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Metadata tables to enable dynamic data modeling and web interface design: the SEER example.

Mark Weiner1, Micah Sherr, Abigail Cohen

  • 1Division of General Internal Medicine, School of Medicine, University of Pennsylvania, 423 Guardian Drive, Room 1116, Philadelphia, PA 19104, USA.

International Journal of Medical Informatics
|March 21, 2002
PubMed
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This study introduces a dynamic web interface for accessing health databases, simplifying data exploration. It allows flexible querying of government health data, like the Surveillance, Epidemiology, and End-Results (SEER) database.

Area of Science:

  • Health Informatics
  • Database Management
  • Public Health Data

Background:

  • Government agencies compile extensive health data on status, outcomes, and resource use.
  • Current data access methods often require downloading large datasets or navigating restrictive web interfaces.
  • Existing tools limit the complexity and flexibility of data queries.

Purpose of the Study:

  • To develop a flexible, web-based database interface engine.
  • To enable dynamic generation of interfaces based on metadata.
  • To improve accessibility and query capabilities for public health databases.

Main Methods:

  • Developed a web-based database interface engine.
  • Utilized a metadata table to dynamically generate interface content and structure.

Related Experiment Videos

  • Designed the system to accommodate changes in the underlying data model via metadata updates.
  • Implemented and tested with the National Cancer Institute's Surveillance, Epidemiology, and End-Results (SEER) database.

    • Main Results:

    • A dynamically generated web interface was created.
    • The interface allows for flexible data querying, overcoming limitations of structured web forms.
    • Changes to the data model can be managed by updating the metadata table, reducing the need for code modification.
    • Demonstrated usability with the SEER database.

    Conclusions:

    • The metadata-driven approach provides a flexible and adaptable solution for accessing complex health databases.
    • This engine enhances user interaction with public health data, facilitating broader research and analysis.
    • The system streamlines data exploration for resources like the SEER database.