Introducing Community Guidelines for Sharing Dataset Quality Information

This presentation introduces the community guidelines for sharing dataset quality information, developed by members of multiple, international groups. The guidelines follow the guiding principles of being findable, accessible, interoperable, and reusable (FAIR). The FAIR dataset quality information guidelines are intended to help stakeholders, such as scientific data centers, digital data repositories, and producers, publishers, stewards and managers of data, to achieve the following: i) capture, describe, and represent quality information of their datasets in a manner that is consistent with the FAIR guiding principles; ii) allow for the maximum discovery, trust, sharing, and reuse of their datasets; and iii) enable international access to and integration of dataset quality information.
Presented at the FAIR-Points webinar on November 30, 2022
{"references":["Peng, G., Lacagnina, C., Ivánová, I., Downs, R. R., Ramapriyan, H., Ganske, A., and others, 2021. International Community Guidelines for Sharing and Reusing Quality Information of Individual Earth Science Datasets. OSF, https://doi.org/10.31219/osf.io/xsu4p. Updated: March 26, 2022","Peng, G., Lacagnina, C., Downs, R.R., Ganske, A., Ramapriyan, H.K., Ivánová, I., Wyborn, L., Jones, D., Bastin, L., Shie, C.-. lin . and Moroni, D.F., 2022. Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets. Data Science Journal, 21, http://doi.org/10.5334/dsj-2022-008","Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., and others, 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, https://doi.org/10.1038/sdata.2016.18"]}