Prof. Dr. Anna Fensel (Professor of Artificial Intelligence and Data Science, Wageningen University, The Netherlands): Abstract

The integration of knowledge graphs and semantic web technologies in agri-food research presents a transformative opportunity for scientific discovery, particularly when aligned with FAIR (Findable, Accessible, Interoperable, Reusable) principles and generative AI. While symbolic AI and semantic web methods offer robust solutions for data integration and interoperability, a persistent challenge often remains: the lack of high-quality, semantically rich data. Current FAIR data implementations often fall short, limiting their usability in AI-driven analyses, including machine learning and deep learning. This issue is especially critical in complex, interdisciplinary fields such as agriculture, health and food sciences, where heterogeneous data must be efficiently linked to address sustainability and climate adaptation challenges. Additionally, data ownership concerns, legal compliance (e.g., GDPR, AI Act), and fragmented governance frameworks further hinder collaboration and innovation. To overcome these barriers, we need specialized research infrastructures that enable responsible data sharing and reuse, while ensuring legal and ethical compliance. In this talk, I will present strategies for leveraging knowledge graphs to enhance FAIR data practices and explore their role in generative AI applications for advancing agri-food research and sustainable development.

Organised by BCS SGAI The Specialist Group on Artificial Intelligence https://www.bcs-sgai.org