COVID-19 Research Data: Findable but Far From Fully Usable – What Needs to Change for Future Pandemics?

The COVID-19 pandemic research generated a lot of data that we can use to make better decisions for the next pandemic, right?

Well, it's complicated...

Our new meta-research study, "COVID-19-related research data availability and quality according to the FAIR principles," evaluates the compliance of COVID-19-related research data with the FAIR principles (Findable, Accessible, Interoperable, and Reusable).

Key findings:

• Data accessibility and interoperability remain significant challenges, with only 21.5% of datasets being accessible and 46.7% meeting interoperability standards.
• The choice of repository was the strongest factor influencing FAIRness, with Harvard Dataverse achieving the highest scores.
• While Findability was universally strong, improvements are critically needed in Reusability and Interoperability to maximize the value of shared data.

This study highlights the gaps that must be addressed to ensure research data is not just shared, but actually usable in times of global need.

Read the full paper here: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0313991