The coursebook link: maastrichtu-library.github.io/qualitative-FAIR-data/

About 📗

Branching from the original FAIR Research Data Coursebook, we have developed a specialized version tailored for those working with qualitative data. In this iteration we maintain the foundational format of the original coursebook while focusing exclusively on examples to qualitative research.

Usually, training materials on FAIR principles are tedious and contain extensive theory. In this Library Carpentries-based coursebook, we aim to teach the implementation of FAIR principles differently. It has low entry-level materials and examples designed explicitly for the qualitative researcher can understand and immediately apply.

The coursebook covers essential topics for qualitative researchers, including:

• Get to know the importance of a “Research Digital Object”.
• Explore the available open-source tools for interoperability to make research digital objects sustainable.
• You will learn what “Data Terms of Use” and “Data Access Protocols” are and how to create them.
• You will review the differences and similarities of “Data Descriptions” in different science fields to discuss what we can do (as a scientific community) to standardize these practices.
• You will learn what “Rich Metadata” technically means on the Semantic Web and its relation to sustainable research output for future researchers.

💡 Following a bolder approach, we want to teach the implementation of FAIR principles differently. There is less focus on the theory and more emphasis on examples. Guided by 6 steps in Research Data Management

The training link: library.maastrichtuniversity.nl/events/qualitative-fair-data/