Implementation Solutions for FAIR Clinical Research Data Management

被引：0

作者：

Borges, Vania ^{[1
]}

de Oliveira, Natalia Queiroz ^{[1
]}

Rodrigues, Henrique F. ^{[1
]}

Luiza Machado Campos, Maria ^{[1
]}

Lopes, Giseli Rabello ^{[1
]}

机构：

[1] Univ Fed Rio de Janeiro, Rio De Janeiro, Brazil

来源：

ENTERPRISE INFORMATION SYSTEMS, ICEIS 2022 | 2023年 / 487卷

关键词：

VODAN Brazil; FAIRification; ETL4FAIR; Clinical Research Platform; FAIR Data Point;

D O I：

10.1007/978-3-031-39386-0_4

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The COVID-19 pandemic and its global actions have emphasized the importance of more detailed clinical data for studies of diseases and their effects. However, collecting and processing these data and publishing them according to rules defined by the responsible institutions is challenging. This paper addresses a modular, scalable, distributed, and flexible platform to promote such processing and publication in a FAIR manner. In addition, we describe approaches adopted to automate the FAIRification phase activities. A proposal for a FAIR Data Point on the cloud is also presented, aiming to improve the scalability of the metadata repository.

引用

页码：64 / 82

页数：19

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