As a researcher, you have probably heard about the FAIR (Findable, Accessible, Interoperable, Reusable) principles. Nevertheless, how do you make research data FAIR? Sign up for this hands-on training on 8 February 2022 and learn what FAIR is and what it means for different disciplines.

This course lies its basis within the PBL approach of Maastricht University. In this sense, we will build both a collective discussion of what FAIR is and what it means to different disciplines. We will then integrate what we have learned collectively by doing FAIR in breakout room sessions.

The participants will have a tutor available to answer questions about the exercises in the breakout rooms. However, it is up to the participants to do the exercises. The intention is to build a collective roadmap of FAIR points in an ending plenary session.

Learning objectives:

Get basic theoretical knowledge about what FAIR is and if and how it could be applied to all scientific disciplines.

Articulate benefits, barriers, and challenges in making data and other outputs FAIR.

Learn collectively through independent hands-on experience with techniques, services, and technologies to make your data FAIR or help others make their data FAIR.

Together come up with a collective roadmap of ideas on what it means to be FAIR. This last point will be used to keep building the course in the future.