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Managing complex change in clinical study metadata.

Cynthia A Brandt1, Rohit Gadagkar, Cesar Rodriguez

  • 1Center for Medical Informatics, Yale School of Medicine, New Haven, CT 06520-8009, USA. cynthia.brandt@yale.edu

Journal of the American Medical Informatics Association : JAMIA
|June 10, 2004
PubMed
Summary
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Managing complex metadata in software is challenging. This study presents a knowledge-base approach for centralized metadata dependency management, improving system maintainability.

Area of Science:

  • Computer Science
  • Software Engineering
  • Database Management

Background:

  • Highly functional metadata-driven software presents complex interrelationships within metadata, leading to maintenance challenges.
  • Existing metadata management approaches may not adequately address the dynamic and complex nature of these dependencies.

Purpose of the Study:

  • To describe a novel approach for metadata management using a knowledge-base subschema.
  • To centralize information about metadata dependencies and specific modification use cases.
  • To implement and evaluate this approach within a clinical study data management system (TrialDB).

Main Methods:

  • Utilizing a knowledge-base subschema to store metadata dependency information.
  • Employing a production-rule system concept for dynamic interpretation and execution of metadata modification specifications.

Related Experiment Videos

  • Implementing the approach in TrialDB, a generic clinical study data management system.

    • Main Results:

    • The proposed system effectively centralizes metadata dependency information.
    • Dynamic execution of metadata modifications through a middleware engine is demonstrated.
    • The system provides a structured way to handle complex metadata interrelationships.

    Conclusions:

    • The knowledge-base approach offers a robust solution for managing complex metadata in driven software.
    • This method enhances maintainability and addresses specific metadata modification use cases.
    • The TrialDB implementation validates the feasibility and utility of the proposed metadata management strategy.