New recipe to FAIRify published observational studies and databases

We are proud to present our FAIRplus recipe on how to make published observational research data more FAIR. The recipe describes the work we did on making data on the website of the Covid-19 EHDEN/OHDSI studyathon, held in March 2020, more findable and interoperable.

The recipe clarifies that simply putting research data on a website makes it more findable for humans. However, search engines such as Google dataset search need more information for the data to be findable. You need to add structured metadata to the back-end of the web page to make them findable.

For the Covid-19 studyathon, this meant creating a semantic model for the metadata. Some entities were already present on, but some concepts commonly used in describing observational medical data represented in OMOP were not, such as database characteristics and population size. Therefore, we created an extension of to capture the OHDSI and clinical data-specific metadata.

In the recipe, three major FAIR initiatives come together in which the Hyve is involved:

The new recipe is a follow-up of this use case detailing work we did for the Pistoia Alliance FAIR toolkit.

If you are interested in learning how to make medical studies and databases shared on the internet more findable and interoperable, just read the new recipe and try it for yourself.

This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 802750 and 806968. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA companies.

This communication reflects the views of the authors and neither IMI nor the European Union, EFPIA or any Associated Partners are liable for any use that may be made of the information contained herein.