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Objects and domains for managing medical data and knowledge

G Wiederhold1

  • 1Computer Science Department, Stanford University, CA, USA.

Methods of Information in Medicine
|March 1, 1995
PubMed
Summary
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This study introduces an algebraic approach to generate data objects from relational data using formal models. While dynamic view-object creation impacts performance, it enhances system scalability for complex, multi-objective environments.

Area of Science:

  • Computer Science
  • Database Systems
  • Data Management

Background:

  • Object-oriented data paradigms offer advantages but face challenges in dynamic view generation.
  • Relational databases struggle with complex data hierarchies and multiple objectives.
  • Scalability in large systems is hindered by autonomous and heterogeneous data domains.

Purpose of the Study:

  • To assess the object-oriented data paradigm and propose an algebraic approach for data object generation.
  • To address performance implications of dynamic view-object creation.
  • To introduce a knowledge-based algebra for managing heterogeneous domains and differing ontologies.

Main Methods:

  • An algebraic approach is described to generate data objects from relational data using a formal Entity-Relationship model (Structural Model).

Related Experiment Videos

  • The approach allows object creation satisfying various views, provided hierarchies are subsumed within the structural model.
  • A knowledge-based algebra is proposed to manage domain knowledge partitioning and shared ontologies via matching rules.

    • Main Results:

    • Objects can be created dynamically to satisfy multiple views, enhancing system scalability.
    • Performance implications arise from dynamic view-object creation, potentially negating expected speedups.
    • A knowledge-based algebra facilitates partitioning of autonomous, heterogeneous domains by defining shared ontologies at intersection points.

    Conclusions:

    • The proposed algebraic approach enables flexible data object generation from relational data, improving scalability for complex systems.
    • While dynamic view creation introduces performance overhead, it is crucial for managing diverse data objectives.
    • A knowledge-based algebra is essential for handling heterogeneous data domains and differing ontologies in large-scale systems.