FAIR Practices in Your PhD: How to Manage Data and Code Responsibly

Diese Veranstaltung findet auf Englisch statt.

In this interactive session, PhD students and researchers will learn via hands-on checklists how to make Data and Code FAIR for their own projects. Participants will explore the FAIR principles and apply selected aspects to a real dataset or software project of their own. Through short quizzes and guided exercises, they map their current practices to FAIR requirements and identify concrete steps to improve issues such as data formats, documentation, licensing, and repository choice. By the end of the session, each participant leaves with a tailored FAIR mini action plan and a reusable workflow for making future data and code releases more FAIR with minimal overhead.

For organizational reasons, advance registration is requested. Please use the Stud.IP course for this purpose.

If you do not have Stud.IP access, please register at learnit@bibliothek.uni-halle.de.

Virtual training room: https://mluconf.uni-halle.de/b/mir-olc-ym1-owx