FAIR Data Management and Stewardship
Contact: Dr. Brendan Palmer
Research funding is evolving and the onus now rests on primary researchers to plan the collection, curation and release of research data with a view to maximising its utility post-project. All funders are now requesting that the data generated within a project adhere to the FAIR guiding principles (Findable, Accessible, Interoperable and Re-usable)1. FAIR provides a roadmap towards ensuring that the data is made as open as possible, yet as closed as is necessary. Therefore responsibility for the data needs to commence at the application stage and be brought through the lifetime of the project.
From the 1st January, 2020 the HRB have made good data governance and stewardship an integral part of all funding calls2. This policy includes all research data, and extends to software and material outputs that underlie HRB-funded projects
HRB CRF-UCC services include:
1. Pre-award support on data management planning and FAIR
2. Post-award development of data management plans guided by the FAIR data principles
3. Use of electronic data capture services offered through Castor EDC
4. Database and data dictionary construction
5. Publication of data objects, project workflows and DOI assignment
The HRB CRF-UCC Statistics and Data Analysis Unit has trained data stewards in place to support investigators adhere to these emerging requirements3. The trained data stewards are available to assist with drafting the data management sections at proposal stage and provide guidance with respect to the associated costs involved. The trained data stewards are also prepared to support successful investigators develop full data management plans, at post-award stage in line with funder requirements.
Please contact: Brendan Palmer (HRB CRF-UCC Associate Statistician)
1. Wilkinson et al., (2016), The FAIR Guiding Principles for scientific data management and stewardship.
2. HRB Policy on Management and Sharing of Research Data.
3. FAIR data management: A new funding requirement, but a pre-existing research necessity.