The core objective of this WG is to create a Health Data Commons Global Open Research Commons (GORC) profile. Health data commons (HDCs) are the health-data-focused versions of data commons, which bring together health data infrastructures. HDCs have been or are being launched across a number of geographies to enable the reuse of participant-level health data at the national and cross-national levels. HDCs will enable machine learning and related artificial intelligence (AI)-based approaches to health data analysis and support the national and cross-national detection and response to epidemics. HDCs can facilitate public health surveillance, observational clinical research, personalized medicine, and the design and conduct of randomized controlled trials (RCTs) by enabling country- and cross-country or global analyses of health data. Whether and how the FAIR principles are implemented affects how metadata and participant-level data can be reused across HDCs. FAIR convergence, as when related stakeholders take the same or similar routes to implementing FAIR, can help foster interoperability in the health data space where there are many standards for the capture or exchange of health data and for which there are limited crosswalks that link ontologies. Open collaboration on FAIR implementation also helps stakeholders reuse available resources and standards rather than developing new ones.

https://www.rd-alliance.org/groups/health-data-commons-gorc-profile-wg/activity/
https://www.rd-alliance.org/groups/health-data-commons-gorc-profile-wg/work-statement/?sow=168502

We just started our first group meetings. We have begun work on two of our groups’ deliverables and will present the first 4 months of work, including the Questionnaire that should be ready for Public release and the scoping review results.