Application of recently developed FAIR metrics to the ELIXIR Core Data Resources

Thu 17 October 2019, 16:00

The FAIR (Findable, Accessible, Interoperable and Reusable) principles aim to maximize the discovery and reuse of digital resources. Using recently developed​ software and metrics to assess FAIRness, an ELIXIR Implementation Study looked at a subset of ELIXIR Core Data Resources to apply these technologies.

In this webinar, the lead of the Implementation Study Michel Dumontier (ELIXIR Netherlands) discussed their approach, findings, and lessons learned towards the understanding and promotion of the FAIR principles.

This webinar was presented jointly with the Pistoia Alliance.

Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research focuses on the development of computational methods for scalable and responsible discovery science. Previously at Stanford University, Dr. Dumontier now leads the interfaculty Institute of Data Science at Maastricht University to develop sociotechnological systems for accelerating scientific discovery, improving human health and well-being, and empowering communities with ethical data-driven decision making. He is a principal investigator in the Dutch National Research Agenda, the European Open Science Cloud, the NCATS Biomedical Data Translator, and the NIH Data Commons Pilots. He is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.

See also: Data Platform