WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand Challenges
- Autores
- Hodson, Simon
- Año de publicación
- 2023
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- First published in 2016, in an article that has now received over 6000 citations, the FAIR (Findability, Accessibility, Interoperability, Reusability) Principles have had a significant influence in policy, practice and thinking about research data management and stewardship. The catchy mnemonic has been effective, but the article and related work convey an important message. The fundamental purpose of the FAIR principles is to provide guidelines such that data and metadata relevant to all kinds of research outputs are machine readable and machine actionable. The vision is one in which research outputs can be visited online and at vast scale and the potential of machine assisted analysis can be realised, but with data and metadata that are sufficiently reliable so as to reduce error and quantify uncertainty.
Ibero-American Science and Technology Education Consortium - Materia
-
Informática
FAIR principles - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/166799
Ver los metadatos del registro completo
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WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand ChallengesHodson, SimonInformáticaFAIR principlesFirst published in 2016, in an article that has now received over 6000 citations, the FAIR (Findability, Accessibility, Interoperability, Reusability) Principles have had a significant influence in policy, practice and thinking about research data management and stewardship. The catchy mnemonic has been effective, but the article and related work convey an important message. The fundamental purpose of the FAIR principles is to provide guidelines such that data and metadata relevant to all kinds of research outputs are machine readable and machine actionable. The vision is one in which research outputs can be visited online and at vast scale and the potential of machine assisted analysis can be realised, but with data and metadata that are sufficiently reliable so as to reduce error and quantify uncertainty.Ibero-American Science and Technology Education Consortium2023info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionResumenhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf15-16http://sedici.unlp.edu.ar/handle/10915/166799enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-2375-2info:eu-repo/semantics/reference/hdl/10915/166184info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:44:25Zoai:sedici.unlp.edu.ar:10915/166799Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:44:25.946SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand Challenges |
title |
WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand Challenges |
spellingShingle |
WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand Challenges Hodson, Simon Informática FAIR principles |
title_short |
WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand Challenges |
title_full |
WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand Challenges |
title_fullStr |
WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand Challenges |
title_full_unstemmed |
WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand Challenges |
title_sort |
WorldFAIR: Open Science and FAIR Data for Cross-Domain Grand Challenges |
dc.creator.none.fl_str_mv |
Hodson, Simon |
author |
Hodson, Simon |
author_facet |
Hodson, Simon |
author_role |
author |
dc.subject.none.fl_str_mv |
Informática FAIR principles |
topic |
Informática FAIR principles |
dc.description.none.fl_txt_mv |
First published in 2016, in an article that has now received over 6000 citations, the FAIR (Findability, Accessibility, Interoperability, Reusability) Principles have had a significant influence in policy, practice and thinking about research data management and stewardship. The catchy mnemonic has been effective, but the article and related work convey an important message. The fundamental purpose of the FAIR principles is to provide guidelines such that data and metadata relevant to all kinds of research outputs are machine readable and machine actionable. The vision is one in which research outputs can be visited online and at vast scale and the potential of machine assisted analysis can be realised, but with data and metadata that are sufficiently reliable so as to reduce error and quantify uncertainty. Ibero-American Science and Technology Education Consortium |
description |
First published in 2016, in an article that has now received over 6000 citations, the FAIR (Findability, Accessibility, Interoperability, Reusability) Principles have had a significant influence in policy, practice and thinking about research data management and stewardship. The catchy mnemonic has been effective, but the article and related work convey an important message. The fundamental purpose of the FAIR principles is to provide guidelines such that data and metadata relevant to all kinds of research outputs are machine readable and machine actionable. The vision is one in which research outputs can be visited online and at vast scale and the potential of machine assisted analysis can be realised, but with data and metadata that are sufficiently reliable so as to reduce error and quantify uncertainty. |
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2023 |
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2023 |
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