FAIR principles allied to data access and reuse

analysis of Covid-19 datasets from PubChem repository

Abstract

This article aims to verify alignment with FAIR principles in health research data sharing and analyze its potential reuse in the Covid-19 health crisis. It uses a theoretical-descriptive, bibliographic, and exploratory approach to establish criteria for selecting the pilot theme, the data source, and the analysis tool.  The pilot theme was chosen, a drug that has been widely debated in the scientific and media field, for the treatment of Covid-19, Chloroquine. As a source of analysis it uses the chemical disciplinary repository PubChem and FairDataBR as an analysis tool to check the level of adherence of the selected datasets to the FAIR principles in a semi-automated way. As a result, it points out that the Accessible and Reusable principles (scores 8.33 and 8.20) obtained the highest scores, mainly due to ease of access, downloading and sharing. On the other hand, the Findable and Interoperable principles (scores 5.20 and 7.75) performed less well because they do not use persistent identifiers in all the available sets and do not make use of a metadata schema formalized by the chemical community. It concludes that, with respect to FAIR principles, there is partial alignment of the Chloroquine datasets deposited in PubChem. Thus, the analysis shows a reuse potential of (average of scores 7.37), as all principles support reuse. Finally, it reaffirms that for data to be FAIR, the ecosystem needs to be FAIR, so some measures should be taken by PubChem to support data generation, such as the designation or mandatory insertion of persistent identifiers.