GO FAIR Brazil: a challenge for brazilian data science
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da FIOCRUZ (ARCA) |
Texto Completo: | https://www.arca.fiocruz.br/handle/icict/37518 |
Resumo: | Instituto Brasileiro em Informação em Ciência e Tecnologia. Rio de Janeiro, RJ, Brasil. |
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Sales, Luana FariasHenning, Patrícia CorrêaVeiga, Viviane Santos de OliveiraCosta, Maira MurrietaSayão, Luís FernandoSantos, Luiz Olavo Bonino da SilvaPires, Luís Ferreira2019-12-02T13:29:28Z2019-12-02T13:29:28Z2019SALES, Luana Farias et al. GO FAIR Brazil: a challenge for brazilian data science. Data Intelligence, v. 2, n. 2020, p. 238-245, 2019.https://www.arca.fiocruz.br/handle/icict/3751810.1162/dint_a_000462641-435XporData IntelligenceGO FAIR Brazil: a challenge for brazilian data scienceinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleInstituto Brasileiro em Informação em Ciência e Tecnologia. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.Ministério da Ciência, Tecnologia, Inovações e Comunicações. Brasília, DF, Brasil.Comissão Nacional de Energia Nuclear. Rio de Janeiro, RJ, Brasil.GO FAIR International Support & Coordination Office (GFISCO). Leiden, Netherlands.University of Twente. Enschede, Netherlands.The FAIR principles, an acronym for Findable, Accessible, Interoperable and Reusable, are recognised worldwide as key elements for good practice in all data management processes. To understand how the Brazilian scientific community is adhering to these principles, this article reports Brazilian adherence to the GO FAIR initiative through the creation of the GO FAIR Brazil Office and the manner in which they create their implementation networks. To contextualise this understanding, we provide a brief presentation of open data policies in Brazilian research and government, and finally, we describe a model that has been adopted for the GO FAIR Brazil implementation networks. The Brazilian Institute of Information in Science and Technology is responsible for the GO FAIR Brazil Office, which operates in all fields of knowledge and supports thematic implementation networks. Today, GO FAIR Brazil-Health is the first active implementation network in operation, which works in all health domains, serving as a model for other fields like agriculture, nuclear energy, and digital humanities, which are in the process of adherence negotiation. This report demonstrates the strong interest and effort from the Brazilian scientific communities in implementing the FAIR principles in their research data management practices.FAIR principlesGO FAIRGO FAIR BrazilOpen ScienceResearch datainfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-83128https://www.arca.fiocruz.br/bitstream/icict/37518/1/license.txt0a01a23320286399b52cf17eb1aafb12MD51ORIGINAL23824-Luana_Sales-33_YV8hCml.pdf23824-Luana_Sales-33_YV8hCml.pdfapplication/pdf2442421https://www.arca.fiocruz.br/bitstream/icict/37518/2/23824-Luana_Sales-33_YV8hCml.pdf60378bb7a3ad3418ebb48deab1029784MD52TEXT23824-Luana_Sales-33_YV8hCml.pdf.txt23824-Luana_Sales-33_YV8hCml.pdf.txtExtracted 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dc.title.pt_BR.fl_str_mv |
GO FAIR Brazil: a challenge for brazilian data science |
title |
GO FAIR Brazil: a challenge for brazilian data science |
spellingShingle |
GO FAIR Brazil: a challenge for brazilian data science Sales, Luana Farias FAIR principles GO FAIR GO FAIR Brazil Open Science Research data |
title_short |
GO FAIR Brazil: a challenge for brazilian data science |
title_full |
GO FAIR Brazil: a challenge for brazilian data science |
title_fullStr |
GO FAIR Brazil: a challenge for brazilian data science |
title_full_unstemmed |
GO FAIR Brazil: a challenge for brazilian data science |
title_sort |
GO FAIR Brazil: a challenge for brazilian data science |
author |
Sales, Luana Farias |
author_facet |
Sales, Luana Farias Henning, Patrícia Corrêa Veiga, Viviane Santos de Oliveira Costa, Maira Murrieta Sayão, Luís Fernando Santos, Luiz Olavo Bonino da Silva Pires, Luís Ferreira |
author_role |
author |
author2 |
Henning, Patrícia Corrêa Veiga, Viviane Santos de Oliveira Costa, Maira Murrieta Sayão, Luís Fernando Santos, Luiz Olavo Bonino da Silva Pires, Luís Ferreira |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Sales, Luana Farias Henning, Patrícia Corrêa Veiga, Viviane Santos de Oliveira Costa, Maira Murrieta Sayão, Luís Fernando Santos, Luiz Olavo Bonino da Silva Pires, Luís Ferreira |
dc.subject.en.pt_BR.fl_str_mv |
FAIR principles GO FAIR GO FAIR Brazil Open Science Research data |
topic |
FAIR principles GO FAIR GO FAIR Brazil Open Science Research data |
description |
Instituto Brasileiro em Informação em Ciência e Tecnologia. Rio de Janeiro, RJ, Brasil. |
publishDate |
2019 |
dc.date.accessioned.fl_str_mv |
2019-12-02T13:29:28Z |
dc.date.available.fl_str_mv |
2019-12-02T13:29:28Z |
dc.date.issued.fl_str_mv |
2019 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
SALES, Luana Farias et al. GO FAIR Brazil: a challenge for brazilian data science. Data Intelligence, v. 2, n. 2020, p. 238-245, 2019. |
dc.identifier.uri.fl_str_mv |
https://www.arca.fiocruz.br/handle/icict/37518 |
dc.identifier.doi.pt_BR.fl_str_mv |
10.1162/dint_a_00046 |
dc.identifier.eissn.pt_BR.fl_str_mv |
2641-435X |
identifier_str_mv |
SALES, Luana Farias et al. GO FAIR Brazil: a challenge for brazilian data science. Data Intelligence, v. 2, n. 2020, p. 238-245, 2019. 10.1162/dint_a_00046 2641-435X |
url |
https://www.arca.fiocruz.br/handle/icict/37518 |
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por |
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por |
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info:eu-repo/semantics/openAccess |
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openAccess |
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Data Intelligence |
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Data Intelligence |
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