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A strategy for database interoperation

P D Karp1

  • 1Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA. pkarp@ai.sri.com

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|January 1, 1995
PubMed
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Declarative queries to biological databases offer powerful, fast analyses beyond interactive navigation. A proposed architecture enables seamless interoperation across diverse biological data resources.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Information Science

Background:

  • Current bioinformatics database interoperation relies heavily on interactive, hypertext navigation.
  • This approach limits the speed and power of complex biological data analysis.
  • There is a need for more robust methods to integrate and query distributed biological databases.

Purpose of the Study:

  • To propose a vision for query-based interoperation infrastructure for biological databases.
  • To identify the requirements and assumptions for such an infrastructure.
  • To present a novel architecture for enabling powerful, declarative querying across multiple biological databases.

Main Methods:

  • Development of a conceptual framework for query-based database interoperation.

Related Experiment Videos

  • Design of a novel architecture incorporating a knowledge base, query routing, and translation modules.
  • Inclusion of database drivers for uniform physical access and schema translators for interconversion.

    • Main Results:

    • A proposed architecture includes a knowledge base for conceptual relationships, a relevance determination module, and a translation module.
    • The architecture features uniform database drivers and schema translators to bridge heterogeneities.
    • This infrastructure facilitates orders-of-magnitude faster and more powerful analyses compared to interactive navigation.

    Conclusions:

    • Query-based interoperation provides a significantly more powerful approach to biological data analysis than interactive navigation.
    • The proposed architecture addresses key challenges in biological database integration at conceptual, data model, query language, and data format levels.
    • This infrastructure is essential for realizing the full potential of biological databases for advanced research.