FAIR By Design

The FAIR Guiding Principles for scientific data management and stewardship is build upon the use of machine-actionability metadata to find, access, interoperate, combine, and directly reuse data with minimal human intervention.

To improve the quality of the reported data and to maximise the potential for reuse the set of metadata must be sufficient to allow for unambiguous interpretation of the associated data. For metadata management Minimum Information standards are used in the Life Sciences consisting of two parts.

Firstly, for each assay and associated data type there is a community accepted checklist of reporting requirements. Secondly, an obligatory data format is used for reporting essential metadata to ensure machine-actionability.


FAIR Data Tools


FAIR Data Station

Allows users to record meta-data in such a way that it ensures FAIR scientific data management from the start. Online app


CWL Workflows

Reuseable computational workflows written in the Common Workflow Language including provenance.
Take at look at our Workflow Hub.



Our code and tools are open source and free. You can find more at our GitLab repository.



Find and learn more about our FAIR By Design approach at: m-unlock.gitlab.io