Proposal for a model of research data management service

• Autor(a) principal: Sales, Luana Farias
• Data de Publicação: 2023
• Outros Autores: Sayão, Luís Fernando
• Tipo de documento: Artigo
• Idioma: por; eng
• Título da fonte: AtoZ (Curitiba)
• Texto Completo: https://revistas.ufpr.br/atoz/article/view/85765
• topic: Research data management services; FAIR data; Scientific knowledge management.; Ciência da Informação; Serviços de gestão de dados de pesquisa; Dados FAIR; Gestão do conhecimento científico.

The planning, development, implementation, and operation of research data management platforms involves many variables that need to be properly addressed. The design of these platforms constitutes a complex and multifaceted problem, of which the solution needs to be manifested in the form of services that meet the needs of research flows in specific disciplinary domains, informational, technological and scientific parameters, varied professional profiles, political, legal and ethical constraints, and economic and temporal sustainability. In this multifaceted environment of contemporary science, the question we intend to answer is: What types of data management services can be offered based on the workflows of the scientific environment, considering the peculiarities of the disciplinary domains and serving as a support mechanism for the development of research and encouraging the sharing and reuse of scientific data? As an answer to the question, theoretical-exploratory research was developed that took as a methodological basis the analysis of the literature in the area, with special emphasis on articles, reports, manuals and data infrastructure projects, prepared by researchers and research institutions, giving prominence to the observation points of the actors most closely involved in the issue. From the interrelationship of the diverse variables raised, the result is the description of a set of services that can be offered, organized in a service model. It is hoped that this model can serve as a guide for research institutions that wish to implement data management platforms closer to their communities and that follow the standards and traditions of sharing and reusing scientific data from their researchers.