Advertisement

Knowledge-Based Schema Analysis in a Multi-Database Framework

  • Jian Yang
  • Mike P. Papazoglou
  • Louis Marinos

Abstract

Schema analysis is a very important issue in the integration of a corporate information system. The basic problems to be dealt with during integration come from structural and semantical diversities in schemas to be merged. Before we integrate local schemas, we must ascertain how conflicts and correspondences between types in different schemas can be identified. In this paper, we present a strategy for schema analysis based on a knowledge-based version of the object-oriented paradigm and describe a methodology for discovering structural and semantic relatedness of components within disparate information sources.

Keywords

Information Source Schema Analysis Object Type Semantic Relationship Role Relationship 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    C. Batini, M. Lenzerini, S. B. Navathe,`A Comparative Analysis of Methodologies for Database Schema Integration’, Computing Surveys, vol. 18, no. 4, December 1986.Google Scholar
  2. [2]
    S. Navathe et al.,`Integration User Views in Database Design’, IEEE Computer, vol. 19, no. 1, January 1986.Google Scholar
  3. [3]
    M V Mannino et al, `A Rule-Based Approach For Merging Generalization Hierarchies’, Information Systems vol. 13, no. 3, pp. 257–272, 1988.CrossRefGoogle Scholar
  4. [4]
    A. P. Sheth, J. A. Larson, `A Tool For Integration Conceptual Schema And User Views’, IEEE Conf. on Data & Knowledge Eng., pp. 176–183, Los Angles, Feb. 1988.Google Scholar
  5. [5]
    S. Hayne, S. Ram, ‘Muti-User View Integration System(MUVIS): An Expert System for View Integration’, IEEE Conf. on Data Si Knowledge Eng., pp. 402–409, Feb. 1990.Google Scholar
  6. [6]
    J. Banerjee et al, `Data Model Issues for Object-Oriented Applications’, ACM trans. on Office Information Systems, vol. 5, no. 1, pp. 3–26, Jan. 1987.CrossRefGoogle Scholar
  7. [7]
    S. Zdonik and D. Maier, `Readings in Object-Oriented Database System’, Morgan Koffman Publishers, San Mateo, CA, 1990.Google Scholar
  8. [8]
    M. P. Papazoglou, `Knowledge-Driven Distributed Information System’, 14th Int’l Computer Software & Application Conference, COMPSAC-90, pp. 671–679, Chicago, Oct. 1990.Google Scholar
  9. [9]
    W. Effelsberg, M. Mannino `Attribute Equivalence in Global Schema Design for Heterogeneous Distributed Databases’, Information Systems, vol. 9, no. 3, 1984.Google Scholar
  10. [10]
    J. Larson et al., `A Theory of Attribute Equivalence in Databases with Application to Schema Integration’, IEEE trans. on Software Engineering, vol. 15, no. 4, pp. 449–463, April 1989.MATHCrossRefGoogle Scholar
  11. [11]
    S. Slade, `Case-Based Reasoning: A Research Paradigm’, AI-Magazine, pp. 42–55, Spring 1991.Google Scholar
  12. [12]
    M. Vilain et al, `On Analytical and Similarity-Based Classification’, AAAI-90 Conference, pp. 867–874, Boston, 1990.Google Scholar

Copyright information

© Springer-Verlag Wien 1991

Authors and Affiliations

  • Jian Yang
    • 1
  • Mike P. Papazoglou
    • 1
  • Louis Marinos
    • 2
  1. 1.Dept of Computer ScienceAustralian National UniversityCanberraAustralia
  2. 2.Laboratory For Artificial IntelligenceErasmus University RotterdamRotterdamHolland

Personalised recommendations