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Application of Recently Developed FAIR Metrics to the ELIXIR Core Data Resources

Webinar Summary

 

This webinar is presented jointly by the Pistoia Alliance and ELIXIR. 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 and supported through an ELIXIR Implementation Study, Michel worked with a subset of ELIXIR Core Data Resources to apply these technologies.

 

In this webinar, he will discuss their approach, findings, and lessons learned towards the understanding and promotion of the FAIR principles.

 

About the Speaker

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.

This on-demand webinar is part of the FAIR Webinar Series. For more information about the Pistoia Alliance’s FAIR Implementation project, please contact us.

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Posted on October 17, 2019 by Catherine Maskell
Categories: FAIR Implementation, Pistoia Webinars

Tags: data, data models, FAIR, Real World Data, webinar


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