ZB MED - Information Centre for Life Sciences, Cologne, Germany.
Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Stud Health Technol Inform. 2024 Aug 30;317:129-137. doi: 10.3233/SHTI240847.
The German Central Health Study Hub is a service that was initially developed at short notice during the COVID-19 pandemic. Since then, it has been expanded in scope, content, active users and functionality. The service is aimed at two main audiences: data provider and data consumers. The former want to share research data from clinical, public health and epidemiological studies and related documents according to the FAIR criteria for research data, and the latter want to find and ultimately reuse relevant research data in the above areas.
The service connects both groups via graphical and programmatic interfaces. A sophisticated information model is employed to describe and publish various research data objects while obeying data protection and fulfilling FAIR requirements. The service is being developed in a demand-driven manner with extensive user interaction.
A free-to-use service, built on open-source software (Dataverse, MICA, Keycloak), accessible via a web-browser. In close collaboration with users several features (ranging from collection to group items to combined data capture via API and UI) were created. The adoption of the service increases continuously and results in over 1,970 research data objects in June 2024.
The service fills a marked gap and connects both user groups, yet it still needs to be improved in various dimensions (features, content, usage). The impact on the community needs to be further assessed. Despite recent legislative changes (GDNG, EHDS), the system improves the findability of sensitive data, provides a blueprint for similar systems and shows how to create a useful and user-friendly service together with users.
德国中央健康研究中心是一项服务，最初是在 COVID-19 大流行期间紧急开发的。自那时以来，它的范围、内容、活跃用户和功能都有所扩大。该服务针对两个主要受众：数据提供者和数据使用者。前者希望根据研究数据的 FAIR 标准共享来自临床、公共卫生和流行病学研究及相关文件的研究数据，后者希望在上述领域找到并最终重用相关研究数据。
该服务通过图形和编程接口将这两个群体联系起来。使用复杂的信息模型来描述和发布各种研究数据对象，同时遵守数据保护和满足 FAIR 要求。该服务是在需求驱动的方式下开发的，用户广泛参与。
这是一项免费使用的服务，构建在开源软件（Dataverse、MICA、Keycloak）之上，可以通过网络浏览器访问。通过与用户的密切合作，创建了几个功能（从集合到组项，再到通过 API 和 UI 进行组合数据捕获）。该服务的采用率不断增加，截至 2024 年 6 月，已有超过 1970 个研究数据对象。
该服务填补了明显的空白，连接了两个用户群体，但仍需要在各个方面（功能、内容、使用）进行改进。需要进一步评估对社区的影响。尽管最近立法有所变化（GDNG、EHDS），该系统提高了敏感数据的可发现性，为类似系统提供了蓝图，并展示了如何与用户一起创建有用且用户友好的服务。
