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A model-driven approach to manage evolving clinical and translational data in relational databases

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3 Author(s)
Qifeng Lin ; Coll. of Comput., Georgia Tech, Atlanta, GA ; Pu, C. ; Lee, E.K.

In this paper, we present a model-driven code generation process that allows for adaptation capability to respond to required changes in evolving and expanding clinical and translational data management. Given an Entity Relationship (ER) model over an ontology, our tools are able to generate new database schema, create the new database and generate new queries to access the new database rapidly. Our experience with four distributed databases (involving imaging, biomarker, clinical, and metabolomics data) shows that model-driven code generation is a promising approach for clinical data management systems that must evolve as the application and data sources change.

Published in:

Bioinformatics and Biomeidcine Workshops, 2008. BIBMW 2008. IEEE International Conference on

Date of Conference:

3-5 Nov. 2008