ABSTRACT
Since their proposal in 2016, the FAIR principles have been largely discussed by different communities and initiatives involved in the development of infrastructures to enhance support for data findability, accessibility, interoperability, and reuse. One of the challenges in implementing these principles lies in defining a well-delimited process with organized and detailed actions. This paper presents a workflow of actions that is being adopted in the VODAN BR pilot for generating FAIR (meta)data for COVID-19 research. It provides the understanding of each step of the process, establishing their contribution. In this work, we also evaluate potential tools to (semi)automatize (meta)data treatment whenever possible. Although defined for a particular use case, it is expected that this workflow can be applied for other epidemical research and in other domains, benefiting the entire scientific community.
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. Copyright © 2022 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
ABSTRACT
Since their proposal in 2016, the FAIR principles have been largely discussed by different communities and initiatives involved in the development of infrastructures to enhance support for data findability, accessibility, interoperability, and reuse. One of the challenges in implementing these principles lies in defining a well-delimited process with organized and detailed actions. This paper presents a workflow of actions that is being adopted in the VODAN BR pilot for generating FAIR (meta)data for COVID-19 research. It provides the understanding of each step of the process, establishing their contribution. In this work, we also evaluate potential tools to (semi)automatize (meta)data treatment whenever possible. Although defined for a particular use case, it is expected that this workflow can be applied for other epidemical research and in other domains, benefiting the entire scientific community. © 2022, Springer Nature Switzerland AG.