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This is based on the comment attached to “Actor perspective” written over here and should be further discussed/elaborated. Which steps do you generally need to do?Really drafty.

General Approach

  1. Define FAIR Objectives & deliverables (Guidance: /wiki/spaces/FSD/pages/294584321 Define your objectives for making data FAIR)

  • Here we assume the goal is to

    • Create a new FAIR Clinical dataset

    • Publish this dataset to make it available for others

    • ?

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  • Communities already over here?

    • Assuming you want to already collect the data in a standardised way, build the study using knowledge from the communities? Reusing existing eCRFs and Codebooks?

    • (Find out whether work has already been done, which you can reuse. Perhaps a link to a page which talks about the communities? Or perhaps a page which talks about reusing what’s already out there?)

  • Build the eCRFs with the fields of interest in the EDC

  1. Collect the (meta)data (Guidance: see XYZ)

  • Collect the necessary / desired metadata requirements;

    • Required: Core metadata mode

    • Desired: Health metadata model (is this extended core?)

    • Desired: Domain specific model(s) (Petals)

  • Collect the data

    • Collect the data in the EDC

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  1. Publish the dataset (Guidance: XYZ)

Applied Example

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Use case: Researcher will collect Diagnosis data in Castor EDC and want wants to make this dataset FAIR.

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Step 2: Build study for data collection

  • Researcher searches HRI codebook library for a preferred codebook with Diagnosis items

  • Researchers builds a Diagnosis eCRF in Castor using suitable tools

  • (In case items are missing, does she join something like the clinical community? Maybe she should, but I’m not sure whether most researchers would)