FAIR Assessment Practices

• DOI: 10.52825/cordi.v1i.344
• Publication Date: 2023-09-08T08:53:45Z
• Authors: Janete Saldanha Bach; Fidan Limani; Yudong Zhang; Atif Latif; Brigitte Mathiak; Peter Mutschke
• Keywords: 0301 basic medicine; 03 medical and health sciences

The poster presents FAIR assessment experiences in the context of the two NFDI consortia KonsortSWD and BERD@NFDI, employing the established Research Data Alliance's FAIR Data Maturity Model (RDA-FDMM) and the F-UJI Tool, an automated solution. RDA-FDMM, a manual technique, is more comprehensive, while the automated F-UJI tool effectively detects areas of improvement in metadata presentation that automated means can address. Our experiences highlight the need to examine both machine-readable as well as non-machine-readable elements and acknowledge automated tools' limitations, while valuing their insights. As the research ecosystem advances, metadata representation should be made increasingly machine-readable. We recommend a "FAIR by design" approach from the beginning to ensure alignment with FAIR principles in project outcomes. Continuous assessments during a project’s lifetime promote ongoing research data infrastructure improvements within the NFDI consortia context, contributing to NFDI infrastructure innovation and optimization.