背景:德国中央卫生研究中心是一项服务,最初是在COVID-19大流行期间在短时间内开发的。从那以后,它的范围已经扩大,内容,活跃的用户和功能。该服务面向两个主要受众:数据提供者和数据消费者。前者希望分享来自临床的研究数据,根据研究数据的公平标准,公共卫生和流行病学研究及相关文件,后者希望找到并最终重用上述领域的相关研究数据。
方法:服务通过图形和编程接口连接两个组。采用复杂的信息模型来描述和发布各种研究数据对象,同时遵守数据保护并满足FAIR要求。该服务正在以需求驱动的方式开发,并具有广泛的用户交互。
结果:免费使用的服务,基于开源软件(Dataverse,MICA,钥匙斗篷),可通过Web浏览器访问。与用户密切合作,创建了几个功能(从收集到组项目到通过API和UI的组合数据捕获)。该服务的采用持续增加,并在2024年6月获得了1,970个研究数据对象。
结论:该服务填补了一个明显的空白,并连接了两个用户组,然而,它仍然需要在各个维度上进行改进(特征,内容,usage).对社区的影响需要进一步评估。尽管最近的立法变化(GDNG,EHDS),该系统提高了敏感数据的可查找性,提供了类似系统的蓝图,并显示了如何与用户一起创建有用且用户友好的服务。
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.