Title: A practical FAIRification workflow for clinical research data: challenges and solutions in the virus outbreak data network Brazil

Authors: Natália Queiroz de Oliveira; Vânia Borges; Henrique Fernandes Rodrigues; Maria Luiza Machado Campos; Giseli Rabello Lopes

Addresses: Programa de Pós-Graduação em Informática (PPGI), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil ' Programa de Pós-Graduação em Informática (PPGI), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil ' Programa de Pós-Graduação em Informática (PPGI), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil ' Programa de Pós-Graduação em Informática (PPGI), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil ' Programa de Pós-Graduação em Informática (PPGI), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil

Abstract: The FAIR (Findable, Accessible, Interoperable, Reusable) principles and their adoption as best practices in data management have increased the publication of research data and associated metadata. The relevance of clinical care data for further in-depth research on the virus and its consequences has been brought to light by the COVID-19 pandemic and the global efforts to combat it. This paper presents a practical FAIRification workflow for the transformation and publication of clinical research data into FAIR (meta)data. It is an extended version of a practical FAIRification workflow approach validated in the Virus Outbreak Data Network Brazil (VODAN BR) pilot. Furthermore, it discusses how the FAIRification process contributes to reproducible clinical research data and presents lessons learned with the development of this process.

Keywords: FAIRification workflow; clinical research data; FAIR (meta)data; ETL4FAIR framework; VODAN.

DOI: 10.1504/IJMSO.2023.140702

International Journal of Metadata, Semantics and Ontologies, 2023 Vol.16 No.4, pp.278 - 297

Received: 22 Sep 2022
Accepted: 08 Dec 2023
Published online: 30 Aug 2024 *

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