DBIRQMJan 19, 2022

A Practical Approach of Actions for FAIRification Workflows

arXiv:2201.07866v13 citations
Originality Synthesis-oriented
AI Analysis

It addresses the problem of defining organized processes for FAIRification, potentially benefiting scientific communities in epidemiological and other domains, though it appears incremental.

This paper tackles the challenge of implementing FAIR principles by presenting a workflow of actions adopted in the VODAN BR pilot to generate FAIR metadata for COVID-19 research, with an evaluation of tools for semi-automation.

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.

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