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titleStatus: IN development

Short description 

The next step in the process is to make your data and metadata linkable, i.e. transform them to a machine readable knowledge graph representation [Generic]. Currently, this is done using Semantic Web and Linked Data technologies [GOFAIR_process]. An example of a linkable machine-readable global framework is the Resource Description Framework (RDF). It provides a common and straightforward underlying model and creates a powerful global virtual knowledge graph [Generic]. To transform the metadata and data into this linkable representation requires the semantic models defined in step X and step Y respectively. See the How to section for practical information.  

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After transforming the eCRF data into a machine-readable RDF representation (step 11), it is stored in a triple store. This is done via the data transformation application upon data entry (collected or updated) in the EDC system (step 10). The URL providing access to the machine-readable data in the triple store is made available in the FAIR Data Point as an access URL in the Distribution layer (Figure S2). 

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 

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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

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