RDM, FAIR, and data sharing practices and perceptions of people who work with sensitive health data

This talk was presented at the University of Manchester Open Research Conference, 9-10 June 2025.

Introduction: Proper adoption of RDM (Research Data Management) and FAIR (Findable, Accessible, Interoperable, Reusable) practices in health data is blocked by technical and cultural barriers, which need to be investigated and understood to drive widespread culture change.

Methods:To explore these barriers and discover the current practices of researchers who work with sensitive health data and their knowledge and understanding of RDM and FAIR, we interviewed researchers at the University of Manchester.

Results:Nine researchers were interviewed - most had not heard of FAIR. All agreed that RDM and FAIR are important and that, overall, motivations outweighed the barriers. Motivations included producing trustworthy, high-quality science, maximising data use, and future proofing research. Limitations included limited time/resources, little-no knowledge of best practice, limited infrastructure and lack of human technical support. Unique to sensitive health data was the volume of legal and ethical “red tape”, and the people, time, and resources needed for this. Four researchers mentioned dropping research ideas and collaborations because of this.

Discussion:Further research is needed into the cultural barriers to good RDM/FAIR practices among sensitive health data researchers, particularly to investigate how to overcome barriers and create widespread cultural shifts in practices.