Abstract
BackgroundPatient data registries that are FAIR—Findable, Accessible, Interoperable, and Reusable for humans and computers—facilitate research across multiple resources. This is particularly relevant to rare diseases, where data often are scarce and scattered. Specific research questions can be asked across FAIR rare disease registries and other FAIR resources without physically combining the data. Further, FAIR implies well-defined, transparent access conditions, which supports making sensitive data as open as possible and as closed as necessary.ResultsWe successfully developed and implemented a process of making a rare disease registry for vascular anomalies FAIR from its conception—de novo. Here, we describe the five phases of this process in detail: (i) pre-FAIRification, (ii) facilitating FAIRification, (iii) data collection, (iv) generating FAIR data in real-time, and (v) using FAIR data. This includes the creation of an electronic case report form and a semantic data model of the elements to be collected (in this case: the “Set of Common Data Elements for Rare Disease Registration” released by the European Commission), and the technical implementation of automatic, real-time data FAIRification in an Electronic Data Capture system. Further, we describe how we contribute to the four facets of FAIR, and how our FAIRification process can be reused by other registries.ConclusionsIn conclusion, a detailed de novo FAIRification process of a registry for vascular anomalies is described. To a large extent, the process may be reused by other rare disease registries, and we envision this work to be a substantial contribution to an ecosystem of FAIR rare disease resources.
Highlights
Patient data registries that are FAIR—Findable, Accessible, Interoperable, and Reusable for humans and computers—facilitate research across multiple resources
By applying the FAIR principles to Rare disease (RD) registries, analysis across multiple RD registries and other relevant FAIR data is made possible, even when access criteria differ per source
The objectives were to (1) base our vascular anomalies (VASCA) registry on the Common Data Elements for Rare Diseases Registration" (CDEs) and the FAIR principles to enable it for analysis across RD registries, and (2) implement de novo FAIRification in our VASCA registry, where data are made FAIR automatically and in real-time upon collection
Summary
Patient data registries that are FAIR—Findable, Accessible, Interoperable, and Reusable for humans and computers—facilitate research across multiple resources. This is relevant to rare diseases, where data often are scarce and scattered. FAIR implies well-defined, transparent access conditions, which supports making sensitive data as open as possible and as closed as necessary. Rare disease (RD) registries contain valuable information for improving diagnosis, treatment and event prevention [1] For this reason, extensive research has been performed on setting up high quality and effective RD. FAIR implies well-defined, transparent access conditions, which supports making data as open as possible and as closed as necessary [7]. By applying the FAIR principles to RD registries (here referred to as the data collected from RD patients), analysis across multiple RD registries and other relevant FAIR data is made possible, even when access criteria differ per source
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