David, Romain
Mabile, Laurence
Specht, Alison
Stryeck, Sarah
Thomsen, Mogens
Yahia, Mohamed
Jonquet, Clement
Dollé, Laurent
Jacob, Daniel
Bailo, Daniele
Bravo, Helena
Gachet, Sophie
Gunderman, Hannah
Hollebecq, Jean-Eudes
Ioannidis, Vassilios
Le Bras, Yvan
Lerigoleur, Emilie
Cambon-Thomsen, Anne
SHARC Community
2020-06-29
<p>The SHARC Interest Group of the Research Data Alliance was established to improve research crediting and rewarding mechanisms for scientists who wish to organise their data (and material resources) for community sharing. This requires that data are findable and accessible on the Web, and comply with shared standards making them interoperable and reusable in alignment with the FAIR principles. It takes considerable time, energy, expertise and motivation. It is imperative to facilitate the processes to encourage scientists to share their data. To that aim, supporting FAIR principles compliance processes and increasing the human understanding of FAIRness criteria – i.e., promoting FAIRness literacy – and not only the machine-readability of the criteria, are critical steps in the data sharing process. Appropriate human-understandable criteria must be the first identified in the FAIRness assessment processes and roadmap. This document is a reusable template that aims to support FAIRification assessment with human understandable criteria. The level of compliance for each criterion can be used to prioritise the most appropriate and sufficient training, support and actions.</p>
https://doi.org/10.5281/zenodo.3922069
oai:zenodo.org:3922069
eng
Zenodo
https://zenodo.org/communities/rda-sharcig
https://zenodo.org/communities/rda-related
https://doi.org/10.5281/zenodo.3922068
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR principles; FAIRness literacy; FAIR assessment, Research data sharing; FAIRification; Pre-FAIRification;
Templates for FAIRness evaluation criteria - RDA-SHARC ig
info:eu-repo/semantics/other