FAIRification process

The “FAIRification” is the process of transforming non-FAIR data into data which follows the four FAIR principles presented in chapter FAIR Principles. The “FAIRification” process, as presented here, is composed by four steps:

• Metadata standardization: is the description of metadata using a formal, accessible, shared, and broadly applicable language for knowledge representation by adoption of metadata standards.

• Data standardization: is the transformation of original data (non-FAIR) using a formal, accessible, shared, and broadly applicable language for knowledge representation by the adoption of data vocabularies that follow FAIR principles and include qualified references to other data.

• Assign license: choosing and assigning a license for the dataset and documenting it using FAIR resources.

• Deploy and Publishing data: preparing data to be published in a FAIR enabled data repository and generating a persistent unique identifier for published datasets.

Warning

Although license information is part of the metadata, we have incorporated the license assignment as a separate step in the FAIRification process to highlight its importance. The absence of an explicit license may prevent others to reuse data, even if the data is intended to be open access.

Note

Deploying and publishing your data is optional for non-open/private datasets. But metadata MUST be deployed and published.