SIKS Symposium on Advancing Education and Knowledge: Exploring Generative AI, Hybrid Intelligence, Governance of Knowledge Graph Artefacts, and FAIR Knowledge Infrastructures

Wednesday 6 March Mini-Symposium 9.00-11.00 (VU HG-02A33) 

SIKS is proud to announce a mini-symposium on the very current topic of Advancing Education and Knowledge: Exploring Generative AI, Hybrid Intelligence, Governance of Knowledge Graph Artefacts, and FAIR Knowledge Infrastructures. This event will take place at the VU campus in the Main Building, room 02A33.

  • 09:00 – 09:05 Welcome
  • 09:05 – 09:30 John Domingue (The Knowledge Media Institute, UK) “Transforming University Education with Generative AI: Experiments at the Open University”

Abstract. It has been a little over a year since ChatGPT burst onto the world. This high exposure of Generative AI has forced universities to reflect upon and rethink many aspects of the way they teach and assess. Building on AI research, innovation and deployment which stretches over many decades, since the beginning of 2023 we have been exploring the potential of Generative AI to aid in OU teaching and learning. In this talk I will report on early results, including proof of concepts in the areas of content generation and digital assistants for students, the views of our students on these technologies, and outline possible future directions. The latest on our work can be found at: 

Bio. John Domingue holds a position of Professor of Computer Science, at the Knowledge Media Institute (KMi) and serves as the President of STI International, an organization specializing in semantics and responsible for the ESWC conference series. With a prolific career including serving as KMi Director from 2015 to 2022, Prof. Domingue has contributed over 240 refereed articles in fields such as semantics, AI, the Web, distributed ledgers, and eLearning. From 2017 to 2021, he led the first of five themes on University Learners for the £40M Institute of Coding, an initiative aimed at increasing the number and diversity of computing graduates in the UK while strengthening the connection between university teaching and corporate training. Between 2022 and 2023, Prof. Domingue spearheaded a project to develop a smart national educational content platform that incorporated cutting-edge AI techniques to support further education educators. Since 2023, he has been at the forefront of examining the impact of Generative AI on higher education. Prof. Domingue has delivered numerous talks on his work, including appearances at the Royal Institution in 2018, TEDx, and featured in THE Campus on interdisciplinary research teams. In 2019, he was inducted as a Fellow of the British Blockchain Association, and in 2020, he became an Honorary Professor at Amity University.

To learn more about his work, visit or follow him on Twitter: @johndmk.

  • 09:30 – 09:55 Ilaria Tiddi (VU University Amsterdam, The Netherlands) Knowledge Engineering for Hybrid Intelligence”

Abstract. Hybrid Intelligence (HI) is a rapidly growing field aiming at creating collaborative systems where humans and intelligent machines cooperate in mixed teams towards shared goals. In this talk, we will discuss how ontologies and knowledge engineering methods can be used to design, compare and improve Hybrid Intelligence applications.

Bio. Ilaria Tiddi is an Assistant Professor in Hybrid Intelligence at the Knowledge in AI (KAI) group of the Vrije Universiteit Amsterdam (NL). Her research focuses on creating systems that generate complex narratives through a combination of semantic technologies, open data and machine learning, applied mostly in scientific and robotics scenarios. She is Editor-in-Chief of the CEUR-WS publication, part of the Steering Committee for the Hybrid Human-AI Conference, and Coordinator of the international Staff Exchange for the Dutch Hybrid Intelligence consortium.

  • 09:55 – 10:10 Coffee break (coffee and tea provided)
  • 10:10 – 10:35 Oscar Corcho (Polytechnic University of Madrid, Spain) On the Governance of all the Artefacts used in Knowledge Graph Creation and Maintenance Scenarios”

Abstract. The creation and maintenance of knowledge graphs is commonly based on the generation and use of several types of artefacts, including ontologies, declarative mappings and different types of scripts and data processing pipelines, sample queries, APIs, etc. All of these artefacts need to be properly maintained so that knowledge graph creation and maintenance processes are sustainable over time, especially in those cases where the original data sources change frequently. It is not uncommon to have situations where ontologies are governed by an organisation or group of organisations, while mappings and data processing pipelines are handled by other organisations or individuals, using different sets of principles. This causes mismatches in the knowledge graphs that are generated, including the need to update all the associated artefacts (declarative mappings, sample queries, APIs, etc.) so as to keep up to date to changes in the ontologies, or in the underlying data sources. In this talk we will discuss several of the challenges associated to the maintenance of all of these artefacts in real-world knowledge graph scenarios, so as to provide some light into how we could set up a complete knowledge graph governance model that may be used across projects and initiatives.

Bio. Oscar Corcho is Full Professor at the AI Department at Universidad Politécnica de Madrid (UPM), where he is the deputy director of the R&D Center for Artificial Intelligence (AI.nnovation Space) and academic director of the EC-funded master on Artificial Intelligence for Public Services (AI4Gov), and leads a research group of 40+ members. His core research activities are centered around Open Science, Knowledge-Graph-based Data Integration and Ontological Engineering. These are applied to several domains of expertise, including public and private organisations. Since 2021, he co-leads the EOSC Association Semantic Interoperability Task Force, continuing with the earlier work on the EOSC FAIR working group, where he led the edition of the EOSC Interoperability Framework.

  • 10:35 – 11:00 Michel Dumontier (Maastricht University, The Netherlands) FAIR Knowledge Infrastructure for Biomedicine

Abstract. The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready – the key motivation behind the FAIR Guiding Principles. In this short presentation, I will discuss the need for and our work in creating FAIR and “AI-ready” data and services, including the FAIR Enough FAIR readiness evaluative framework, the Knowledge Collaboratory to curate and publish small FAIR data, and efforts to produce semantic web accessible services. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.

Bio. Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.