, Training & Serious Games || Peer reviewed articles || AI tools for generating Digital Heritage Twins enhancing storytelling in educational games || https://doi.org/10.1016/J.DAACH.2025.E00451
|-
| Ethics, Society, Arts & Culture || Conference proceedings || Remembering the Gulag with a Walking Simulator || https://doi.org/10.1109/ICIR64558.2024.10976896
|-
| Ethics, Society, Arts & Culture || Conference proceedings || A Video Game About Gulag Archaeology and the Memoirs of Women Prisoners || https://doi.org/10.1109/GEM61861.2024.10585492
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || An RL -Driven Adaptive Game Approach to Support Cultural Heritage Learning || https://doi.org/10.1111/JCAL.70156
|}

Meetween

2026-09-01T14:49:41Z

CollectiveIntelligenceAdmin:

=== Meetween Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135798 || 01/01/2024 || 31/12/2027 || TRANSLATED SRL / Rome, Italy
|}
=== Project description ===
In a world of increasing preoccupation with artefacts, interacting with our fellow human beings remains one of our most enjoyable, but also one of our practically most critical activities. We derive inspiration from each other, solve problems and chart our future together. Yet our interaction with fellow humans is far from seamless or frictionless: despite much greater world-wide reach, we suffer (perhaps more than ever) from isolation, barriers and separation due to language, culture, physical distances, time-zones, scheduling conflicts, and distractions to our attention. With greater freedom, reach and flexibility, our isolation and complexities also appear to increase. In our proposed project “Meetween”, we aim to find solutions to these problems. Rather than artificial intelligence (AI) getting in the way of the human experience, we harness its power to make human-human interaction more seamless and natural, eliminate language barriers, replace the techno-clutter with support. The project aims to 1) build the science-based technology solutions needed to power the next generation of videoconferencing platforms for Europe, to support smooth, engaging, barrier-free collaboration across languages; 2) exploit the all-round, integrated algorithmic capabilities offered by foundation models and self-supervised training on large datasets to nimbly adapt to participant context, cultural and regional specificities, including linguistic ones; 3) foster and facilitate business collaboration throughout the European Union by providing real-time machine-learning-powered speech-to-speech translation, summarization and virtual assistant services for online meetings; 4) defend a European vision for AI with regard to safety, privacy, social and ethical approaches, anchored in our regulations, data standards and shared initiatives and resources.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Audio, Speech & NLP || Conference proceedings || Prepending or Cross-Attention for Speech-to-Text? An Empirical Comparison || https://doi.org/10.18653/V1/2025.NAACL-LONG.153
|-
| Audio, Speech & NLP || Conference proceedings || What the Harm? Quantifying the Tangible Impact of Gender Bias in Machine Translation with a Human-centered Study || https://doi.org/10.18653/V1/2024.EMNLP-MAIN.1002
|-
| Audio, Speech & NLP || Conference proceedings || Findings of the Quality Estimation Shared Task at WMT 2024: Are LLMs Closing the Gap in QE? || https://doi.org/10.18653/V1/2024.WMT-1.3
|-
| Audio, Speech & NLP || Conference proceedings || FINDINGS OF THE IWSLT 2024 EVALUATION CAMPAIGN || https://doi.org/10.18653/V1/2024.IWSLT-1.1
|-
| Audio, Speech & NLP || Conference proceedings || NUTSHELL: A Dataset for Abstract Generation from Scientific Talks || https://doi.org/10.18653/V1/2025.IWSLT-1.2
|-
| Audio, Speech & NLP || Conference proceedings || StreamAtt: Direct Streaming Speech-to-Text Translation with Attention-based Audio History Selection || https://doi.org/10.18653/V1/2024.ACL-LONG.202
|-
| Audio, Speech & NLP || Conference proceedings || Decoupled Vocabulary Learning Enables Zero-Shot Translation from Unseen Languages || https://doi.org/10.5445/IR/1000174872
|-
| Audio, Speech & NLP || Conference proceedings || FBK@IWSLT Test Suites Task: Gender Bias evaluation with MuST-SHE || https://doi.org/10.18653/V1/2024.IWSLT-1.10
|-
| Audio, Speech & NLP || Conference proceedings || Speech Translation with Speech Foundation Models and Large Language Models: What is There and What is Missing? || https://doi.org/10.18653/V1/2024.ACL-LONG.789
|-
| Audio, Speech & NLP || Conference proceedings || SimulSeamless: FBK at IWSLT 2024 Simultaneous Speech Translation || https://doi.org/10.18653/V1/2024.IWSLT-1.11
|-
| Audio, Speech & NLP || Conference proceedings || Quality Estimation with $k$-nearest Neighbors and Automatic Evaluation for Model-specific Quality Estimation || https://doi.org/10.5445/IR/1000174743
|-
| Audio, Speech & NLP || Conference proceedings || From Speech to Summary: A Comprehensive Survey of Speech Summarization || https://doi.org/10.5445/IR/1000180972
|-
| Audio, Speech & NLP || Conference proceedings || Factorized-VITS: Decoupling Prosody and Text in End-to-End Speech Synthesis without External or Secondary Aligner || https://doi.org/10.1109/ICASSP49660.2025.10890003
|-
| Audio, Speech & NLP || Conference proceedings || MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation Model Training on EU Languages || https://doi.org/10.18653/V1/2024.EMNLP-MAIN.771
|-
| Audio, Speech & NLP || Conference proceedings || Optimizing Rare Word Accuracy in Direct Speech Translation with a Retrieval-and-Demonstration Approach || https://doi.org/10.48550/ARXIV.2409.09009
|-
| Audio, Speech & NLP || Peer reviewed articles || A decade of gender bias in machine translation || https://doi.org/10.1016/J.PATTER.2025.101257
|-
| Audio, Speech & NLP || Peer reviewed articles || How “Real” is Your Real-Time Simultaneous Speech-to-Text Translation System? || https://doi.org/10.1162/TACL_A_00740
|-
| Computer Vision, 3D Modeling & Rendering || Other || Facial Attribute Based Text Guided Face Anonymization || https://doi.org/10.48550/ARXIV.2505.21002
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Speech LMM open release - V1 || AI Model || https://huggingface.co/meetween/Llama-speechlmm-1.0-l || Open release of the Speech Large Multimodal Model (SpeechLMM) created by the project.
|-
| Mumospee open release - V1 || Dataset || https://huggingface.co/datasets/meetween/mumospee || One of the largest open multimodal datasets created to train the SpeechLMM.
|-
| MOSEL || Dataset || https://doi.org/10.18653/V1/2024.EMNLP-MAIN.771 || 950,000 hours of speech data utilized for open-source speech foundation model training on EU languages.
|-
| NUTSHELL || Dataset || https://doi.org/10.18653/V1/2025.IWSLT-1.2 || A dataset built specifically for abstract generation from scientific talks.
|-
| FAMA || Foundation Model || https://doi.org/10.48550/ARXIV.2505.22759 || The first large-scale open-science speech foundation model for Italian and English.
|}

MAX-R

2026-09-01T14:49:33Z

CollectiveIntelligenceAdmin:

=== MAX-R Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101070072 || 01/09/2022 || 28/02/2025 || UNIVERSIDAD POMPEU FABRA / Spain
|}
=== Project description ===
Extended reality has the potential to radically disrupt traditional media. The EU-funded MAX-R project aims to help develop new extended reality (XR) programming by creating new tools for generating, processing and delivering content in real time. The project’s software pipeline will use open APIs as well as open-file and data-transfer formats to encourage development and support the integration of new open-source and proprietary tools. MAX-R will also build on recent research and advances in virtual production to develop real-time processes to deliver enhanced interactivity and novel content based on media data.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Progressive Network Streaming of Textured Meshes in the Binary glTF 2.0 Format || https://doi.org/10.1145/3611314.3615907
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Large-Area Spatially Aligned Anchors || https://doi.org/10.1007/978-3-031-71707-9_3
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Tracking and Co-Location of Global Point Clouds for Large-Area Indoor Environments || https://doi.org/10.1007/S10055-024-01004-0
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Lessons Learned From a Large-Scale Virtual Reality Experience Over Wi-Fi || https://doi.org/10.1109/TON.2025.3582033
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Projector-camera calibration with non-overlapping fields of view using a planar mirror || https://doi.org/10.21203/RS.3.RS-4605720/V1
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Experimenting with Adaptive Bitrate Algorithms for Virtual Reality Streaming over Wi-Fi || https://doi.org/10.1145/3636534.3697322
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Vegvisir: A testing framework for HTTP/3 media streaming || https://doi.org/10.1145/3587819.3592550
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || HTTP/3's Extensible Prioritization Scheme in the Wild || https://doi.org/10.1145/3673422.3674887
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || PRoGS: Progressive Rendering of Gaussian Splats || https://doi.org/10.48550/ARXIV.2409.01761
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Responsive and Timely Virtual Reality Gaming: Which Frame Rate Should One Choose? || https://doi.org/10.1109/COG60054.2024.10645558
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Performance Evaluation of MLO for XR Streaming: Can Wi-Fi 7 Meet the Expectations? || https://doi.org/10.1109/CAMAD62243.2024.10943088
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Is Wi-Fi 6 Ready for Virtual Reality Mayhem? A Case Study Using One AP and Three HMDs || https://doi.org/10.36227/techrxiv.24230728.v1
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Cross that boundary: Investigating the feasibility of cross-layer information sharing for enhancing ABR decision logic over QUIC || https://doi.org/10.1145/3592473.3592563
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Experimental evaluation of interactive Edge/Cloud Virtual Reality gaming over Wi-Fi using unity render streaming || https://doi.org/10.1016/J.COMCOM.2024.08.001
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Data Hubs / XRDataHub || Open-Source Software || https://github.com/FilmakademieRnd/DataHub || Open-source software associated with XRDataHub, AnimHost, and browser-based XR tools.
|-
| EDM-Research/UE-LASAA || Software Code || https://doi.org/10.5281/zenodo.15517094 || Published code base developed to support the project's XR media pipelines.
|}

MASTER

2026-09-01T14:49:25Z

CollectiveIntelligenceAdmin:

== MASTER Project ==
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator !! Project website
|-
| https://cordis.europa.eu/project/id/101093079 || 01/01/2023 || 30/06/2026 || PANEPISTIMIO PATRON || https://www.master-xr.eu/project/
|}
=== Project description ===
The transition to Industry 4.0 required the adoption of new robotic and automation tools in its processes. The adoption of such tools requires that workers understand how to use and take advantage of them. Additionally, extended reality (XR) technologies have reached sufficient maturity to enter the domain of industrial applications and, among other things, support the training of operators. The EU-funded MASTER project will use XR tools to address the education challenges and create new training material to help operators learn and adapt to the new automation tools, boosting the XR ecosystem's capacity for training in robotics in manufacturing. The project will launch two Open Calls; the first will provide the XR platform with the necessary training tools and features to be enhanced by selected companies, while the second will test first-hand the platform and tools by creating training material

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Cross-Viewpoint Semantic Mapping: Integrating Human and Robot Perspectives for Improved 3D Semantic Reconstruction || https://doi.org/10.3390/s23115126
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || A review of machine learning in scanpath analysis for passive gaze-based interaction || https://doi.org/10.3389/frai.2024.1391745
|-
| Healthcare, Medicine & Accessibility || Conference proceedings || Interactive Fixation-to-AOI Mapping for Mobile Eye Tracking Data based on Few-Shot Image Classification || https://doi.org/10.1145/3581754.3584179
|-
| Healthcare, Medicine & Accessibility || Conference proceedings || IMETA: An Interactive Mobile Eye Tracking Annotation Method for Semi-automatic Fixation-to-AOI mapping || https://doi.org/10.1145/3581754.3584125
|}
==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| IMETA || Software Tool || https://doi.org/10.1145/3581754.3584125 || An interactive mobile eye-tracking annotation method for semi-automatic fixation-to-AOI mapping.
|}

LUMINOUS

2026-09-01T14:49:17Z

CollectiveIntelligenceAdmin:

=== LUMINOUS Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135724 || 01/01/2024 || 31/12/2026 || DFKI / Germany
|}
=== Project description ===
LUMINOUS aims at the creation of the next generation of Language Augmented XR systems, where natural language-based communication and Multimodal Large Language Models (MLLM) enable adaptation to individual, not predefined user needs and unseen environments. This will enable future XR users to interact fluently with their environment, while having instant access to constantly updated global as well as domain- specific knowledge sources to accomplish novel tasks. We aim to exploit MLLMs injected with domain specific knowledge for describing novel tasks on user demand. These are then communicated through a speech interface and/or a task adaptable avatar (e.g. coach/teacher) in terms of different visual aids and procedural steps for the accomplishment of the task. Language driven specification of the style, facial expressions, and specific attitudes of virtual avatars will facilitate generalisable and situation-aware communication in multiple use cases and different sectors. LLMs will benefit in parallel in identifying new objects that were not part of their training data and then describing them in a way that they become visually recognizable. Our results will be prototyped and tested in three pilots, focussing on neurorehabilitation (support of stroke patients with language impairments), immersive industrial safety training, and 3D architectural design review. A consortium of six leading R&D institutes experts in six different disciplines (AI, Augmented Vision, NLP, Computer Graphics, Neurorehabilitation, Ethics) will follow a challenging workplan, aiming to bring about a new era at the crossroads of two of the most promising current technological developments (LLM/AI and XR), made in Europe.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Next Generation XR Systems—Large Language Models Meet Augmented and Virtual Reality || https://doi.org/10.1109/MCG.2025.3548554
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Vision-Language Models Struggle to Align Entities across Modalities || https://doi.org/10.18653/V1/2025.FINDINGS-ACL.965
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Sparse Semi-DETR: Sparse Learnable Queries for Semi-Supervised Object Detection || https://doi.org/10.1109/CVPR52733.2024.00558
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || PixT3: Pixel-based Table-To-Text Generation || https://doi.org/10.18653/V1/2024.ACL-LONG.364
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content Creation || https://doi.org/10.1109/CVPR52734.2025.00759
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Compact 3D Scene Representation via Self-Organizing Gaussian Grids || https://doi.org/10.1007/978-3-031-73013-9_2
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Realtime-Rendering of Dynamic Scenes with Neural Radiance Fields || https://doi.org/10.1109/VRW66409.2025.00345
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Improving Adaptive Density Control for 3D Gaussian Splatting || https://doi.org/10.5220/0013308500003912
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Gaussian Splatting Decoder for 3D-aware Generative Adversarial Networks || https://doi.org/10.1109/CVPRW63382.2024.00794
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Multi-Resolution Generative Modeling of Human Motion from Limited Data || https://doi.org/10.1145/3697294.3697309
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || 3DGS.zip: A survey on 3D Gaussian Splatting Compression Methods || https://doi.org/10.1111/CGF.70078
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Text2CAD || AI Model || https://luminous-horizon.eu/index.php/blogs/introducing-text2cad-revolutionizing-cad-generation-from-text-prompts-for-next-gen-xr-in-luminous/ || A generative model capable of producing sequential CAD designs from text prompts.
|-
| MARVEL-40M+ || AI Model / Framework || https://doi.org/10.1109/CVPR52734.2025.00759 || A multi-level visual elaboration framework designed for high-fidelity text-to-3D content creation.
|}

INDUX-R

2026-09-01T14:49:09Z

CollectiveIntelligenceAdmin:

=== INDUX-R Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135556 || 01/01/2024 || 31/12/2026 || ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS / GREECE
|}
=== Project description ===
In an intriguing historical twist, Joseph von Fraunhofer’s once-secret optics work contrasts with today’s dominance of non-European players in industrial extended reality (XR). With this in mind, the EU-funded INDUX-R project aims to revolutionise Europe’s XR industry. Facing fragmentation and investment challenges, INDUX-R proposes a human-centric XR ecosystem, empowering users and fostering innovation. It focuses on core XR technologies and addresses multi-user challenges with scalable 5G architecture and secure IoT networks. With diverse applications from event planning to virtual medical training, INDUX-R emphasises user involvement and ethical development, aligning technological progress with European values. By bridging scientific breakthroughs and real-world needs, INDUX-R aims to reshape European industries and societal norms.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Peer reviewed articles || Time-Series Forecasting in Industrial Environments: A Performance Study and a Novel Late Fusion Framework || https://doi.org/10.1109/JSEN.2025.3526362
|-
| Audio, Speech & NLP || Conference proceedings || INTERSPEECH 2009 Emotion Challenge Revisited: Benchmarking 15 Years of Progress in Speech Emotion Recognition || https://doi.org/10.21437/INTERSPEECH.2024-97
|-
| Audio, Speech & NLP || Conference proceedings || Enrolment-based personalisation for improving individual-level fairness in speech emotion recognition || https://doi.org/10.48550/ARXIV.2406.06665
|-
| Audio, Speech & NLP || Peer reviewed articles || Audio Enhancement for Computer Audition—An Iterative Training Paradigm Using Sample Importance || https://doi.org/10.48550/ARXIV.2408.06264
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Overcoming occlusions in AR, via multi-view, real-time 3D human pose estimation || https://doi.org/10.1007/S00138-025-01783-9
|}

HXR

2026-09-01T14:49:03Z

CollectiveIntelligenceAdmin:

=== HXR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101145548 || 01/03/2024 || 31/10/2025 || SWAVE / Belgium
|}
=== Project description ===
Lifelike 3D images (holograms) have the potential to revolutionize key sectors, such as manufacturing, healthcare, consumer electronics, and creative industries. However, it has not yet been possible to create usable holographic displays for commercial applications due to the low visual quality of digital holograms and the very limited field of view of holographic projections. Swave is developing HXR, the world’s first spatial light modulator specifically designed for digital holography. Our proprietary technology will be commercialized as a novel chipset with supporting systems and algorithms, capable of generating and displaying high-fidelity dynamic holographic imagery. HXR will enable display manufacturers to create immersive, ultra-high resolution holographic displays, disrupting visualization markets forecast to grow to >€100bn by 2030. Swave is a spin-off from IMEC, leveraging 12+ years of research and a team with 100+ years of experience in bringing semiconductor/imaging products to market.

HEAT

2026-09-01T14:48:57Z

CollectiveIntelligenceAdmin:

=== HEAT Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101135637 || 01/06/2024 || 31/05/2027 || UNIVERSITA DEGLI STUDI DI CAGLIARI / Italy
|}
=== Project description ===
Hybrid Extended reAliTy (HEAT) is born to pave the way for the next-generation distributed experiences by addressing major challenges to make those experiences that up to now could only be in our imagination: being realistically immersed (holo-ported) within real captured omnidirectional and navigable hyper-realistic 3D spaces, feeling their atmosphere, and sharing these experiences with others, regardless of their location. The aim of this proposal is to integrate immersive media technologies such as point cloud/holographic imaging, multi-sensorial media, Social VR in a multi-user, feedback-enabled communication system to provide the construction of compelling context-aware and embodied experiences for innovative hybrid XR applications, where remote users can experience a real captured environment through immersive VR, while in presence users can visualise and interact with the holograms of remote users integrated in the real environment through holographic rendering. The system will aim at facilitating the exploitation of agile (multi-sensory) 3D data acquisition techniques, enhancing performance while reducing technology costs. It will create a scalable communication pipeline embodying either encapsulation of different media from classical audio-video to multisensorial to holographic video or a combination of them, providing means for efficient and scalable encoding, processing, storage, (real-time) streaming and rendering. In such a way, the system will allow users to provide/exploit the features according to the acquisition/rendering system available. The project will provide well designed and fully tested scenarios in real-world environments for enhanced XR experiences: a blended learning, a modern theatre act, a music festival and an opera show. All pilot actions will ensure that GDPR and ethics are addressed for end-users (privacy and ethics by design methodology).

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || Forecasting Ethereum Prices with Machine Learning, Deep Learning, and Explainable Artificial Intelligence Using Multi-source Market Articles and Hybrid Sentiment Analysis || https://doi.org/10.1007/978-3-032-04339-9_12
|-
| AI, Machine Learning & Data Science || Conference proceedings || Pixelating to the Edge: Generative AI Art on Edge Devices || https://doi.org/10.1109/BMSB65076.2025.11165718
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Low-Complexity Patch-Based No-Reference Point Cloud Quality Metric Exploiting Weighted Structure and Texture Features || https://doi.org/10.48550/ARXIV.2503.15001
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || CNN-Based 360° Scene Recognition for Automatic Generation of Omnidirectional Scent Effects || https://doi.org/10.1109/TMM.2025.3618574
|-
| Ethics, Society, Arts & Culture || Conference proceedings || Proxemic Behavior in a Multi-User Virtual Reality Experience for Multilingual Cultural Heritage Education || https://doi.org/10.1109/ISPA66905.2025.11259464
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Immersive Live Concert: A Multi-Sensory Experience Based on Real-Time Lyrics Detection from Spatial Audio Data || https://doi.org/10.5753/IMXW.2025.1139
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Social eXtended Reality (XR) and Virtual Production: Toward New Engaging Immersive Experiences || https://doi.org/10.1145/3706370.3731642
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Immersive Application for Real-Time Interactive Music Performances Using Spatial Audio || https://doi.org/10.1109/BMSB65076.2025.11165553
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Live Feedback for Immersive Music Performances - A Case Study || https://doi.org/10.5753/IMXW.2025.8520
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || aDapT-XR: Adaptive Data Allocation and Prioritization for Synchronizing Real and Virtual Worlds in XR Digital Twins || https://doi.org/10.1109/BMSB65076.2025.11165558
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || EmoLoop: A Bi-Directional System for Emotion-Driven Interaction Between Remote Audiences and Live Performers || https://doi.org/10.1109/IS264627.2025.11284604
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || A Fast Volumetric Capture and Reconstruction Pipeline for Dynamic Point Clouds and Gaussian Splats || https://doi.org/10.1145/3756863.3769713
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || An Architecture for Real-Time Interactive Music Performances || https://doi.org/10.1109/MEDCOMNET65822.2025.11103534
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Enhancing XR Theatre with Remote Scent Delivery Using Audio Speech Recognition and Convolutional Neural Network-Based Scene Detection || https://doi.org/10.1109/IS264627.2025.11284558
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Social eXtended Reality (XR) and Virtual Production: Crafting New Frontiers in Immersive Storytelling || https://doi.org/10.5753/IMXW.2025.1505
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Toward Interactive and Distributed Hybrid Extended Reality Experiences || https://doi.org/10.1145/3672406.3672424
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Social VR with multi-user holo-portation: toward a new medium for rich interactive shared media consumption || https://doi.org/10.1109/BMSB65076.2025.11165698
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || Social VR With Holographic Comms: Enablers for New Engaging Experiences Within the TV / Video Consumption Landscape || https://doi.org/10.1109/TBC.2025.3570869
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Collaborative 360-Degree Video Streaming: A Multi-User Synchronization Solution with Socket.IO || https://doi.org/10.1109/BMSB65076.2025.11165535
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Estimating Quality of Experience in Multicast Point Cloud Streaming over 5G Networks || https://doi.org/10.1109/BMSB65076.2025.11165660
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || Mass Live and Interactive Multi-Cam VR360 Experiences as an Immersive Parallel Window to TV Broadcast Shows || https://doi.org/10.1109/BMSB65076.2025.11165554
|-
| Networks, Cloud & Telecommunications (5G/6G) || Conference proceedings || QoE-aware ML models based on network parameters for video streaming over 5G O-RAN architecture || https://doi.org/10.1109/BMSB65076.2025.11165626
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Utility-Aware Adaptive Streaming of Segmented Holographic Video Over Wireless Networks: A Knapsack-Theoretic Approach || https://doi.org/10.1109/JIOT.2025.3605830
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || Quality and Energy-Aware Cooperative Distributed Solution for Mobile Rich Media Delivery in Wireless Heterogeneous Environments || https://doi.org/10.1109/TBC.2025.3609056
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || A UAV-Centric Improved Soft Actor-Critic Algorithm for QoE-Focused Aerial Video Streaming || https://doi.org/10.1109/TVT.2024.3396349
|-
| Networks, Cloud & Telecommunications (5G/6G) || Peer reviewed articles || A Live Adaptive Streaming Solution for Enhancing Quality of Experience in Co-Created Opera || https://doi.org/10.1109/TBC.2025.3541875
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| EmoLoop || System / Software || https://doi.org/10.1109/IS264627.2025.11284604 || A bi-directional system designed for emotion-driven interaction between remote audiences and performers.
|}

GuestXR

2026-09-01T14:48:49Z

CollectiveIntelligenceAdmin:

=== GuestXR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101017884 || 01/01/2022 || 31/12/2025 || FUNDACIO EURECAT / Spain
|}
=== Project description ===
User content often stimulates antisocial interaction and abuse, representing a threat to vulnerable adults, teenagers and children. The EU-funded GuestXR project intends to develop a socially interactive multisensory platform system that uses extended reality – virtual and augmented – as a vehicle to connect people for immersive, synchronous face to face interaction with positive social results. The project will introduce a critical innovation consisting of the intervention of artificial agents that learn over time to assist the virtual social gathering in realising its purposes. This agent, ‘The Guest’, will exploit machine learning to enable the meeting towards specific results. The project will rely on neuroscience and social psychology research on group behaviour to deliver rules to agent based models.

=== Project outputs ===
==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Motivational Interviewing Transcripts Annotated || Dataset || https://doi.org/10.5281/zenodo.12792623 || Annotated transcripts used for training AI-generated patient simulations.
|-
| MB-RIRs: a Synthetic Room Impulse Response Dataset || Dataset || https://doi.org/10.48550/arxiv.2507.09750 || Synthetic room impulse responses featuring frequency-dependent absorption coefficients.
|-
| Inceptor || Open-Source Tool || https://doi.org/10.1109/vrw58643.2023.00102 || An open-source tool developed for the automated creation of 3D social scenarios in virtual environments.
|-
| Topo-Speech || Sensory System || https://doi.org/10.3389/fnhum.2022.1058093 || A sensory substitution system conveying spatial information to blind and vision-impaired individuals.
|}

FLUAR

2026-09-01T14:48:42Z

CollectiveIntelligenceAdmin:

=== FLUAR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/190144382 || 01/04/2023 || 31/03/2025 || ARSPECTRA S.A.R.L.
|}
=== Project description ===
Fluorescence-guided surgery (FGS) uses near-infrared (NIR) sensors to detect and display fluorescent biomarkers indicating the exact location of tumors. But the current cameras and monitors force surgeons to match the images to the body via subjective comparisons. This long, error-prone process reduces the accuracy, and increases operating times and cost. This is a critical problem in cancer surgery where complete tumor removal is key to prevent recurrence, e.g. a yearly incidence of <0.5 M breast cancer patients requires over 2.8 M surgeries. FLUAR are novel augmented reality (AR) glasses with integrated high-end NIR sensors and computer vision algorithms. They detect and display the fluorescent biomarkers in the surgeons’ direct sight, hence show the tumor margins on the target. FLUAR will increase the surgeons’ accuracy and reduce tumor removal times. This project aims to finalize and validate FLUAR’s technical developments and clinical usability according to end-user requirements.

EXPERIENCE

2026-09-01T14:48:36Z

CollectiveIntelligenceAdmin:

=== EXPERIENCE Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101017727 || 01/01/2021 || 30/06/2025 || UNIVERSITA DI PISA
|}
=== Project description ===
In recent years, virtual reality (VR) has found more commercial applications and larger market share. However, VR still holds great potential to enhance interaction and expression. The EU-funded EXPERIENCE project seeks to use VR to enhance daily life by allowing brand new ways of social interaction and personal expression. It will develop the technology required to help users easily create and manipulate their own unique VR environments, significantly improving their virtual experiences. The goal is to bring VR into areas such as mental health treatment, entertainment and education, promoting VR as a means of significantly improving the human experience.

=== Project outputs ===
==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| 4Ward || Algorithm / Software || https://doi.org/10.1016/j.neucom.2023.127058 || A relayering strategy designed for the efficient training of arbitrarily complex directed acyclic graphs.
|-
| Virtual Experience Toolkit || Software Framework || https://doi.org/10.3390/s24123837 || An end-to-end automated 3D scene virtualization framework using computer vision techniques.
|}

EO4EU

2026-09-01T14:48:30Z

CollectiveIntelligenceAdmin:

=== EO4EU Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101060784 || 01/06/2022 || 31/05/2025 || ETHNIKO KAI KAPODISTRIAKO PANEPISTIMIO ATHINON / Greece
|}
=== Project description ===
Vast amounts of data are produced each day and become available via various channels, significantly enhancing our lives. The EU-funded EO4EU project will focus on Earth observation (EO) data, aiming to make it accessible to a larger audience, from professionals to citizens. To that end, it will deliver a set of advanced tools and methods leveraging AI and the FAIR data principles that will bridge the gap between domain experts and end users, encouraging wider EO data exploitation. Serverless data processing will further boost the EO data market, allowing comprehensible information modelling for a broad range of data.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Other || Enhancing Kubernetes Resilience through Anomaly Detection and Prediction || https://doi.org/10.48550/ARXIV.2503.14114
|-
| AI, Machine Learning & Data Science || Other || Earth Observation Data Management: A Knowledge Graph-Based Approach || https://doi.org/10.1007/978-981-97-8598-8_4
|-
| Cybersecurity, Privacy & Blockchain || Conference proceedings || An Unsupervised Anomaly-Based Detection System for Microservices Applications on Kubernetes || https://doi.org/10.1109/ISORC65339.2025.00032
|-
| Earth Observation, Environment & Smart Cities || Book chapters || EO4EU - AI-augmented ecosystem for Earth Observation data accessibility with Extended reality User Interfaces for Service and data exploitation || https://doi.org/10.2777/167982
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Copernicus data and services uptake with EO4EU platform: an AI-augmented ecosystem for Earth Observation data accessibility and exploitation. || https://doi.org/10.5194/EGUSPHERE-EGU25-10683
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Environmental plague monitoring : Desert Locust prediction with artificial intelligence and stochastic model || https://doi.org/10.5194/EGUSPHERE-EGU25-1720
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Land cover and management factor in soil erosion assessments: where do we stand and where are we going? || https://doi.org/10.5194/EGUSPHERE-EGU25-15855
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Assessing Associations Between Pollen Resilience Index Forecast Values and Allergic Health Symptoms Induced by Aeroallergens || https://doi.org/10.5194/EGUSPHERE-EGU25-12519
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Horizon projects using environmental observations and artificial intelligence for the benefit of science and society || https://doi.org/10.2777/167982
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Simplifying EO Application Development Through A Domain Specific Language || https://doi.org/10.1109/IGARSS53475.2024.10641829
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || A Replicable Multi-Cloud Automation Architecture for Earth Observation || https://doi.org/10.5194/EGUSPHERE-EGU24-1857
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Earth Observation Data Management: A Knowledge Graph-Based Approach || https://doi.org/10.1007/978-981-97-8598-8_4
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || EO4EU - AI-augmented ecosystem for Earth Observation data accessibility with Extended reality User Interfaces for Service and data exploitation || https://doi.org/10.5194/EGUSPHERE-EGU23-5038
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || EO4EU - AI-augmented ecosystem for Earth Observation data accessibility with Extended reality User Interfaces for Service and data exploitation || https://doi.org/10.2760/46796
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || EO4EU: AI-augmented ecosystem for EO data accessibility with XR User Interfaces for Service and Data Exploitation || https://doi.org/10.5446/58269
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || EuroGEO 2024 Poster: EO4EU - AI-augmented ecosystem for Earth Observation data accessibility with Extended reality User Interfaces for Service and data exploitation || https://doi.org/10.5281/zenodo.15020161
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Machine Learning tools and systems support for EO data processing and applications (OEMC Workshop) || https://doi.org/10.2760/45471
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || EO4EU - AI-augmented ecosystem for Earth Observation data accessibility with Extended reality User Interfaces for Service and data exploitation || https://doi.org/10.5194/egusphere-egu23-5038
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || EuroGEO 2022 Poster: EO4EU: AI-augmented ecosystem for EO data accessibility with XR User Interfaces for Service and Data Exploitation || https://doi.org/10.5281/zenodo.7970986
|-
| Earth Observation, Environment & Smart Cities || Conference proceedings || Environmental plague monitoring: desert locust prediction with artificial intelligence and stochastic model || https://doi.org/10.5281/zenodo.15020363
|-
| Earth Observation, Environment & Smart Cities || Other || Enhancing EO Data Accessibility: Policy Recommendations and Insights from EO4EU Platform || https://doi.org/10.5281/ZENODO.15011162
|-
| Earth Observation, Environment & Smart Cities || Peer reviewed articles || Simulation of climate change and thinning effects on Central European beech forests using 3-PGmix || https://doi.org/10.1007/S10342-025-01851-9
|-
| Earth Observation, Environment & Smart Cities || Peer reviewed articles || European pollen reanalysis, 1980–2022, for alder, birch, and olive || https://doi.org/10.1038/S41597-024-03686-2
|-
| Earth Observation, Environment & Smart Cities || Peer reviewed articles || Monthly to seasonal rainfall erosivity over Italy: Current assessment by empirical model and future projections by EURO-CORDEX ensemble || https://doi.org/10.1016/J.CATENA.2023.106943
|-
| Earth Observation, Environment & Smart Cities || Peer reviewed articles || Enhancing precision in coastal dunes vegetation mapping: ultra-high resolution hierarchical classification at the individual plant level || https://doi.org/10.1080/01431161.2024.2354135
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || MASK-air: An OECD (Organisation for Economic Co-operation and Development) Best Practice for Public Health on Integrated Care for Chronic Diseases || https://doi.org/10.1016/J.JAIP.2024.03.024
|-
| Healthcare, Medicine & Accessibility || Peer reviewed articles || Changes in pollen season duration and their relationship with meteorological conditions in Lithuania || https://doi.org/10.1016/J.AEAOA.2025.100397
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| European pollen reanalysis, 1980-2022, for alder, birch, and olive, v.1.1 || Dataset || https://doi.org/10.1038/S41597-024-03686-2 || An extensive dataset providing pollen reanalysis (alder, birch, and olive) across Europe.
|}

E-DIPLOMA

2026-09-01T14:48:22Z

CollectiveIntelligenceAdmin:

=== e-DIPLOMA Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator
|-
| https://cordis.europa.eu/project/id/101061424 || 01/09/2022 || 31/08/2025 || UNIVERSITAT JAUME I DE CASTELLON / SPAIN
|}
=== Project description ===
The COVID-19 pandemic placed students and teachers online. Now the question is how to improve and enhance the quality of distance learning experiences. While the shift to online learning during the pandemic was sudden, it was unavoidable. It also exposed the many challenges, such as inadequate technology infrastructure, lack of training for teachers and limited access to technology for some students. In this context, the EU-funded e-DIPLOMA project will revolutionise e-learning by integrating emerging technologies such as augmented reality/virtual reality, artificial intelligence, interactive technologies, chatbots, and gamification into a newly designed e-learning platform. Adopting a co-creation methodology, the project will involve teachers, educators, pupils, families, course providers, and policymakers with the aim to create inclusive, accessible and sustainable e-learning practices.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| Audio, Speech & NLP || Book chapters || NLP-Assisted Educational Memory Game Experiment || https://doi.org/10.1007/978-3-031-42134-1_6
|-
| Education, Training & Serious Games || Book chapters || Gaps in Tertiary Education Institutions to Facilitate Practice-Based E-Learning with Disruptive Learning Technologies || https://doi.org/10.1007/978-3-031-84170-5
|-
| Education, Training & Serious Games || Book chapters || Puzzle Playground – Teaching VR Interactions Through a Puzzle Game || https://doi.org/10.1007/978-3-031-78269-5_39
|-
| Education, Training & Serious Games || Book chapters || The e-DIPLOMA Platform: A Cloud-Based Solution for Educational Groupwork in Gamified Environments || https://doi.org/10.1007/978-3-031-84170-5_4
|-
| Education, Training & Serious Games || Conference proceedings || INTERACTIVITY AND SCAFFOLDING IN PRACTICE BASED LEARNING WITH DISRUPTIVE TECHNOLOGIES || https://doi.org/10.21125/INTED.2024.0819
|-
| Education, Training & Serious Games || Conference proceedings || Predicting Student Performance with Virtual Resources Interaction Data || https://doi.org/10.1007/978-3-031-34111-3_39
|-
| Education, Training & Serious Games || Other || e-DIPLOMA - Deliverable 7.1: Report on Mapping Legal and Ethical Considerations || https://doi.org/10.5281/ZENODO.10259758
|-
| Education, Training & Serious Games || Other || Electronic, Didactic and Innovative Platform for Learning based On Multimedia Assets || https://doi.org/10.5281/ZENODO.17465663
|-
| Education, Training & Serious Games || Other || e-DIPLOMA: Aprendiendo a programar en entornos inmersivos || https://doi.org/10.5281/ZENODO.17465560
|-
| Education, Training & Serious Games || Other || e-DIPLOMA Deliverable 2.2 e-learning ecosystem for practice based learning with disruptive technologies || https://doi.org/10.5281/ZENODO.8406119
|-
| Education, Training & Serious Games || Other || e-DIPLOMA - Deliverable 4.2: Platform Software || https://doi.org/10.5281/ZENODO.14534383
|-
| Education, Training & Serious Games || Other || e-DIPLOMA Deliverable 4.1 Platform technology specification || https://doi.org/10.5281/ZENODO.8406053
|-
| Education, Training & Serious Games || Other || e-DIPLOMA - Deliverable 6.1: Report of current policy situation and policy recommendation || https://doi.org/10.5281/ZENODO.10390984
|-
| Education, Training & Serious Games || Other || e-DIPLOMA: Deliverable 5.2: Definition of appropriate metrics for the assessment of learning competencie || https://doi.org/10.5281/ZENODO.14535619
|-
| Education, Training & Serious Games || Other || e-DIPLOMA - Deliverable 5.1: Competency Specifications || https://doi.org/10.5281/ZENODO.14535523
|-
| Education, Training & Serious Games || Other || e-DIPLOMA - Dataset: European remote e-learning ecosystem survey data || https://doi.org/10.5281/ZENODO.10432816
|-
| Education, Training & Serious Games || Other || e-DIPLOMA: Initial analysis conclusions of the e-learning ecosystem for practice-based learning with disruptive technologies || https://doi.org/10.5281/ZENODO.8321110
|-
| Education, Training & Serious Games || Other || Development of an Immersive Virtual Reality System to Practice the Lumbar Puncture Manoeuvre || https://doi.org/10.1007/978-3-031-42134-1_10
|-
| Education, Training & Serious Games || Peer reviewed articles || Which videos are better for the students? Analyzing the student behavior and video metadata || https://doi.org/10.1016/J.HELIYON.2024.E39682
|-
| Education, Training & Serious Games || Peer reviewed articles || Towards the Adoption of Recommender Systems in Online Education: A Framework and Implementation || https://doi.org/10.3390/BDCC9100259
|-
| Education, Training & Serious Games || Peer reviewed articles || Immersive Virtual-Reality System for Aircraft Maintenance Education: A Case Study || https://doi.org/10.3390/app13085043
|-
| Ethics, Society, Arts & Culture || Conference proceedings || ETHICAL CONSIDERATIONS FOR CONDUCTING RESEARCH WITH VIRTUAL REALITY IN EDUCATION: ESTABLISHING REQUIREMENTS FOR CONSENT FORMS || https://doi.org/10.21125/ICERI.2023.1298
|-
| Ethics, Society, Arts & Culture || Other || e-DIPLOMA - Deliverable 1.3: Data Management Plan || https://doi.org/10.5281/ZENODO.10390670
|-
| Ethics, Society, Arts & Culture || Other || e-DIPLOMA - Deliverable 6.2 Report on the SWOT || https://doi.org/10.5281/ZENODO.10259900
|-
| Ethics, Society, Arts & Culture || Other || e-DIPLOMA: Baselines for the framework development of co-creation || https://doi.org/10.5281/ZENODO.8321129
|-
| Ethics, Society, Arts & Culture || Other || e-DIPLOMA - Deliverable 8.2: Project Website, Logo and Social Networks accounts || https://doi.org/10.5281/ZENODO.10259198
|-
| Ethics, Society, Arts & Culture || Other || e-DIPLOMA - Deliverable 7.2: Ethics Plan || https://doi.org/10.5281/ZENODO.10370507
|-
| Ethics, Society, Arts & Culture || Other || e-DIPLOMA - Deliverable 7.3: Sociocultural Contextualization Policy || https://doi.org/10.5281/ZENODO.10390253
|-
| Ethics, Society, Arts & Culture || Other || e-DIPLOMA - Deliverable 8.4: Business strategy baseline || https://doi.org/10.5281/ZENODO.10259081
|-
| Ethics, Society, Arts & Culture || Other || Exploring Value and Ethical Dimensions of Disruptive Technologies for Learning and Teaching || https://doi.org/10.1007/978-3-031-42134-1_11
|-
| Ethics, Society, Arts & Culture || Other || Balancing Innovation and Responsibility: The e-DIPLOMA Project's Approach to Ethical, Inclusive, Accessible, and Sustainable Research. || https://doi.org/10.5281/zenodo.8123835
|-
| Extended Reality (VR/AR/MR) & HCI || Peer reviewed articles || IEEE Access || https://doi.org/10.1109/ACCESS.2025.3578769
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| European remote e-learning ecosystem survey data || Dataset || https://doi.org/10.5281/ZENODO.10432816 || Survey data detailing the remote e-learning ecosystem across Europe.
|-
| e-DIPLOMA Platform Software || Software / Platform || https://doi.org/10.5281/ZENODO.14534383 || A complex package of cooperating software modules for the e-DIPLOMA learning ecosystem.
|-
| Photogrammetry workflow for low-polygon 3D models || Workflow / Tool || https://repositori.uji.es/bitstreams/578c3673-2fd3-40e8-aac6-483cb08eacf8/download (PDF File) || A reusable workflow relying on free software to obtain low-polygon 3D models.
|}

DIDYMOS-XR

2026-09-01T14:48:14Z

CollectiveIntelligenceAdmin:

=== DIDYMOS-XR Project ===
{| class='wikitable' style='margin:auto'
|-
! CORDIS Reference !! Start date !! End date !! Coordinator !! Project website
|-
| https://cordis.europa.eu/project/id/101092875 || 01/01/2023 || 31/12/2025 || JOANNEUM / Austria || https://didymos-xr.eu/
|}
=== Project description ===
The digital transformation and the availability of more diversified and cost-effective means for 3D capture have led to the creation of digital twins also for physical environments. Based on such digital twins, various applications could be built using real-time data from real-world environments, serving as a blueprint for smart cities and for improving performance and efficiency across industries. Currently, creating high-fidelity digital twins is costly, and their update requires manual intervention. Furthermore, data integration from heterogeneous sensors is challenging. The EU-funded DIDYMOS-XR project will implement technology to create improved large-scale digital twins, synchronised with the real world. DIDYMOS-XR will investigate and develop methods for data reconstruction and mapping from heterogeneous inputs, including static and mobile sensors, AI-based data fusion, scene understanding and rendering.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
|-
| AI, Machine Learning & Data Science || Conference proceedings || Perception for Connected Autonomous Vehicles under Adverse Weather Conditions || https://doi.org/10.1109/IROS58592.2024.10801295
|-
| AI, Machine Learning & Data Science || Conference proceedings || User-Centric Evaluation Methods for Digital Twin Applications in Extended Reality || https://doi.org/10.1109/AIXVR63409.2025.00028
|-
| AI, Machine Learning & Data Science || Conference proceedings || MGSO: Monocular Real-Time Photometric SLAM with Efficient 3D Gaussian Splatting || https://doi.org/10.48550/ARXIV.2409.13055
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || HINT-3D: Human-in-the-Loop Interactive Test-Time Adaptation for 3D Segmentation || https://doi.org/10.5281/ZENODO.18491843
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Deep 3D Geometric Saliency Estimation from Light Field Images || https://doi.org/10.1109/DSP58604.2023.10167953
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || HAME-NeRF: High Accuracy Mesh Extraction Leveraging Neural Radiance Fields || https://doi.org/10.1007/978-3-032-04968-1_28
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Visual Localization in Complex Environments: Merging Traditional Geometry with Learning-Based Techniques || https://doi.org/10.1109/AIXVR63409.2025.00022
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Volumetric Video Reconstruction and Communications: Toward a New Era of Interactive and Immersive Social Virtual Reality (VR) Experiences || https://doi.org/10.1145/3672406.3672421
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Training a Segmentation-Based Visual Anonymization Service for Street Scenes || https://doi.org/10.1007/978-981-96-2074-6_26
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || GDNeRF: Generalizable Depth-based NeRF for sparse view synthesis || https://doi.org/10.1109/ICME59968.2025.11209482
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || HAL-NeRF: High Accuracy Localization Leveraging Neural Radiance Fields || https://doi.org/10.1109/AIXVR63409.2025.00024
|-
| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Leveraging Anisotropic Error for Robust Point Cloud Registration || https://doi.org/10.1109/DSP65409.2025.11074865
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Urban scene removal and completion || https://doi.org/10.3233/FAIA250603
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Visual localization using implicit representations and particle filtering-based pose refinement || https://doi.org/10.5281/ZENODO.18468790
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || ExpPoint-MAE: Better Interpretability and Performance for Self-Supervised Point Cloud Transformers || https://doi.org/10.1109/ACCESS.2024.3388155
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Interactive digital twins enabling responsible extended reality applications || https://doi.org/10.1038/S41598-025-17855-9
|-
| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || MaskUno: Switch-Split Block For Enhancing Instance Segmentation || https://doi.org/10.48550/ARXIV.2407.21498
|-
| Ethics, Society, Arts & Culture || Conference proceedings || Digital Twins for Extended Reality Tourism: User Experience Evaluation Across User Groups || https://doi.org/10.1007/978-3-031-97769-5_3
|-
| Ethics, Society, Arts & Culture || Peer reviewed articles || Reimagining Historical Exploration: Multi-User Mixed Reality Systems for Cultural Heritage Sites || https://doi.org/10.3390/APP15052854
|-
| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Cooperative Perception for Digital Twin Reconstruction* || https://doi.org/10.1109/AIXVR63409.2025.00023
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
|-
| Dataset for Learning Scene Semantics from Vehicle-centric Data for City-scale Digital Twins || Dataset || https://ieeexplore.ieee.org/document/10859207 || Data utilized for learning scene semantics intended for city-scale digital twins.
|-
| ADAPT JR-Sim2Real dataset || Dataset || https://zenodo.org/records/12805642 || Dataset associated with domain transfer for instance segmentations for AR scenes.
|-
| MGSO || Software / Algorithm || https://doi.org/10.48550/ARXIV.2409.13055 || A monocular real-time photometric SLAM algorithm utilizing efficient 3D Gaussian Splatting.
|-
| HINT-3D || Software / Framework || https://doi.org/10.5281/ZENODO.18491843 || A human-in-the-loop interactive test-time adaptation framework for 3D segmentation.
|-
| Visual localization using implicit representations || Software / Model || https://doi.org/10.5281/ZENODO.18468790 || Software for visual localization utilizing implicit representations and particle filtering-based pose refinement.
|}