FAIRness of DKRZ's LTA WDCC service
The WDCC is aligned with the FAIR Guiding Principles for scientific data management and stewardship. These has become one of, if not the most frequently required aspect in data management.
DKRZ is committed to ensure the FAIRness of research data through signing the COPDESS (Coalition on Publishing Data in the Earth and Space Sciences) Commitment in June 2018. Specifically, the native philosophy behind DKRZ's long-term archiving service LTA WDCC reflects the FAIR data principles by design - and even goes beyond them by ensuring very long-term (>10 years) preservation and therefore long-term reusability of archived data (see below for details).
In the context of the discipline specific datasets archived in LTA WDCC, we recap the FAIR data guiding principles as standing for (meta)data being
- data and metadata are easy to find by both humans and machines and are assigned globally resolvable identifiers
- limitations on the use of data (licenses), and access mechanisms are made explicit for both humans and machines
- data and metadata comply with community specific file formats and (meta)data standards such that they can readily combined with other data
- data are associated with ample metadata, documentation and uncertainty estimates such that the scope of the re-use becomes immediately clear to the re-user
In order to substantiate our assertion of offering FAIR climate data in the WDCC archive, we have assessed a representative subset of WDCC’s data holdings. We did so by applying five different FAIRness evaluation approaches. The results of this assessment are published as peer-reviewed research paper in the Data Science Journal (Peters-von Gehlen et al. (2022), underlying data are provided in Peters-von Gehlen (2021) and Peters-von Gehlen and Höck (2021)). The paper also provides recommendations for the future of assessing domain-specific FAIRness.
Peters-von Gehlen, Karsten (2021). F-UJI evaluation output for the paper "Recommendations for discipline-specific FAIRness evaluation derived from applying an ensemble of evaluation tools". World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.35095/WDCC/F-UJI_results_WDCC
Peters-von Gehlen, Karsten; Höck, Heinke (2021). Data underlying the publication "Recommendations for discipline-specific FAIRness evaluation derived from applying an ensemble of evaluation tools". World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.35095/WDCC/Results_from_FAIRness_eval
Peters-von Gehlen, Karsten; Höck, Heinke; Fast, Andrej; Heydebreck, Daniel; Lammert, Andrea; Thiemann, Hannes (2022). Recommendations for Discipline-Specific FAIRness Evaluation Derived from Applying an Ensemble of Evaluation Tools. Data Science Journal, 21(1), p.7. https://doi.org/10.5334/dsj-2022-007