JOWO 2025 Workshops

Cognition And OntologieS, celebrates its 9th edition. CAOS investigates fundamental cognitive phenomena and concepts across language, psychology, and reasoning, examining how these can be formally and ontologically analyzed in the context of both traditional symbolic AI and contemporary neural approaches. The workshop emphasizes the exploration of connections between cognitive sciences/experimental psychology and ontologies, while also incorporating insights from recent advances in large language models and embodied cognition. This investigation aims to develop robust formal and logical modeling approaches that can capture these relationships effectively. The workshop particularly focuses on how such formalizations and ontological analyses can enhance current AI systems and information architectures, bridging the gap between broad but shallow artificial intelligence and human-like cognitive capabilities.

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FOMI is an international forum and the flagship meeting of the Industry and Standards Technical Committee (ISTC) of IAOA. It brings together researchers and practitioners to analyze and discuss challenges related to formal ontologies, knowledge modeling, and semantic interoperability in diverse industrial contexts. The workshop aims to gather results, address key issues, and share lessons learned from the implementation of theoretical approaches and ontological analyses of existing industrial systems.

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SWODCH 2024 is the fifth edition of the International Workshop on Semantic Web and Ontology Design for Cultural Heritage. The purpose of the workshop is two-fold: First, it aims to gather foundational research work on the design of conceptual models, knowledge graphs, ontologies, and Semantic Web (SW) technologies for Cultural Heritage (CH) and the Digital Humanities (DH). A plethora of heterogeneous and multi-format data currently available in these domains asks for principled methodologies and technologies to semantically characterise, integrate, and reason with data, and to support their retrieval, management, analysis and visualisation. We also welcome philosophical and sociological analyses of data, knowledge representation models and modelling practices in CH and DH, possibly taking into account the social or historical dimensions of data. Second, SWODCH aims to bring together stakeholders from various fields of Computer Science and the Humanities, involved in the development and deployment of concrete SW solutions for CH, efficiently building, managing, exploring, visualising or mining CH knowledge graphs. More than 20 years after the beginning of this century, any SW solution should be designed according to the FAIR principles and the workshop supports the creation of datasets and applications that respect and are compliant with these principles.

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ISD9 is the ninth edition of a series of fun and interesting workshops devoted to cognitive primitives, spatial reasoning, embodied cognition, analogical reasoning and investigations of the puzzle pieces of mind. A truly interdisciplinary event, we invite contributions from a range of scientific, professional and artistic domains. Typical submissions consist of work such as formal modelling of cognitive phenomena, ontological structures of mental patterns, semantic analysis of language and/or art, psycholinguistics experiments and formal application in robotics/intelligent agents. The workshop series takes pride in being a friendly and welcoming environment for researchers of all stages. All contributions will be peer-reviewed by an international program committee of experts on the field. 

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The application of ontologies to food systems involves a number of perspectives that altogether promise a more stable, permanent open-source vocabulary which can evolve incrementally to describe food system behaviour as it spans from ecosystem and anthropogenic source, to individual and population-level nutritional and socioeconomic import.  Philosophical discussion of food semantics helps to arrive at a consensus model/language of food materials, roles, dispositions, functions, and processes – a middle/upper-level ontology that we can all agree upon.  A technical / applied ontology perspective brings structure and tools for vocabulary curation, quality control, lookup, and reuse, as well as application focus on food related biosample collection, plant or animal breeding, robotics, industrial automation, etc.  A sociotechnical view wraps all of this work into a broader interdisciplinary “lingua franca of data science” effort to blend tangential domains of knowledge – from life science, animal and plant rearing, industrial and distribution infrastructure, food traceability, and regulatory management towards public and environmental health and security.  Our time of rapid change demands narratives that identify, anticipate and explain courses of action to alleviate hunger, food insecurity, environmental degradation and climate change, narratives that rely on ontologies to salvage learning by enabling precise integration and comparison of past and present food system research and production data.

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This workshop focuses on foundational ontologies, which systematize high-level categories like objects, events, and relations to enhance interoperability in systems and software. Despite their recognized importance, debates persist regarding their scope, structure, and role in relation to domain ontologies. The workshop provides a platform for researchers to explore these foundational aspects, discuss philosophical underpinnings, present new research, compare existing ontologies, and assess their broader relevance.

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Ontologies, e.g. foundational, core, and domain-specific, facilitate the definition, disambiguation and formalisation of meanings, and promote shared understandings via semantic alignment within and between domains. Additionally, ontologies can foster interoperability, an essential redress to the challenges of information fragmentation and compartmentalised knowledge which affect scientific understanding and communication in critical sectors such as health, education and sustainability. Yet formal and applied ontologies remain inaccessible to many, scientific experts and lay people alike, who, given the chance to engage with ontologies and ontological thinking, could benefit in their structuring of knowledge and understandings of data and information. Indeed, ontologies can be difficult to learn and challenging to develop and apply, which hinders their usability, understandability, and quality. This state of affairs suggests the importance of discovering, and elaborating more diverse and human-centric approaches to ontology learning, teaching, development and sharing. The II edition of Playing with Meanings (PwM 2025) workshop builds upon the very successful first edition, hosted at the 14th International Conference on Formal Ontology in Information Systems (FOIS 2024). The workshop will continue to explore interaction design methodologies, in particular game ad play, co-creation and and knowledge co-design for learning, teaching, developing, and using ontologies, ontology-based conceptual models, and their associated notions. The broader goals of PwM are to (i) introduce the methodologies of game, play and embodied sense-making (i.e. situated, socially coordinated learning through action), (ii) engage hands-on with ontology-games and activities such as group modelling and scenario analysis, and overall (iii) reflect on, and search for solutions to, the challenges of learning and applying ontologies.

The Knowledge Management and Process Mining for Law (KM4LAW) workshop explores how Artificial Intelligence (AI), Knowledge Modelling (KM), and Information Extraction (IE) methods drive innovation in legal informatics. It covers fields such as ontologies, argumentation, natural language processing, and network analysis, often with a multilingual focus. Rapid AI advances enable new approaches to once-intractable challenges, raising questions about the limits of automated systems and how they address remaining ambiguities requiring legal interpretation. Topics include classifying and clustering legal sources, process mining for compliance, extracting and aligning multilingual data, and deploying transformers and Large Language Models (LLMs) in legal tasks. Through these themes, KM4LAW fosters a holistic dialogue on knowledge management and process mining for law.

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Cybersecurity, which concerns both human and technological aspects, refers to a set of techniques used to protect the integrity of networks, programs, and data from attack, damage, or unauthorized access. With the spread of systems and applications, attacks continue to grow in sophistication, with attackers using an ever-expanding variety of tactics such as social engineering, malware, and ransomware. To reduce the risk of cyber-attacks and protect against exploitations, new methods and technologies are emerging. Formal methods, in particular ontologies, constitute an effective approach to mitigate the incompleteness and ambiguity of security directives and to semantically characterize security stakeholders, ranging from offensive techniques to compliance, vulnerability, encryption, data protection, authentication, confidentiality, integrity, and availability. The “Semantic Shields: International Workshop on Modeling for Cybersecurity” aims to bring together cybersecurity experts, conceptual modelers, and ontologists, from scholars to practitioners, to develop applications, methods, and tools impacting the cybersecurity domain.

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The continued evolution and widespread adoption of Large Language Models (LLMs) in 2025 have intensified interest in integrating ontologies and knowledge graphs to enhance their capabilities and address limitations. Ontologies provide structured, semantically rich representations that can improve LLM reasoning, trustworthiness, and explainability, while LLMs offer new opportunities for ontology learning, knowledge extraction, and dynamic reasoning. This workshop explores the convergence of knowledge representation and LLMs, bringing together researchers, practitioners, and policymakers from industry, academia, and government to discuss emerging trends, challenges, and solutions. We invite submissions that examine strategies, design patterns, models, and benchmarks for integrating ontologies and LLMs, with a focus on advancing explainable AI and improving hybrid knowledge architectures.

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Extracting nuanced and context-sensitive information (i.e. the subtle, often implicit data embedded in text, images, and multimodal signals) is a key challenge in advancing Entity Linking (EL) and Information Retrieval (IR). While effective for explicit knowledge extraction, traditional pipelines often struggle to capture more complex elements, such as emotional undertones, sociocultural themes, or context-dependent subtleties. Recent advancements in machine learning, particularly Large Language Models (LLMs), show promise for directly inferring enriched semantic graphs that bridge this gap. The first edition of EIKE – Explicit and Implicit Knowledge Extraction from Text offers an opportunity to discuss breakthrough techniques, including neuro-symbolic systems, deep learning models, and ontology-based methods to address these challenges. By focusing on the direct extraction and representation of knowledge, the workshop aims to advance the state-of-the-art in semantically rich and context-aware knowledge systems. This workshop accepts contributions on several topics, such as (but not limited to): knowledge extraction, information extraction, machine reading, ontology-driven contextualization, neuro-symbolic AI for EL and IR, and ethical aspects of knowledge extraction.

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Semantic Technologies provide a formal way to represent knowledge in ways that are interpretable by computers and a related technology stack to store, integrate and query information semantically. Technical advances in the past decade have led to a growing role for semantic technologies and other AI techniques in the service of humanity. As their integration into society advances, exciting new opportunities emerged to apply them towards addressing increasingly complex problems. The purpose of the OSS workshop is to foster communication and strengthen interdisciplinary work at the intersection of semantic technologies, service provisioning, and social good. We invite researchers from the Knowledge Representation, Ontologies, Semantic Web, LLMs, Machine Learning, and Neuro-symbolic AI communities to submit theoretical contributions, novel algorithms, artifacts, ontologies and tools related to the interaction of service provisioning and social-good. We welcome reports from sociologists and service practitioners across various society-focused domains (e.g. social workers, therapists, physicians, probation officers, urban planners, etc.) on their experiences using semantic-enabled technologies, best practices, and insights.

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This workshop explores the role of semantic technologies in advancing research on healthy aging. Disparities in definitions, measurement approaches, and theoretical frameworks often hinder effective synthesis across studies on aging-related phenomena. For example, solitude research frequently examines short-term psychological states, while narrative identity studies focus on long-term identity development and meaning-making, and gerotranscendence research investigates shifts in life perspectives among older adults. Although these areas share conceptual overlaps, inconsistencies in construct definitions and methodologies limit their integration. Semantic technologies provide a structured approach to bridging these gaps, enabling more coherent, reproducible, and interoperable research on aging. We invite submissions that explore how ontologies and knowledge representation methods can contribute to understanding and promoting healthy aging, supporting researchers in integrating diverse data sources, standardizing key concepts, and fostering interdisciplinary insights.

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This workshop explores the nature and role of dispositions and other realizable entities—things like fragility, toxicity, or the ability to perform an activity—that connect the static and dynamic aspects of reality. These entities are central in formal ontology, influencing fields such as biology, health sciences, engineering, enterprise modeling, and risk assessment. Despite significant progress, key questions remain: Which types of use cases benefit from the explicit representation of realizable entities? How should realizable entities be formally characterized? How do they relate to other ontological categories, such as qualities and events? Can dispositions provide a solid foundation for causation and replace laws of nature in ontology? Bringing together computer scientists, philosophers, cognitive scientists, domain experts, and other specialists, this interdisciplinary workshop provides a platform for discussing realizable entities from multiple perspectives, addressing both theoretical and applied aspects.

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Automated Planning and Ontology are two well-established fields of Artificial Intelligence (AI). The former investigates techniques to formally model and reason about the effects of actions, and decide the combinations of actions that allow an agent to achieve goals. The latter investigates techniques to formally represent and define knowledge (by formally describing domain entities and their interrelations), allowing agents to process information about objects, events, and other sorts of entities, and incrementally build and verify beliefs.
Both Automated Planning and Ontology generally rely on logic to model knowledge and reasoning over it, organizing reasoning mechanisms. They support the development of cognitive capabilities that autonomous agents need to effectively act in the real world.

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