FAIRness evaluation of WDCC for the paper "Recommendations for discipline-specific FAIRness evaluation derived from applying an ensemble of evaluation tools"


Peters-von Gehlen, Karsten; Hoeck, Heinke

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Results from five different FAIRness evaluation approaches applied to selected data collections archived in the WDCC. These data form the basis for the publication "Recommendations for discipline-specific FAIRness evaluation derived from applying an ensemble of evaluation tools" by Karsten Peters-von Gehlen et al., submitted to Data Science Journal in September 2021.

The applied FAIRness evaluation tools are:
1) Checklist for Fitness for Use (CFU, Austin et al., 2019)
2) F-UJI (Devaraju & Huber, 2020)
3) FAIR Maturity Evaluation Service (FMES, Wilkinson et al., 2019)
4) FAIRshake (Clarke et al., 2019)
5) Self Assessment based on Bahim et al. (2020)

The spreadsheet belonging to each test is evident from the file name.

Calculated mean FAIRscores and cross-correlations between tests are also included.
Karsten Peters-von Gehlen (
Use constraints
Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Data Catalog
World Data Center for Climate
Access constraints
registered users
51.05 KiB (52275 Byte)
completely archived
Creation Date
Future Review Date
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Cite as
Peters-von Gehlen, Karsten; Hoeck, 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

[Entry acronym: Results_from_FAIRness_eval] [Entry id: 3891995]
Contact typePersonORCIDInstitute

Is documented by

[1] DOI Austin, Claire; Cousijn, Helena; Diepenbroek, Michael; Petters, Jonathan; Soares e Silva, Marina. (2019). WDS/RDA Assessment of Data Fitness for Use WG Outputs and Recommendations. doi:10.15497/rda00034
[2] DOI Devaraju, Anusuriya; Huber, Robert. (2020). F-UJI - An Automated FAIR Data Assessment Tool. doi:10.5281/zenodo.4063720
[3] DOI Wilkinson, Mark D.; Dumontier, Michel; Sansone, Susanna-Assunta; Bonino da Silva Santos, Luiz Olavo; Prieto, Mario; Batista, Dominique; McQuilton, Peter; Kuhn, Tobias; Rocca-Serra, Philippe; Crosas, Mercѐ; Schultes, Erik. (2019). Evaluating FAIR maturity through a scalable, automated, community-governed framework. doi:10.1038/s41597-019-0184-5
[4] DOI Clarke, Daniel J.B.; Wang, Lily; Jones, Alex; Wojciechowicz, Megan L.; Torre, Denis; Jagodnik, Kathleen M.; Jenkins, Sherry L.; McQuilton, Peter; Flamholz, Zachary; Silverstein, Moshe C.; Schilder, Brian M.; Robasky, Kimberly; Castillo, Claris; Idaszak, Ray; Ahalt, Stanley C.; Williams, Jason; Schurer, Stephan; Cooper, Daniel J.; de Miranda Azevedo, Ricardo; Klenk, Juergen A.; Haendel, Melissa A.; Nedzel, Jared; Avillach, Paul; Shimoyama, Mary E.; Harris, Rayna M.; Gamble, Meredith; Poten, Rudy; Charbonneau, Amanda L.; Larkin, Jennie; Brown, C. Titus; Bonazzi, Vivien R.; Dumontier, Michel J.; Sansone, Susanna-Assunta; Ma’ayan, Avi. (2019). FAIRshake: Toolkit to Evaluate the FAIRness of Research Digital Resources. doi:10.1016/j.cels.2019.09.011
[5] DOI Bahim, Christophe; Casorrán-Amilburu, Carlos; Dekkers, Makx; Herczog, Edit; Loozen, Nicolas; Repanas, Konstantinos; Russell, Keith; Stall, Shelley. (2020). The FAIR Data Maturity Model: An Approach to Harmonise FAIR Assessments. doi:10.5334/dsj-2020-041


FAIRness of WDCC