Harvesting the Low Hanging Fruits From the FAIRtree

Extensive workflows have been designed to FAIRify data from various domains. These tend to be cumbersome and overwhelming. This work summarises our own experiences with FAIRification in health data management and provides simple steps that can be implemented to achieve a relatively low but improved level of FAIRness. The steps lead the data steward to register the data in a repository and then annotate it with the metadata recommended by that repository. It further leads the data steward to provide the data in a machine-readable format using an established and accessible language, establish a well-defined framework to describe and structure the (meta)data as well as publish the (meta)data. We hope that following the simple roadmap described in this work helps to demystify the FAIR data principles in the health domain.