DocumentCode
3533117
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
fYear
2008
fDate
3-5 Nov. 2008
Firstpage
109
Lastpage
110
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomeidcine Workshops, 2008. BIBMW 2008. IEEE International Conference on
Conference_Location
Philadelphia, PA
Print_ISBN
978-1-4244-2890-8
Type
conf
DOI
10.1109/BIBMW.2008.4686217
Filename
4686217
Link To Document