A Platform to Generate FAIR Data for COVID-19 Clinical Research in Brazil

Vânia Borges, Natalia Queiroz de Oliveira, Henrique Rodrigues, Maria Campos, Giseli Lopes

2022

Abstract

The COVID-19 pandemic and the global actions to address it have highlighted the importance of clinical care data for more detailed studies of the virus and its effects. Extracting and processing such data, in terms of confidentiality issues, is a challenge. In addition, the mechanisms necessary for their publication are aimed at reuse in research to better understand the effects of this pandemic or other viral outbreaks. This paper describes a modular, scalable, distributed, and flexible platform, based on a generic architecture, to promote the publication of FAIR clinical research data. This platform collects heterogeneous data from Electronic Health Records, transforms these data into interconnected and interoperable (meta)data that are processable by software agents, and publishes them through technological solutions such as repositories and FAIR Data Point.

Download


Paper Citation


in Harvard Style

Borges V., Queiroz de Oliveira N., Rodrigues H., Campos M. and Lopes G. (2022). A Platform to Generate FAIR Data for COVID-19 Clinical Research in Brazil. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-569-2, pages 218-225. DOI: 10.5220/0011066800003179


in Bibtex Style

@conference{iceis22,
author={Vânia Borges and Natalia Queiroz de Oliveira and Henrique Rodrigues and Maria Campos and Giseli Lopes},
title={A Platform to Generate FAIR Data for COVID-19 Clinical Research in Brazil},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2022},
pages={218-225},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011066800003179},
isbn={978-989-758-569-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - A Platform to Generate FAIR Data for COVID-19 Clinical Research in Brazil
SN - 978-989-758-569-2
AU - Borges V.
AU - Queiroz de Oliveira N.
AU - Rodrigues H.
AU - Campos M.
AU - Lopes G.
PY - 2022
SP - 218
EP - 225
DO - 10.5220/0011066800003179