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MAGICPL: A Generic Process Description Language for Distributed Pseudonymization Scenarios
Methods of Information in Medicine ( IF 1.7 ) Pub Date : 2021-07-05 , DOI: 10.1055/s-0041-1731387
Galina Tremper 1, 2 , Torben Brenner 1, 2 , Florian Stampe 1 , Andreas Borg 3 , Martin Bialke 4 , David Croft 1, 2 , Esther Schmidt 1, 2 , Martin Lablans 1, 2
Affiliation  

Objectives Pseudonymization is an important aspect of projects dealing with sensitive patient data. Most projects build their own specialized, hard-coded, solutions. However, these overlap in many aspects of their functionality. As any re-implementation binds resources, we would like to propose a solution that facilitates and encourages the reuse of existing components.

Methods We analyzed already-established data protection concepts to gain an insight into their common features and the ways in which their components were linked together. We found that we could represent these pseudonymization processes with a simple descriptive language, which we have called MAGICPL, plus a relatively small set of components. We designed MAGICPL as an XML-based language, to make it human-readable and accessible to nonprogrammers. Additionally, a prototype implementation of the components was written in Java. MAGICPL makes it possible to reference the components using their class names, making it easy to extend or exchange the component set. Furthermore, there is a simple HTTP application programming interface (API) that runs the tasks and allows other systems to communicate with the pseudonymization process.

Results MAGICPL has been used in at least three projects, including the re-implementation of the pseudonymization process of the German Cancer Consortium, clinical data flows in a large-scale translational research network (National Network Genomic Medicine), and for our own institute's pseudonymization service.

Conclusions Putting our solution into productive use at both our own institute and at our partner sites facilitated a reduction in the time and effort required to build pseudonymization pipelines in medical research.



中文翻译:

MAGICPL:分布式假名化场景的通用过程描述语言

目标 化名是处理敏感患者数据的项目的一个重要方面。大多数项目构建自己的专门的、硬编码的解决方案。但是,它们在功能的许多方面都存在重叠。由于任何重新实现都会绑定资源,因此我们希望提出一种解决方案,以促进和鼓励现有组件的重用。

方法 我们分析了已经建立的数据保护概念,以深入了解它们的共同特征以及它们的组件链接在一起的方式。我们发现我们可以用一种简单的描述性语言(我们称之为 MAGICPL)加上相对较小的组件集来表示这些假名化过程。我们将 MAGICPL 设计为一种基于 XML 的语言,使其易于人类阅读并可供非程序员使用。此外,组件的原型实现是用 Java 编写的。MAGICPL 可以使用组件的类名引用组件,从而轻松扩展或交换组件集。此外,还有一个简单的 HTTP 应用程序编程接口 (API) 来运行任务并允许其他系统与假名过程进行通信。

结果 MAGICPL 已用于至少三个项目,包括重新实施德国癌症联盟的假名过程,大规模转化研究网络(国家网络基因组医学)中的临床数据流,以及我们自己研究所的假名服务。

结论 将我们的解决方案在我们自己的研究所和我们的合作伙伴站点投入生产使用,有助于减少在医学研究中构建假名管道所需的时间和精力。

更新日期:2021-07-06
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