A terminological canonical data model for cooperating heterogeneous geographical information systems

  • Tarek Branki
  • Bruno Defude
Modelling I
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1308)


The best way to make cooperate heterogeneous GIS (Geographical Information Systems) is to integrate them through a federated architecture. This last one necessitates in its first step the definition of a Canonical Data Model (CDM). The GEOgraphical COOPerative Model (GEOCOOPM) we have defined belongs to the family of terminological systems also known as description logics. We develop, in this paper, a precise syntax and semantic of Geocoopm and demonstrate the following: (1) First, Geocoopm gives a semantic to the spatial dimension. (2) It also permits the definition of heterogeneous data types (maps, numerical data, spatial data). (3) Geocoopm can represent various transformations on these data. (4) Finally, it provides a great facility for a good organisation of data and transformations using the subsumption function which enables building many hierarchies of data and transformations. This is a first step towards the schema integration process. We provide many examples to illustrate our claims.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    D. J. Abel, P. J. Kilby and J. R. Davis. The systems integration problem. International Journal of Geographical Information Systems, Volume 8, Number 1, pages 1–12, 1994.Google Scholar
  2. 2.
    G. Alonso and A. El Abbadi.Cooperative modelling in applied geographic research. International Journal of Intelligent and Cooperative Information Systems, Volume 3, Number 1, pages 83–102, 1994.Google Scholar
  3. 3.
    H. W. Beck, S. K. Gala and S. B. Navathe. Classification as a query processing technique in the CANDIDE semantic data model. In Proc. IEEE CS Intl. Conf. on Data Engineering, pages 572–581, Los Angeles, February 1989.Google Scholar
  4. 4.
    R. J. Brachman. What's in concept: Structural foundations for semantic networks. International Journal Man-Machine Studies, pages 127–152, 1977.Google Scholar
  5. 5.
    R. J. Brachman, D. L. Me Guiness, P.F. Patel-Schneider, L. A. Resnick and A. Borgida. Living with CLASSIC: When and how to use a KL-ONE like language. Principles of Semantic Networks: Explorations of the Representation of Knowledge, pages 401–456, 1991.Google Scholar
  6. 6.
    T. Branki and B. Defude. A terminological canonical data model for cooperating heteregeneous geographical information systems. Technical report, National Institute of Telecommunications, 1997.Google Scholar
  7. 7.
    M. Egenhofer. SpatialSQL: A query and presentation language. IEEE Transactions on Knowledge and Data Engineering, Volume 6, pages 86–95, 1994.Google Scholar
  8. 8.
    R. H. Guting. An introduction to spatial database systems. VLDB Journal, Volume 3, Number 4, pages 357–399, 1994.Google Scholar
  9. 9.
    R. Laurini. Raccordement géométrique de bases de données géographiques fédérées. Ingénierie des Systèmes d'Information, Volume 4, Number 3, pages 361–388, 1996.Google Scholar
  10. 10.
    S. Morehouse. ARC/INFO: A geo-relational model for spatial information. In Seventh Proceedings on Digital Representation of Spatial Knowledge, pages 388–397, Washington D. C, March 1985.Google Scholar
  11. 11.
    B. Nebel. Computational complexity of terminological reasoning in BACK. Artificial Intelligence Magazine, Volume 34, Number 3, pages 371–383, 1988.Google Scholar
  12. 12.
    C. Parent, S. Spaccapietra and T. Devogele. Conflicts in spatial database integration. In Ninth International Conference on Parallel and Distributed Computing Systems, Dijon, France, September 1996.Google Scholar
  13. 13.
    M. Scholl and A. Voisard. Thematic map modelling. In First International Symposium, SSD'89, pages 167–190, Santa Barbara, California, July 1989.Google Scholar
  14. 14.
    A. P. Sheth, S. K. Gala and S. B. Navathe. On automatic reasoning for schema integration. International Journal of Intelligent and Cooperative Information Systems, Volume 2, Number 1, pages 23–50, 1993.Google Scholar
  15. 15.
    A. P. Sheth and J. A. Larson. Federated database systems for managing distributed, heteregeneous and autonomous databases. ACM Computing Surveys, Volume 22, Number 3, pages 183–236, 1990.Google Scholar
  16. 16.
    S. Spaccapietra and C. Parent. View integration: a step forward in solving structural conflict. IEEE Transactions on Knowledge and Data Engineering, Volume 6, Number 2, pages 258–274, 1994.Google Scholar
  17. 17.
    M. F. Worboys and P. Bofakos. A canonical model for a class of areal spatial objects. In Third International Symposium, SSD'93, pages 36–52, Singapore, June 1993.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Tarek Branki
    • 1
    • 2
  • Bruno Defude
    • 2
  1. 1.Laboratoire d'informatique Paris NordUniversité Paris13VilletaneuseFrance
  2. 2.Computer science departmentInstitut National des TélécommunicationsEvry cedexFrance

Personalised recommendations