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From FAIR to FAIRS: Data security by design for the global burden of animal diseases

Solving complex global problems involving data and data analysis can require data from both the public and private sectors. The sharing of data has traditionally been restricted to open data. To facilitate the use of both open and private data, a new data‐sharing framework has been constructed as an...

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Autores principales: Stacey, Deborah, Wulff, Kenneth, Chikhalla, Nidhip, Bernardo, Theresa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9790701/
https://www.ncbi.nlm.nih.gov/pubmed/36590757
http://dx.doi.org/10.1002/agj2.21017
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author Stacey, Deborah
Wulff, Kenneth
Chikhalla, Nidhip
Bernardo, Theresa
author_facet Stacey, Deborah
Wulff, Kenneth
Chikhalla, Nidhip
Bernardo, Theresa
author_sort Stacey, Deborah
collection PubMed
description Solving complex global problems involving data and data analysis can require data from both the public and private sectors. The sharing of data has traditionally been restricted to open data. To facilitate the use of both open and private data, a new data‐sharing framework has been constructed as an extension to the popular Findable‐Accessible‐Interoperable‐Reusable (FAIR) framework. The “Secure by Design” approach has been taken to define the FAIRS data‐sharing framework where S stands for Secure. A Cloud infrastructure architecture is proposed that would allow data brokers to implement FAIRS. This architecture is being constructed for the Global Burden of Animal Diseases (GBADs) to facilitate the sharing of livestock data.
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spelling pubmed-97907012022-12-28 From FAIR to FAIRS: Data security by design for the global burden of animal diseases Stacey, Deborah Wulff, Kenneth Chikhalla, Nidhip Bernardo, Theresa Agron J Special Section: Big Data Promises and Obstacles: Agricultural Data Ownership and Privacy Solving complex global problems involving data and data analysis can require data from both the public and private sectors. The sharing of data has traditionally been restricted to open data. To facilitate the use of both open and private data, a new data‐sharing framework has been constructed as an extension to the popular Findable‐Accessible‐Interoperable‐Reusable (FAIR) framework. The “Secure by Design” approach has been taken to define the FAIRS data‐sharing framework where S stands for Secure. A Cloud infrastructure architecture is proposed that would allow data brokers to implement FAIRS. This architecture is being constructed for the Global Burden of Animal Diseases (GBADs) to facilitate the sharing of livestock data. John Wiley and Sons Inc. 2022-03-30 2022 /pmc/articles/PMC9790701/ /pubmed/36590757 http://dx.doi.org/10.1002/agj2.21017 Text en © 2022 The Authors. Agronomy Journal published by Wiley Periodicals LLC on behalf of American Society of Agronomy. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Special Section: Big Data Promises and Obstacles: Agricultural Data Ownership and Privacy
Stacey, Deborah
Wulff, Kenneth
Chikhalla, Nidhip
Bernardo, Theresa
From FAIR to FAIRS: Data security by design for the global burden of animal diseases
title From FAIR to FAIRS: Data security by design for the global burden of animal diseases
title_full From FAIR to FAIRS: Data security by design for the global burden of animal diseases
title_fullStr From FAIR to FAIRS: Data security by design for the global burden of animal diseases
title_full_unstemmed From FAIR to FAIRS: Data security by design for the global burden of animal diseases
title_short From FAIR to FAIRS: Data security by design for the global burden of animal diseases
title_sort from fair to fairs: data security by design for the global burden of animal diseases
topic Special Section: Big Data Promises and Obstacles: Agricultural Data Ownership and Privacy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9790701/
https://www.ncbi.nlm.nih.gov/pubmed/36590757
http://dx.doi.org/10.1002/agj2.21017
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