In this use case, we intend to discuss potential FAIR metrics for the Earth and Environmental Sciences community (here: solid earth and oceans excluding atmosphere and biosphere) in collaboration with projects such as FAIR-EASE, Blue-Cloud and ENVRI-FAIR. For this purpose we want to analyze the FAIR habits of this community to find out if there are similarities in the use of e.g. identifiers, standards and vocabularies that justify deriving their own FAIR metrics from the existing FAIRsFAIR metrics. We will investigate existing technical interfaces for metadata exchange and use FAIR implementation profiles of relevant data archives.
Initiatives such as GEOSS or OGC have contributed in recent years to the fact that the level of standardization of earth and environmental science data repositories is generally quite high. In addition, there are a number of ongoing EU projects dealing with the implementation of the FAIR principles in this community. However, the Earth science community is quite diverse and there is no common understanding of FAIR so far. Using the example of some established research infrastructures from different fields of earth and environmental sciences, we will first investigate how homogeneous the use of FAIR implementation resources such as metadata standards or vocabularies is and try to develop metrics for the community or for appropriate parts of this community.
Challenges that need to be addressed
Within the earth and environmental sciences, there are a number of sub-communities that have already established functioning infrastructures for sharing data and metadata. Although there are many intersections in the use of standards and formats, there is no overview or appropriate database for this. Furthermore, there is a lack of information on how these communities intend to or already have implemented the FAIR principles. It will also be challenging to propose and agree on a common set of FAIR metrics for this community.
Expected impact of the Use Case
The main impact of the use-case will be to create synergies between ongoing initiatives on FAIR and to reuse existing preliminary research on FAIR from the FAIR-EASE, Blue-Cloud and ENVRI-FAIR projects. In particular, we will identify FAIR convergences between these projects and the data repositories involved in them. The resulting FAIR metrics will be used to derive tests in F-UJI that will be of significant help to the community in assessing the FAIRness of individual datasets.
Expected outputs
- Collection of FAIR Implementation Profiles from this community
- Draft FAIR metrics for the earth & environmental sciences
- Draft community specific FAIR assessments implemented in F-UJI