FAIR Assessment in Geo-INQUIRE: Lessons Learned from Two Years of Experience

The Geo-INQUIRE* project concerns an initiative in which, in a cross-domain setting, the European ESFRI landmark environmental research infrastructures EPOS, EMSO, ECCSEL, the Center of Excellence for Exascale Computing ChEESE, and the ARISE infrasound community, exploit innovative techniques to meet their FAIR data ambitions. At EGU25 we informed the audience about the project’s data management objectives and the strategies that were applied to translate the abstract concept FAIRness into practices that could widely be adopted in a large heterogeneous landscape of data producers. Specifically, we demonstrated how we established a pipeline for the assessment of levels of FAIRness with the integration of the F-UJI tool. This Geo-INQUIRE FAIRness Assessment Pipeline (GiFAP) is in use now for a period of about two years, in which it has proven to be a valuable instrument for the ongoing evaluation of the FAIRness of multiple datasets over time. However, interpreting and comparing snapshots of the value collections is by no means trivial and must be managed and communicated with care.

Because the integration of an assessment tool like F-UJI at the time always involves the adoption of a solution which itself is under active development and as such can hinder the reproducibility of outcomes, special care must be taken with respect to the versions used of both the tool itself and the underlying metrics framework. It is also essential to understand the effect of choices made during repeated assessment across time on the FAIR scores and their subsequent interpretation. The practical use of the overall pipeline as a tool to guide improvements in the FAIRness of data, mainly by adapting and improving the metadata, has revealed valuable insights in the subtleties of applying the FAIR data concept in different communities and to different data types.

As an important real-world example of applying the FAIR concept in a complex dynamic data-lifecycle setting we will explain how we technically integrated the F-UJI instrument in the existing infrastructure. A special focus will be put on possible pitfalls and their solutions regarding versioning issues that naturally arise when comparisons will be made over a longer period of time. The importance of managing expectations, the dependency on data managers, and the interference with applications for long tail researchers will be discussed and we will explain how we covered these within the project. Finally, we will explain how the Geo-INQUIRE solution could be adopted for comparable scenarios. 

* Geo-INQUIRE is funded by the European Union (GA 101058518)