, Volume 1, Issue 4, pp 327–343 | Cite as

A Taxonomy of Spatial Data Integrity Constraints

  • Sophie Cockcroft


Spatial data quality has become an issue of increasing concern to researchers and practitioners in the field of Spatial Information Systems (SIS). Clearly the results of any spatial analysis are only as good as the data on which it is based. There are a number of significant areas for data quality research in SIS. These include topological consistency; consistency between spatial and attribute data; and consistency between spatial objects’ representation and their true representation on the ground. The last category may be subdivided into spatial accuracy and attribute accuracy. One approach to improving data quality is the imposition of constraints upon data entered into the database. This paper presents a taxonomy of integrity constraints as they apply to spatial database systems. Taking a cross disciplinary approach it aims to clarify some of the terms used in the database and SIS fields for data integrity management. An overview of spatial data quality concerns is given and each type of constraint is assessed regarding its approach to addressing these concerns. Some indication of an implementation method is also given for each.

database constraints spatial data quality system development rules 


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  1. 1.
    S. Aronoff. Geographic Information Systems: A Management Perspective. WDL Publications: Ottawa, Canada, 1989.Google Scholar
  2. 2.
    A. Chadwick. “An Architecture to support business rules in custom GIS applications,” in Proceedings: 18th AM/FM International Conference, 1047–1058, 1995.Google Scholar
  3. 3.
    F.C. Collins and J.L. Smith, “Taxonomy for error in GIS,” in Proceedings: International symposium on spatial accuracy in Natural Resource Data Bases “Unlocking the puzzle,” R.G. Congalton (Ed.), American Society for Photogrammetry and Remote Sensing, Williamsburg, Virginia, 1–7, 1994.Google Scholar
  4. 4.
    R.G. Congalton. International symposium on spatial accuracy in Natural Resource Data Bases “Unlocking the puzzle.” American Society for Photogrammetry and Remote Sensing, Williamsburg, Virginia, 1994.Google Scholar
  5. 5.
    C. Date. “A contribution to the study of database integrity,” in Relational Database Writings 1985–1989, (pp. 185–215), Addison Wesley: Saratoga, 1990.Google Scholar
  6. 6.
    M.J. Egenhofer. “Pre-processing Queries with spatial constraints,” Photogrammetric Engineering and Remote Sensing, 60(6):783–790, 1994.Google Scholar
  7. 7.
    M.J. Egenhofer and A.U. Frank. “LOBSTER: combining AI and database technologies for GIS,” Photogrammatic Engineering and Remote Sensing, 56(6):919–926, 1990.Google Scholar
  8. 8.
    M.J. Egenhofer and R.D. Franzosa. “Point-set Topological Relations,” International Journal of Geographical Information Systems, 5(2):161–174, 1991.Google Scholar
  9. 9.
    R. Elmasri and S. Navathe. Fundamentals of Database Systems, Benjamin/Cummings, 1994.Google Scholar
  10. 10.
    C. Fahrner, T. Marx, and S. Philippi. Integration of Integrity Constraints into Object Oriented database schema according to ODMG-93 (RR-9-95), University of Koblenz, 1995.Google Scholar
  11. 11.
    P.G. Firns. “An Extended Entity Relationship Model Applicable to the design of Spatially Referenced Databases,” Ph.D. Thesis, University of Otago, Dunedin, New Zealand, 1994.Google Scholar
  12. 12.
    H.W. Fowler and F.G. Fowler (Eds.). The Concise Oxford Dictionary of Current English (Ninth Edition), Oxford: Clarendon Press, 1995.Google Scholar
  13. 13.
    O. Günther and J. Lamberts. “Object-oriented Techniques for the Management of Geographic and Environmental Data,” The Computer Journal, 37(1):16–25, 1994.Google Scholar
  14. 14.
    T. Hadzilacos and N. Tryfona. “A model for expressing topological integrity constraints in geographic databases,” in Proceedings: Theories and Methods of Spatio-Temporal Reasoning in Geographic Space. International Conference GIS—From Space to Territory, A.U. Frank, I. Campari, and U. Formentini (Ed.), Pisa, Italy, 252–268, 1992.Google Scholar
  15. 15.
    T. Hadzilacos and N. Tryfona. “Logical data modelling for geographic applications,” International Journal of Geographical Information Systems, 10(2):179–200, 1996.Google Scholar
  16. 16.
    G.J. Hunter. “Management issues in GIS: Accuracy and Data Quality,” in Proceedings: Conference on managing Geographic Information Systems for success, G.J. Hunter (Ed.), Aurisa: Melbourne, Australia, 95–101, 1996.Google Scholar
  17. 17.
    C. Jones and L. Luo. “Hierarchies and objects in a deductive spatial database,” in Proceedings: Advances in GIS research: Proceedings of the 6th International Symposium on spatial data handling, R.G. Healy (Ed.), 589–603, 1994.Google Scholar
  18. 18.
    P.C. Kanellakis, G. Kuper, and P.Z. Revesz. “Constraint Query Languages,” Journal of Computer and System Sciences, 51(1):26–52, 1995.Google Scholar
  19. 19.
    R. Laurini and F. Milleret-Raffort. “Using integrity constraints for checking consistency of spatial databases,” in Proceedings: GIS/LIS 91, Atlanta, Georgia, 634–642, 1991.Google Scholar
  20. 20.
    L. Luo and C. Jones. “A deductive database model for GIS,” in Innovations in GIS 2, P. Fisher (Ed.), Taylor and Francis, 33–42, 1995.Google Scholar
  21. 21.
    D.F. Marble. “The extended data dictionary: A critical element in building viable spatial databases,” in Proceedings: 11th annual ESRI user conference, 1990.Google Scholar
  22. 22.
    C.B. Medeiros and M.J. Andrade. “Implementing Integrity Control in Active Data Bases,” Journal of Systems and Software, 27:171–181, 1994.Google Scholar
  23. 23.
    C.B. Medeiros and M. Cilia. “Maintenance of binary topological constraints through active databases,” in Proceedings: 3rd ACM International Workshop on Advances in Geographic Information Systems, P. Bergougnoux (Ed.), Baltimore, Maryland, USA, 127–133, 1995.Google Scholar
  24. 24.
    C.B. Medeiros and G.C. Magalhaes. Rule application in GIS–a case study (DCC-18/93), UNICAMP, 1993.Google Scholar
  25. 25.
    T. Smith, R. Ramakrishnan, and A. Voisard. “An Object-Based Data Model and a Deductive Language for Spatio-Temporal Database Applications,” in Proceedings: Proceedings of the Workshop of the BRA Esprit project “GOODS”, M. Gambosi, Scholl and P. Widmayer (Ed.), Springer-Verlag: Berlin, 1992.Google Scholar
  26. 26.
    M. Stonebraker and G. Kemnitz. “The Postgres next-generation database management system,” Communications of the ACM, 34(10):78–92, 1991.Google Scholar
  27. 27.
    T. Ubeda and S. Servigne. “Geometric and Topological Consistency of Spatial Data,” in Proceedings: 1st International Conference on Geocomputation, Leeds, UK, 830–842, 1996.Google Scholar
  28. 28.
    M.F. Worboys. GIS: A Computing Perspective, Taylor and Francis: London, 1995.Google Scholar

Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Sophie Cockcroft
    • 1
  1. 1.Department of Information ScienceUniversity of OtagoDunedinNew Zealand

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