Short Description
In this step in the post-FAIRification phase check whether you managed to reach the FAIRification goals you set initially [Generic]. If your goals have not yet been met, you may need to revisit some of the earlier steps, or, if that is unfeasible, you may need to adjust your goals. Furthermore, you can check the FAIRness of your (meta)data using FAIRness assessment tooling. If initially a pre-FAIR assessment was also done (step 5), you can compare the results from the pre- and post-FAIRification assessment. Also, such tooling can help track the progress towards FAIRness of your data [FAIRopoly].
Working Group
Why is this step important
You set out with FAIR goals in mind and this step will help you assess whether you reached them and can help you pinpoint where further work is necessary.
...
Q: is there movement towards journals demanding some form of formal statistics when claims towards FAIRness of data are made? If so, that should be added here, since you’d need to objectively assess FAIRness for publications.
Expertise requirements for this step
This section could describe the expertise required. Perhaps the Build Your Team step could then be an aggregation of all the “Expertise requirements for this step” steps that someone needs to fulfil his/her FAIRification goals.
How to
Using FIPs to assess FAIRness?
FAIR cookbook has a chapter about this topic: https://faircookbook.elixir-europe.org/content/recipes/assessing-fairness.html
...
This phase is usually run in short sprints of 3-month.
Practical Examples from the Community
This section should show the step applied in a real project. Links to demonstrator projects.
Further reading & References
[FAIRopoly] FAIRopoly https://www.ejprarediseases.org/fairopoly/
...
[De Novo] https://ojrd.biomedcentral.com/articles/10.1186/s13023-021-02004-y
Authors / Contributors
Experts who contributed to this step and whom you can contact for further information