Cátia Pesquita, an integrated researcher at LASIGE, was the keynote speaker at the 8th Workshop on Semantic Web Solutions for Large-scale Biomedical Data Analytics, a co event with the ESWC 2025: Extended Semantic Web Conference, which took place in Portoroz, Slovenia, from 1 to 5 June 2025.

The talk “Knowledge Graphs for Explainable Scientific Discovery” explores the role of knowledge graphs in addressing these challenges through the lens of biomedical research with a particular focus on protein-protein interaction prediction and drug repurposing. It highlights the limitations of current knowledge graph embedding techniques, which, although able to integrate domain knowledge into models, often trade explainability for predictive performance, and examines recent advances in explainable approaches for semantic similarity, embeddings, and path-based reasoning and concludes with a vision of the future of scientific research, where artificial intelligence systems are able to generate scientifically meaningful outcomes grounded in domain knowledge, verifiable against existing evidence, and capable of advancing understanding.