Short Description 

Once you’ve build your team, you can assess training needs. If expertise is missing from your team a variety of trainings are available. 

Literature?? 

Why is this step important 

This section should explain why this step is crucial 

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. 

Depending on the type of step, this can, for example, be a reference to one or more (doable) recipes, or perhaps some form of checklist? The recipes/best-practices presented should be based on experts from the field. 

This should probably be a subpage so as not to have too much text on this page.  

References, if relevant, to FAIRCookbook, RDMKit, GOFAIR?  

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. 

Further reading & References 

<since the descriptions are mostly based on the references below, I put them in the template...> 

[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  

Authors / Contributors 

Experts whom you can contact for further information