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This step will help you assess the current FAIRness level of your data. Comparing the current FAIRness to the previously defined FAIRification objectives will help you shape the necessary steps and requirements needed to achieve your FAIRification goals and help you create your
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Another promising development is the FAIR Implementation Profile (FIP). A FIP is a collection of FAIR implementation choices made for all FAIR Principles by a community (for example a research project or an institute). It was developed by the GO FAIR Foundation.
Once published, a FIP can be reused by others, thus acting as a recipe for making data FAIR by a community based on agreements and standards within that community. Therefore, a FIP aids in achieving FAIR principle R1.3, which states that “(Meta)data meet domain-relevant community standards.". A FIP can, in the future, potentially be used to compare your currently used FAIR implementation choices, such as standards used in your dataset, to those used by your community, thus providing a Pre-FAIR score. FIPs and their usage are currently still under active development. For more information, see Creating a FAIR Implementation Profile (FIP), FIP Mini Questionnaire and the FIP Datastewardship Data Stewardship Wizard.
Step 3
Generally, doing pre-FAIR assessments will require the expertise of a data steward to get a reliable value. Once you’ve familiarised yourself with the tool you intend to use, involve the necessary experts for the final evaluation.
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Tools and resources on this page
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Online self-assessment surveys
Online (Semi-) automated tests
FIPs
Training
Relevant training will be added in the future if available.
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