Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets.
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Open-source science builds on open and free resources that include data, metadata, software, and workflows. Informed decisions on whether and how to (re)use digital datasets are dependent on an understanding about the quality of the underpinning data and relevant information. However, quality information, being difficult to curate and often context specific, is currently not readily available for sharing within and across disciplines. To help address this challenge and promote the creation and (re) use of freely and openly shared information about the quality of individual datasets, members of several groups around the world have undertaken an effort to develop international community guidelines with practical recommendations for the Earth science community, collaborating with international domain experts. The guidelines were inspired by the guiding principles of being findable, accessible, interoperable, and reusable (FAIR). Use of the FAIR dataset quality informa.....
JournalData Science Journal
Sustainable Development Goals (SDG)14.a
DOI Originalhttps://doi. org/10.5334/dsj-2022-008
CitationPeng, G., Lacagnina, C., Downs, R.R., Ganske, A., Ramapriyan, H.K., Ivánová, I., Wyborn, L., Jones, D., Bastin, L., Shie, C.-L. and Moroni, D.F., 2022. Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets. Data Science Journal, 21:008, 20pp.. DOI: http://doi.org/10.5334/dsj-2022-008
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