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|Title:||GO FAIR Brazil: a challenge for brazilian data science|
Veiga, Viviane Santos de Oliveira
Costa, Maira Murrieta
Sayão, Luís Fernando
Santos, Luiz Olavo Bonino da Silva
Pires, Luís Ferreira
|Affilliation:||Instituto 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.
|Abstract:||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.|
GO FAIR Brazil
|Citation:||SALES, Luana et al. GO FAIR Brazil: a challenge for brazilian data science. Data Intelligence, v. 2, n. 2020, p. 238–245, 2019.|
|Appears in Collections:||ICICT - Artigos de Periódicos|
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