FAIR data practices for qualitative research in transdisciplinarity.
FAIRqual explores how to make FAIR data practices part of qualitative data management in transdisciplinary research. Qualitative data raise ethical and confidentiality questions that make open sharing hard, yet sharing them can improve learning between transdisciplinary processes and engagement between science and society. The project works through workshops, expert interviews, technical workflows, and a community of practice.
The funded project ran from autumn 2024 to autumn 2026 and is completed. The team carries the work on, and the material here keeps evolving.
- website: source of the project website at https://fairqual.github.io/website/ with blog, events, slides, and the proposal.
- dataitd24: R data package with the ITD24 workshop data, documented at https://fairqual.github.io/dataitd24/ and archived on Zenodo.
Franziska Mohr, Mollie Chapman, and Bianca Vienni-Baptista (Transdisciplinarity Lab) with Lars Schöbitz and Elizabeth Tilley (Global Health Engineering), all at ETH Zurich. See the About page.
Email mollie.chapman@usys.ethz.ch or open an issue on the relevant repository.
Supported by the Open Research Data Program of the ETH Board.