• 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