Prof. Toshiaki Katayama
Database Center for Life Science (DBCLS), Tokyo, Japan
Toshiaki Katayama is a bioinformatics researcher working at the Database Center for Life Science in Japan. He graduated from Kyoto University in 2001 and worked for developing the KEGG database as an associate instructor at the Bioinformatics Center in Kyoto University. He became assistant professor of the Human Genome Center at the University of Tokyo in 2003 where he developed Web services for the KEGG database. In 2012, he moved to the Database Center for Life Science and is currently working on the data integration and standardization of life science databases with Semantic Web technologies. He has been organizing annual international BioHackathon and monthly Togothon meetings. He received Ph.D. from the University of Tokyo in 2019 for his work on standardization and interoperability of bioinformatics data and web services. See the LinkedIn public profile for more details.
Prof. Anna Fensel
Wageningen University & Research, Wageningen, the Netherlands
Title: Knowledge graphs for FAIR principles and legal compliance in health care and life sciences data.
Abstract
The adoption of semantic web technologies in health care and life sciences has a long-standing record of success, demonstrating that many of the challenges we face today already have well-established solutions. Symbolic artificial intelligence (AI) and the semantic web in particular provide robust methods that prioritize data integration and interoperability. However, a critical bottleneck persists: the need for high-quality data and metadata. This has a broader overall impact for AI in life sciences, as the utility of any computational approach is inherently limited by the availability and quality of its input data. A significant issue here lies in the frequent lack or insufficiency of semantics in the current deployments of FAIR (Findable, Accessible, Interoperable, Reusable) data practices. Data across life sciences disciplines often remain un-FAIR, also for its processing with further AI techniques, such as machine learning and deep learning. This is especially problematic in addressing complex, interdisciplinary challenges, such as adapting to climate change, where heterogeneous data sources must be seamlessly integrated. Furthermore, researchers and organizations frequently exhibit a possessive attitude toward data, creating further barriers to collaboration and sharing. The need for legal compliance (with laws such as GDPR, AI Act, etc.) is adding even further risks and barriers. To address these challenges, we must implement better data governance frameworks that facilitate responsible and legal data reuse while preserving ownership and trust. Specialized research data infrastructures, underpinned by semantic web technologies, can enable the realization of FAIR principles at scale. Knowledge graphs and formal ontologies, in particular, offer a powerful tooling for organizing and linking diverse datasets, ensuring compliance with legal and ethical standards while enhancing their utility in health care and life sciences. In this talk, I will showcase practical solutions and strategic directions for employing knowledge graphs to advance FAIR principles and legal compliance, and discuss their adoption, emphasizing their transformative potential for life sciences, green sciences and beyond.
C.V.
Anna Fensel is a Full Professor in Artificial Intelligence and Data Science at Wageningen University & Research, Wageningen, the Netherlands. Previously, she was an Associate Professor and Senior Assistant Professor at Semantic Technology Institute (STI) Innsbruck, Department of Computer Science, University of Innsbruck, Austria, and prior to this worked as a Senior Researcher at FTW – Telecommunications Research Center Vienna, Austria, and a Research Fellow at the University of Surrey, UK, and as a project employee at DERI Innsbruck, University of Innsbruck, Austria. Anna has earned her habilitation (2018) and her doctoral degree (2006) in Computer Science at the University of Innsbruck. Prior to that, she has received a diploma in Mathematics and Computer Science equivalent to the Master degree (2003) from Novosibirsk State University, Russia. Her research focus is on semantic technology, linked data and knowledge graphs, and their application and adoption in various domains (e.g. sustainability, energy efficiency, production, food and health, social sciences), as well as across them. Anna has been extensively involved in EU and national third-party funded projects, being a consortium coordinator of several projects, as well as a principal investigator in further more than 20 projects. She has been a co-organizer or a Program Committee member of more than 100 scientific events, including being in chair roles at major events (e.g. RuleML+RR, SEMANTiCS, and ESWC), an editor and reviewer for numerous journals (e.g. as an editorial board member of Engineering Applications of Artificial Intelligence) and a project proposals evaluator for numerous EU and national funding agencies. She has co-authored ca. 150 refereed publications, and received several best paper awards.
Prof. Jiri Vondrasek
PI – Vondrasek’s group at IOCB AS CR, Head of the ELIXIR CZ Infrastructure
Title and abstract to be defined.
Miguel Pedrera Jimenez, PhD
Health Data Platform Specialist at Better
Title and abstract to be defined.