The FAIR Metroline provides you with FAIR guidance. However, which steps are actually relevant for your FAIRification journey depends on your FAIR objectives. For example, if your objective is to make your existing data Findable and Accessible in a catalogue, a step like Design eCRF will not be relevant.
This section provides guidance for common FAIR objectives through FAIR use cases.
Evaluate FAIRness of your data
Assess how well your data meets FAIR principles and identify areas for improvement using evaluation tools and frameworks.
How to make my dataset Findable?
Register your dataset in institutional catalogs with proper metadata to comply with data policies and enable discovery.
How to make a new dataset interoperable from the start
I want to design my new dataset so it is interoperable from the start, including alignment to existing standards or reference datasets.
Make an existing dataset citable in a publication
I want to make the dataset underlying my publication citable, while meeting journal requirements and respecting institutional policies and any restrictions on data access.
How can we connect equipment data, metadata and repositories?
Illustrative WUR/IBISBA-style use case showing how equipment data, structured metadata and research assets could move from LEAF and FAIR Data Station into FAIRDOM-SEEK.