A Generic Workflow for the Data FAIRification Process

The process of making data FAIR (“FAIRification”) can be described in multiple steps. Figure 1 shows a generic step-by-step workflow for the process of making data FAIR (“FAIRification”). The workflow is divided  into  three  “phases”:  Pre-FAIRification,  FAIRification,  and  Post-FAIRification  (dark  grey  boxes)  that  are  further  specified  by  “steps”  indicating  typical  aspects  of  practical  FAIRification  (light  grey  boxes):  1)  identify  FAIRification objective, 2) analyze data, 3) analyze metadata, 4a) define semantic data model, 4b) define semantic metadata model, 5a) make data linkable, 5b) make metadata linkable, 6) host FAIR data, and 7) assess FAIR data.

The order is not strict and can be iterative.