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The UMLS knowledge source server: an object model for delivering UMLS data.

Anantha Bangalore1, Karen E Thorn, Carolyn Tilley

  • 1US National Library of Medicine, Bethesda, MD, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|January 20, 2004
PubMed
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The Unified Medical Language System Knowledge Source Server (UMLSKS) was redesigned using Java and XML for faster, more flexible data retrieval. This new system enhances access to vital biomedical knowledge sources for researchers.

Area of Science:

  • Biomedical Informatics
  • Health Informatics
  • Knowledge Management

Background:

  • The Unified Medical Language System (UMLS) provides essential knowledge sources for biomedical research.
  • The UMLS Knowledge Source Server (UMLSKS) is the primary distribution channel for these resources.
  • Previous versions of UMLSKS required updates to improve performance and flexibility.

Purpose of the Study:

  • To present the design of a completely redesigned UMLS Knowledge Source Server (UMLSKS).
  • To implement a fast, reliable, flexible, and extensible system for retrieving UMLS data.
  • To provide an Application Programmer's Interface (API) and Object Model for key UMLS knowledge sources.

Main Methods:

  • The new UMLSKS was developed using Java and Extensible Markup Language (XML) technologies.

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  • The system incorporates an Object Model for the UMLS Metathesaurus, Semantic Network, and SPECIALIST Lexicon.
  • The design focuses on efficient data retrieval and system extensibility.

    • Main Results:

    • The redesigned UMLSKS offers improved speed, reliability, and flexibility in accessing UMLS data.
    • Statistics demonstrate significant usage of the new UMLSKS and its associated data.
    • The new system provides enhanced programmatic access through its API and Object Model.

    Conclusions:

    • The new Java and XML-based UMLSKS represents a significant advancement in accessing biomedical knowledge.
    • The system's design supports future development and integration within the research community.
    • Enhanced data retrieval and accessibility will facilitate further biomedical research and innovation.