Title :
A model-driven approach to manage evolving clinical and translational data in relational databases
Author :
Lin, Qifeng ; Pu, Calton ; Lee, Eva K.
Author_Institution :
Coll. of Comput., Georgia Tech, Atlanta, GA
Abstract :
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.
Keywords :
medical information systems; ontologies (artificial intelligence); program compilers; query processing; relational databases; biomarker; clinical data; data management; entity relationship; imaging; metabolomics data; model-driven code generation; ontology; queries; relational databases; translational data; Application software; Computer architecture; Distributed databases; Educational institutions; Erbium; Image databases; Medical services; Ontologies; Relational databases; XML;
Conference_Titel :
Bioinformatics and Biomeidcine Workshops, 2008. BIBMW 2008. IEEE International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
978-1-4244-2890-8
DOI :
10.1109/BIBMW.2008.4686217