FAIRness for HL7 FHIR: supporting interoperability of health datasets
semanticscholar(2021)
摘要
The FAIR (Finable Accessible Interoperable Reusable) principles have been established as best practice in the generation of health datasets for open science, research, and innovation. The FAIR4Health project (fair4health.eu) aims to encourage FAIRification and reuse of research data generated by publicly funded research projects. The Research Data Alliance (RDA) research community organization aims at building the social and technical infrastructure to enable open sharing and re-use of data. FAIR4Health and the RDA FAIR data maturity model WG initiated the HL7 FAIRness for FHIR implementation guide (IG) project to provide guidance on how to assess the FAIRness of health data sets with the RDA FAIR Data Maturity Model and support delivery of FAIR health datasets using the HL7 FHIR standard. In this paper, we present how we applied the guidance of the HL7 FAIRness for FHIR IG on selected PhysioNet datasets and reflect on the experience gained by discussing the recommendations of the IG on how to use HL7 FHIR resources to advance the FAIRness of health data sets.
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