Kim Mijung, Kurc Tahsin, Orso Alessandro, Cobb Jake, Gutman David, Harrold Mary Jean, Post Andrew, Sharma Ashish, Saltz Joel
College of Computing, Georgia Institute of Technology, Atlanta, GA.
AMIA Jt Summits Transl Sci Proc. 2011;2011:22-6. Epub 2011 Mar 7.
Clinical research is increasingly relying on information gathered and managed in different database systems and institutions. Distributed data collection and management processes in such settings can be extremely complex and lead to a range of issues involving the integrity and accuracy of the distributed data. To address this challenge, we propose a middleware framework for assessing the data integrity and correctness in federated environments. The framework has two main elements: (1) a test model describing the dependencies between and constraints on data sources and datasets, and (2) a family of testing techniques that create and execute test cases based on the model.
临床研究越来越依赖于在不同数据库系统和机构中收集和管理的信息。在这种情况下,分布式数据收集和管理过程可能极其复杂,并导致一系列涉及分布式数据完整性和准确性的问题。为应对这一挑战,我们提出了一个用于评估联邦环境中数据完整性和正确性的中间件框架。该框架有两个主要元素:(1)一个描述数据源和数据集之间的依赖关系及约束的测试模型,以及(2)一组基于该模型创建和执行测试用例的测试技术。