Department of Medical Imaging, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Orphanet J Rare Dis. 2021 Sep 4;16(1):376. doi: 10.1186/s13023-021-02004-y.
Patient 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.
We 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.
In 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.
对于人类和计算机来说，可发现、可访问、可互操作且可重复使用的患者数据注册中心（FAIR）有助于跨多个资源进行研究。这对于罕见病尤其重要，因为数据通常稀缺且分散。可以在 FAIR 罕见病注册中心和其他 FAIR 资源上提出具体的研究问题，而无需实际合并数据。此外，FAIR 意味着定义明确、透明的访问条件，这支持尽可能开放敏感数据，并在必要时进行适当的封闭。
我们成功地开发并实施了将血管异常罕见病注册表 FAIR 的过程，从最初的构想开始。在这里，我们详细描述了该过程的五个阶段：（i）FAIR 前阶段，（ii）促进 FAIR 化阶段，（iii）数据收集阶段，（iv）实时生成 FAIR 数据阶段，以及（v）使用 FAIR 数据阶段。这包括创建电子病例报告表和要收集的元素的语义数据模型（在这种情况下：欧洲委员会发布的“罕见病注册通用数据元素集”），以及在电子数据捕获系统中实现自动实时数据 FAIR 化的技术实现。此外，我们描述了我们如何为 FAIR 的四个方面做出贡献，以及我们的 FAIR 化过程如何被其他注册中心重复使用。
总之，描述了一个详细的血管异常注册表从头 FAIR 化过程。在很大程度上，该过程可以被其他罕见病注册表重复使用，我们设想这项工作将对 FAIR 罕见病资源生态系统做出重大贡献。
