Short Description
Common Data Elements (CDEs) are standardised, precisely defined question paired with specific allowable responses. These CDEs can be used systematically across different sites, studies, or clinical trials to ensure consistent data collection [NIH]. These CDEs can be annotated with an ontological model to define their meaning and facilitate integration of CDEs from different registries [De Novo]. The ontological model is essential for computers to assess that common data elements are indeed common [De Novo].
By openly publishing the CDEs and the ontologies to annotate them, they can be reused to build case report forms for data collection [De Novo]. See the Register record level metadata step?
[NIH] https://www.nlm.nih.gov/oet/ed/cde/tutorial/03-100.html
Why is this step important
By using common data elements, it is ensured that the data being collected uses the exact same definitions and, if annotated, ontological model. This is an important step for the interoperability of the data.
How to
[De Novo]
Furthermore, we have made our eCRF interoperable and reusable, as the codebook describing the eCRF templates containing the CDEs and the ontologies to annotate them is openly available in ART-DECOR [34]. Via the openly available iCRF Generator tool [35], the codebook can be directly implemented in other EDC systems such as OpenClinica and REDcap.
We could add something about creating and publishing codebooks?
We could say something about setting up new CDEs and reusing existing ones?
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.
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.”