FAIRification workflow: a process for making data FAIR

Under construction

To be able to onboard datasets into the Health-RI infrastructure, requirements will need to be defined. They will include requirements regarding the FAIRness of the dataset. To help data owners making their data FAIR for the onboarding process, we need to define a FAIRification workflow they can follow.

Instead of creating a new FAIRification workflow, we have mapped existing FAIR workflows and processes already in use,​ to identify the important and common steps. Below you find the outcome of this excercise and you can read the details on this mapping process in this poster presentation.

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Currently we are discussing which steps we need within Health-RI and what they actually mean. When we have decided on the steps we will complete the details for each of them on how to perform them (see this example page).

We are also developing FAIR services together with funders, to incorporate FAIR into projects from the start.

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Example of a possible FAIRification steps selection

Further reading: 

• FAIRopoly – FAIRification Guidance for ERN Patient Registries  

• FAIRification framework FAIRplus (article)

• A Generic Workflow for the Data FAIRification Process   

• https://rdmkit.elixir-europe.org/machine_actionability.html  

• FAIR and the notion of metadata   

• F2: Data are described with rich metadata - GO FAIR  

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