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Modeling community standards for metadata as templates makes data FAIR
It is challenging to determine whether datasets are findable, accessible, interoperable, and reusable (FAIR) because the FAIR Guiding Principles refer to highly idiosyncratic criteria regarding the metadata used to annotate datasets. Specifically, the FAIR principles require metadata to be “rich” an...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653497/ https://www.ncbi.nlm.nih.gov/pubmed/36371407 http://dx.doi.org/10.1038/s41597-022-01815-3 |
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author | Musen, Mark A. O’Connor, Martin J. Schultes, Erik Martínez-Romero, Marcos Hardi, Josef Graybeal, John |
author_facet | Musen, Mark A. O’Connor, Martin J. Schultes, Erik Martínez-Romero, Marcos Hardi, Josef Graybeal, John |
author_sort | Musen, Mark A. |
collection | PubMed |
description | It is challenging to determine whether datasets are findable, accessible, interoperable, and reusable (FAIR) because the FAIR Guiding Principles refer to highly idiosyncratic criteria regarding the metadata used to annotate datasets. Specifically, the FAIR principles require metadata to be “rich” and to adhere to “domain-relevant” community standards. Scientific communities should be able to define their own machine-actionable templates for metadata that encode these “rich,” discipline-specific elements. We have explored this template-based approach in the context of two software systems. One system is the CEDAR Workbench, which investigators use to author new metadata. The other is the FAIRware Workbench, which evaluates the metadata of archived datasets for their adherence to community standards. Benefits accrue when templates for metadata become central elements in an ecosystem of tools to manage online datasets—both because the templates serve as a community reference for what constitutes FAIR data, and because they embody that perspective in a form that can be distributed among a variety of software applications to assist with data stewardship and data sharing. |
format | Online Article Text |
id | pubmed-9653497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96534972022-11-15 Modeling community standards for metadata as templates makes data FAIR Musen, Mark A. O’Connor, Martin J. Schultes, Erik Martínez-Romero, Marcos Hardi, Josef Graybeal, John Sci Data Article It is challenging to determine whether datasets are findable, accessible, interoperable, and reusable (FAIR) because the FAIR Guiding Principles refer to highly idiosyncratic criteria regarding the metadata used to annotate datasets. Specifically, the FAIR principles require metadata to be “rich” and to adhere to “domain-relevant” community standards. Scientific communities should be able to define their own machine-actionable templates for metadata that encode these “rich,” discipline-specific elements. We have explored this template-based approach in the context of two software systems. One system is the CEDAR Workbench, which investigators use to author new metadata. The other is the FAIRware Workbench, which evaluates the metadata of archived datasets for their adherence to community standards. Benefits accrue when templates for metadata become central elements in an ecosystem of tools to manage online datasets—both because the templates serve as a community reference for what constitutes FAIR data, and because they embody that perspective in a form that can be distributed among a variety of software applications to assist with data stewardship and data sharing. Nature Publishing Group UK 2022-11-12 /pmc/articles/PMC9653497/ /pubmed/36371407 http://dx.doi.org/10.1038/s41597-022-01815-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Musen, Mark A. O’Connor, Martin J. Schultes, Erik Martínez-Romero, Marcos Hardi, Josef Graybeal, John Modeling community standards for metadata as templates makes data FAIR |
title | Modeling community standards for metadata as templates makes data FAIR |
title_full | Modeling community standards for metadata as templates makes data FAIR |
title_fullStr | Modeling community standards for metadata as templates makes data FAIR |
title_full_unstemmed | Modeling community standards for metadata as templates makes data FAIR |
title_short | Modeling community standards for metadata as templates makes data FAIR |
title_sort | modeling community standards for metadata as templates makes data fair |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653497/ https://www.ncbi.nlm.nih.gov/pubmed/36371407 http://dx.doi.org/10.1038/s41597-022-01815-3 |
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