FAIR for Qualitative Data

FAIR for Qualitative Data is a course for researchers working with qualitative research material and willing to explore how FAIR (Findable, Accessible, Interoperable, Reusable) could fit their work. The course will be informative but also hands-on and practice-based.

The course covers the basics of FAIR practices and helps qualitative researchers decide how the FAIR principles could be applied to their work. The course is a co-constructive exercise, so your work and active participation will be key to keep designing the course.

Learning objectives:

• Theoretically discuss FAIR and its possible limits for non-readable machine research data.
• In breakout rooms look into FAIR repositories with qualitative data and constructively be critical to the researcher’s approaches in terms of becoming findable and accessible.
• We will use a real case scenario to explore how inter-operability and re-usability can become useful aids while working with teams of qualitative researchers.

Target group: Researchers at Maastricht University Working with Qualitative Data

Language: English

Pre-requisites: Researcher at Maastricht University, Advanced English C2 level

Maximum number of participants: 15

You can register for the event here.