Practical Tools, Applications, and Training for Researchers Working with Sensitive and Federated Data
Leiden, Netherlands, December 2025 – The Chair of FAIR Data Science at LUCID‑LUMC has released a new practical guide titled “Advancing FAIR Open Science in LUCID (LUMC)”, authored by Prof. Dr. Mirjam van Reisen. This guide offers researchers a hands‑on roadmap for applying FAIR Data Principles in clinical, humanitarian, and interdisciplinary research settings.
The guide is designed to support researchers at Leiden University Medical Centre (LUMC) and its global partners — including AUN‑FOS, EEPA, VODAN‑Africa, and the Digital Governance in Africa programme — in strengthening data stewardship, interoperability, and ethical analytics.
What’s Inside the Guide?
- Understanding FAIR Data
- Origins of FAIR at Leiden University
- Definitions: FAIRification, FAIR Data Points, Federated Repositories
- Semantic enrichment and machine‑actionable metadata
- Ownership, localisation, and regulatory compliance (FAIR‑OLR)
- Practical Applications
- Creation of FAIR Data Points for research datasets
- Real‑time epidemiological surveillance using federated models
- Patient data workflows for epidemic preparedness
- Inclusion of sensitive data from vulnerable populations
- Humanitarian data stewardship and personal data pods
- Tools and Support
- Access to LUMC’s FAIR Data Point: fdp.lumc.nl
- Deployment examples from Ethiopia, Kenya, Nigeria, and Uganda
- GitHub resources and training support from the Chair of FAIR Data Science
- Interdisciplinary collaboration with LIACS, Tilburg University, and UNA Europa
- Curriculum and Capacity Building
- Training modules for PhD students, clinicians, and data stewards
- FAIR‑by‑design strategies for humanitarian and clinical data
- Use cases in GBV reporting, refugee protection, and antenatal care
Why This Guide Matters?
As FAIR Data becomes a cornerstone of global research policy, this guide empowers researchers to:
- Make their data findable, accessible, interoperable, and reusable
- Ensure ethical and secure handling of sensitive datasets
- Participate in cross‑border research collaborations
- Align with emerging Health and Humanitarian Data Spaces in Africa and Europe