Funders, publishers and scientific organizations have highly endorsed the adoption of FAIR principles (Findable, Accessible, Interoperable, and Reusable) to promote research data reusability and reproducibility. However, FAIR principles are high-level guidelines without explicit requirements for their implementation. Practical solutions such as metrics and associated tools are required to support the assessment of FAIR compliance of research artefacts such as services and datasets. This talk will introduce an open-source tool named F-UJI which was mainly developed to support trustworthy data repositories committed to FAIR data provision to programmatically measure datasets for their level of FAIRness over time. The talk will provide an overview the development and application of F-UJI and use cases it has supported so far.