Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

Status
colourPurple
titlestatus: Future work

Short description 

FAIRification is a continuous process. If you have not yet reached all of your objectives, you can decide to restart the process and further optimise it to reach more of your goals [FAIRopoly].  

An approach to review the overall success of can be to have individuals not directly involved in the practical implementation work, but familiar with the overall data, reviewing of the outcomes of the FAIRification work against the initial goals [FAIRPlusFAIRinAction]. This provides independent feedback and prevents the danger for work to continue beyond the point where the benefits exceed the cost. 

Furthermore, other types of results, such as lessons learned and developed recipes can be disseminated for the benefit of the community [FAIRPlusFAIRinAction]. 

 

---  

FAIRopoly 

FAIRification is a continuous process, do not get discouraged by achieving only some of your goals. If that is the case, it may be time to reassess and restart the process optimising it to your project priorities. 

...

Developed recipes are shared publicly in the cookbook. If applicable, update FAIRness levels in IMI catalogue.  Integrate lessons learnt with other initiatives e.g. Pistoia FAIR toolkit, RDMKit 

Working Group

Why is this step important 

...

Furthermore, by disseminating lessons learned, new recipes etc, others can learn from your experience and perhaps reuse your methods.  

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 

This section should help complete the step. It’s crucial that this is practical, doable and scalable. 

...

Sub headers if relevant for specific domains? 

Practical Examples from the Community 

This section should show the step applied in a real project. Links to demonstrator projects.  

References & Further reading

[FAIRopoly] FAIRopoly https://www.ejprarediseases.org/fairopoly/  

[Generic] A Generic Workflow for the Data FAIRification Process: https://direct.mit.edu/dint/article/2/1-2/56/9988/A-Generic-Workflow-for-the-Data-FAIRification   

[Elixir] https://faircookbook.elixir-europe.org/content/recipes/introduction/fairification-process.html   

[Elixir2] A framework for FAIRification processes: https://faircookbook.elixir-europe.org/content/recipes/introduction/metadata-fair.html   

[GOFAIR] https://www.go-fair.org/fair-principles/f2-data-described-rich-metadata/  

[RDMkit] https://rdmkit.elixir-europe.org/machine_actionability.html  

[De Novo] https://ojrd.biomedcentral.com/articles/10.1186/s13023-021-02004-y  

 

 

[FAIRPlus] https://www.nature.com/articles/s41597-023-02167-2  

Authors / Contributors 

Experts who contributed to this step and whom you can contact for further information The How to section should:

  • be split into easy to follow steps;

    • Step 1

    • Step 2

    • etc.

  • help the reader to complete the step;

  • aspire to be readable for everyone, but, depending on the topic, may require specialised knowledge;

  • be a general, widely applicable approach;

  • if possible / applicable, add (links to) the solution necessary for onboarding in the Health-RI National Catalogue;

  • aim to be practical and simple, while keeping in mind: if I would come to this page looking for a solution to this problem, would this How-to actually help me solve this problem;

  • contain references to solutions such as those provided by FAIR Cookbook, RMDkit, Turing way and FAIR Sharing;

  • contain custom recipes/best-practices written by/together with experts from the field if necessary. 

Expertise requirements for this step 

Describes the expertise that may be necessary for this step. Should be based on the expertise described in the Metroline: Build the team step.

Practical examples from the community 

Examples of how this step is applied in a project (link to demonstrator projects).  

Training

Add links to training resources relevant for this step. Since the training aspect is still under development, currently many steps have “Relevant training will be added in the future if available.” 

Suggestions

Visit our How to contribute page for information on how to get in touch if you have any suggestions about this page.