On the Specification of Database Semantic Integrity,

Abstract

Semantic integrity is fundamental to the correct application and use of database systems. A database exhibits semantic integrity if it is logically consistent and complete with respect to the real world application being modelled. Although the evaluation of semantic integrity relies on intuition to a large degree, database models should facilitate its demonstration. To meet these requirements database models must be rich enough to permit the specification of the necessary semantics and to support the verification and validation of consistency. Database, programming language, and artificial intelligence concepts are integrated and extended to provide tools and techniques for improved database semantic integrity. Artificial intelligence concepts are applied to improve the semantic power of database models. Data type concepts are extended to accommodate databases and vice versa. The result is a semantically rich database model, based on data type concepts, and a schema specification language which integrates these concepts. This approach permits data type concepts to be applied directly to databases. It is argued that database semantic integrity can be improved through specification and verification tools and techniques based on data type concepts.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1979
Accession Number
ADA105826

Entities

People

  • Michael L. Brodie

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computer Programming
  • Computer Science
  • Computers
  • Data Processing
  • Databases
  • Engineering
  • High Level Languages
  • Information Systems
  • Language
  • Model Theory
  • Programming Languages
  • Relational Databases
  • Reliability
  • Software Development
  • Structured Programming
  • Systems Management

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Geospatial Intelligence and Artificial Intelligence Analytics

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Information Retrieval