About MOVE
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About Measuring Ontologies for Value Enhancement (MOVE)
MOVE (Measuring Ontologies for Value Enhancement) is a research movement focused on evaluating how structured representations—ontologies, frameworks, modeling formalisms, and semantic scaffolds—create value, enable action, and shape outcomes across scientific, technical, organizational, and societal domains.
Unlike traditional ontology venues that assume a relatively stable notion of “ontology,” MOVE adopts a plural and pragmatic understanding of structured knowledge artifacts. Contributions to MOVE span formal ontologies, conceptual and enterprise models, enterprise architecture frameworks, evaluative frameworks, and emerging semantic architectures used in areas such as artificial intelligence, sustainability, governance, and socio-technical systems.
MOVE’s distinctiveness lies not only in proposing new representational formalisms but in examining how different forms of structuring meaning, knowledge, and intent perform under real-world constraints, risk, and uncertainty. This perspective enables MOVE to connect established ontology and systems research with emerging challenges, including, but not limited to, adaptive systems, collective intelligence, and evolving forms of artificial and hybrid intelligence.
Through this lens, MOVE functions as a bridge between ontology engineering, systems modeling, and broader questions of value, agency, and impact, positioning it across disciplinary boundaries while maintaining methodological rigor.
Beyond its technical contributions, MOVE plays an active role in supporting an inclusive and globally connected research community. The workshop series is designed to foster a heterogeneous environment, bringing together researchers and practitioners from different disciplines, methodological traditions, career stages, and geographic regions. MOVE places particular emphasis on supporting research in progress, offering timely and constructive feedback and mentoring that enable ideas to mature across iterations. By encouraging cross-venue dialogue and welcoming diverse forms of structured knowledge—ranging from formal ontologies to frameworks and emerging semantic approaches—MOVE provides a shared space where work that might otherwise remain fragmented can be meaningfully connected.
MOVE partners and collaborates with universities and research organizations across the world. For example, the inaugural MOVE2020 workshop was collocated with the Computer-Aided Cooperative Work (CSCW) conference. The MOVE2024 workshop was organized in collaboration with The Technical University of Sidney, Australia. MOVE2026 will be collocated at the Informatics Research Centre, Henley Business School, University of Reading, UK. In this way, MOVE supports its research-impact objectives by promoting inclusive scholarly participation, responsible dissemination practices, and sustained research development across diverse global communities.
The MOVE2026 workshop will take place in September 2026; further details, including submission guidelines and participation, are available in the Call for Papers
MOVE2026 Workshop Call for Papers and Presentations
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MOVE2026 - Measuring Ontologies for Value Enhancement (MOVE) Workshop
Theme: MOVE and AI
16-18 Sept. 2026
Dear Members of the MOVE and wider Research Community,
Dr. Simon Polovina (Department of Computing and Digital Technologies, Sheffield Hallam, UK, and Similie Logics Limited, Sheffield, UK), Dr. David Jakobsen (Department of Culture and Communication, Aalborg University, Denmark), and I, Dr. Rubina Polovina (Systems Affairs, Toronto, Ontario, Canada), are organizing the third MOVE workshop, titled “MOVE and AI”. It will be a hybrid (on-site and virtual) event, co-located at the Informatics Research Centre, Henley Business School, University of Reading, UK, 16-18 September 2026.
Our research community comprises academics from different science faculties and practitioners across the globe. We serve as a platform for publishing cutting-edge research that explores the role of ontologies and related paradigms and technologies in advancing AI. By engaging with the MOVE and wider research community, we can attract diverse, high-quality submissions from academia and industry, fostering innovation at the intersection of ontologies, ontology-like methods, and AI.
About the MOVE Community
The MOVE initiative explores the role of ontologies in AI systems, focusing on frameworks for knowledge representation, reasoning, and interoperability. Our work emphasizes how systematically integrated ontologies can address complex challenges in AI.
The MOVE community held its inaugural workshop in 2020, in collaboration with the CSCW 2020 (Computer Supported Cooperative Work) conference. Selected and enhanced papers from this workshop were published in the post-proceedings, “Aligning Computing Productivity with Human Creativity for Societal Adaptation,” available at https://link.springer.com/book/10.1007/978-3-031-22228-3.
The second MOVE workshop was hosted in 2024 in collaboration with the University of Technology Sydney, Australia. We are currently finalizing the proceedings for the MOVE2024 workshop published by Springer.
MOVE workshops play a pivotal role in generating high-quality research contributions. These workshops provide a platform for engaging diverse researchers and practitioners, fostering collaboration, and cultivating innovative ideas. Short papers (up to 15 pages without references) presented at MOVE workshops undergo a single-blind peer-review process to ensure their relevance, originality, and alignment with the track’s themes. Only selected and enhanced MOVE workshop papers will be submitted to the special track, where they will undergo an additional peer review to turn them into long papers. Alongside submissions received directly through the manuscript collection website, the workshops will serve as a valuable source of scholarly and practical contributions, enriching the special track with cutting-edge insights into ontology-driven AI research.
Proposed Themes
We envision the MOVE2026 topics encompassing, but not limited to, the following themes:
- Foundations of Ontologies: Advancing formalization to strengthen AI reasoning and decision-making.
- Evaluation and Benchmarking: Developing methods to assess and enhance ontology quality and utility.
- Applications Across AI Subfields: Leveraging ontologies in robotics, healthcare, NLP, and intelligent systems.
- Human-Computer Interfaces: Enhancing interaction and personalization through ontology-based frameworks.
- Emerging Paradigms: Integrating ontologies with quantum computing, hybrid AI, and explainable AI and other emerging technologies.
- Knowledge Representation: Supporting complex problem-solving via contextual and temporal modeling.
- Interoperability and Standards: Improving AI system coherence through standardized frameworks.
- Reasoning Under Uncertainty: Facilitating probabilistic and non-deterministic reasoning with ontologies.
- Multidimensional Modeling: Bridging dimensions like context, relationships, and time for holistic AI models.
- Advances in Knowledge Graphs: Enhancing scalability and utility via ontology-driven approaches.
- Conceptual Structures: Bringing Computer Productivity and AI to Human Creativity
- Case Studies: Highlighting real-world successes of ontology-driven AI.
- Ethics and Ontologies: Addressing bias, transparency, and accountability in ethical AI design.
- AI and Enterprise Architecture: Aligning ontologies with enterprise systems for adaptive, efficient solutions.
- Collective Intelligence: Advancing collaboration and knowledge sharing through ontology paradigms.
- Endeavour Architecture: Enabling human agency and purposeful action in Enterprise Architecture, such as advancing Human Rights.
- Facilitating Governance with AI and Ontologies: Advancing the integration of AI with ontologies and ontology-like frameworks to enhance governmental functions, with examples such as policymaking, complex decision-making processes, and informed political actions.
- Exploring AGI/ASI: Investigating ontologies’ role in designing and advancing general, multidimensional intelligence, such as human-like intelligence and beyond.
- Large Language Models (LLMs): Investigating how ontologies can enhance the interpretability, consistency, and contextual grounding of LLMs in various applications.
- Deep Semantics: Exploring ontologies and ontology-based frameworks to capture nuanced meanings, relationships, and contextual dependencies, enabling richer AI understanding and reasoning.
- Semiotics and Meaning-Making: Investigating sign systems, symbol grounding, and interpretation processes in AI, including the role of ontologies in structuring and stabilizing meaning across representations, modalities, and contexts.
- Sense-Making and Interpretation: Examining how agents construct, stabilize, and revise meaning under uncertainty, drawing on established sense-making traditions (e.g., organizational and information science) and connecting these processes to ontology design, semantic modeling, and AI reasoning.
- Philosophical Foundations of Meaning and Intelligence: Engaging with relevant philosophical theories (e.g., philosophy of mind, language, cognition, and logic) where they inform AI modeling, ontology design, and the interpretation of intelligence. Submissions should demonstrate clear implications for computational or representational frameworks.
- Origins of Intelligence and Life: Exploring theories of the emergence of life and intelligence, including biologically grounded and systems-based accounts. Contributions may examine how such theories inform AI architectures, definitions of intelligence, the development of ontology-driven models, and the structuring of the DIKW (Data–Information–Knowledge–Wisdom) space.
- Leveraging ontologies to facilitate NLP: Enhancing the understanding, translation, and generation of natural languages.
- Advance ecological and biological research: Using ontologies and AI to support groundbreaking efforts, such as facilitating interspecies communication, including whale communication, and broader ecological insights.
- Revolutionize neuroscience and medicine: Applying ontologies and AI to uncover complex neural dynamics, enhance diagnostics, personalize treatments, and advance our understanding of the brain and human health
The Editorial Team
The editorial team comprises members of the MOVE committee and experts in ontologies and AI. The MOVE committee will also assist in reviewing and promoting the track to ensure its success.
Next Steps
We believe the MOVE2026 workshop will provide an invaluable platform for advancing research at the intersection of AI and ontologies, and we look forward to the opportunity to collaborate. Participation in the MOVE2026 workshop is free of charge for all accepted authors.
Sincerely,
Rubina Polovina, PhD
On behalf of the MOVE Committee