Funders and publishers increasingly expect research data to be FAIR (findable, accessible, interoperable, and reusable). But turning that catchy acronym into research practice can be far from straightforward.

The FAIR principles are often technical and complex, leaving many researchers unsure of how to meet requirements in practice. Without clear guidance, you risk spending extra time on compliance or missing opportunities to make your data more visible, reusable, and impactful.

In this course you will get a hands-on introduction to what FAIR really means and how to apply it in your own projects.

You will learn how to:

• Make your research data more findable and accessible
• Ensure interoperability and reusability through good documentation and formats
• Take practical FAIRification steps before, during, and after your project

Sign up today and learn how to turn the FAIR principles into everyday research practice.

Optional: You can prepare by watching modules 1 and 2 of our eLearning course on Research Data Management.