An informatics framework for testing data integrity and correctness of federated biomedical databases.

• Type of Material: Article
• Authors: Mijung Kim, Georgia Institute of Technology; Tahsin Kurc, Emory University; Alessandro Orso, Georgia Institute of Technology; Jake Cobb, Georgia Institute of Technology; David Gutman, Emory University; Mary Jean Harrold, Georgia Institute of Technology; Andrew Post, Emory University; Ashish Sharma, Emory University; Joel Saltz, Georgia Institute of Technology
• Language: English
• Date: 2011
• Publisher: American Medical Informatics Association
• Publication Version: Final Published Version
• Copyright Statement: ©2011 AMIA. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose.
• Title of Journal or Parent Work: AMIA Joint Summits on Translational Science Proceedings
• Volume: 2011
• Start Page: 22
• End Page: 26
• Grant/Funding Information: Partially funded by: Federal funds from the National Cancer Institute; National Institutes of Health Contracts HHSN261200800001E, 94995NBS23, and 85983CBS43; NIH PHS Grants (UL1 RR025008, KL2 RR025009 or TL1 RR025010) from the CTSA program of NCRR; NHLBI R24 HL085343; NIH U54 CA113001; NLM R01LM009239-01A1, and BISTI P20 EB000591; NSF award CCF-0725202.
• Research Categories: Health Sciences, General; Computer Science; Biology, Bioinformatics

Abstract

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.