Description

Online

Zoom

27 November 2024, from 13:00 to 17:00

29 November 2024, from 13:00 to 17:00

4 December 2024, from 13:00 to 17:00

5 December 2024, from 13:00 to 17:00

11 December 2024, from 13:00 to 17:00

25 (online)

  Barbara Magagna (GO FAIR Foundation), Erik Schultes (GO FAIR Foundation)

The FAIR Principles call for findable, accessible, interoperable, and reusable data for humans and for machines, but they don’t provide detailed instructions on how to achieve these goals. This course provides a rigorous understanding of the FAIR Principles and ideas on how to roadmap your FAIR implementation ambitions using the Three-Point-FAIRification Framework.

After completion of the course the trainees will be knowledgeable about the origins and history of FAIR, the problems that FAIR solves (Why do we need FAIR?), the costs/benefits of implementing FAIR, be aware of good implementation examples and of “Fake FAIR”, be aware of qualitative and quantitative FAIR assessment tools, be knowledgeable on how FAIR fits into data management and data stewardship, and understand how to prioritize FAIR implementations in project proposals and roadmapping.

Participation is documented as publicly available nanopublications.