Advertisement

Query Models and Languages for Geographical Information Systems

  • Michel Mainguenaud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1929)

Abstract

This paper presents a synthesis on the query models and languages to manipulate a geographical database. We present the different classes of query languages : based on predicates, based on operators without composition and based on operators with composition. We analyze the consequences on the data model, on the expressive power and on the query modeling. The introduction of operators as query primitives requires the closedness of these operators on geographical data. The introduction of operators increases the expressive power allowing queries involving a composition of operators. As a path operator (with the same arguments) provides several answers and may appear several times in a query, the query modeling must provide such an opportunity. Depending on the required expressive power, we present the different classes of interfaces at the user’s level.

Keywords

Geographical Information System Geographical Information System Query Language Expressive Power Geographical Data 
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.
    Aufaure M.A., Trepied C.: A Survey of Query Languages for Geographic Information Systems. Interfaces to databases (IDS-3), Napier University Edinburgh, 8–10 July (1996)Google Scholar
  2. 2.
    Batini C., Catarci T., Costabile M.F., Levialdi S.: Visual Query Systems: A Taxonomy, Visual Database Systems II, IFIP-TC2/WG2.6, Budapest, Hungary, IFIP Transaction A7, 30/9–3/10 (1991)Google Scholar
  3. 3.
    Calcinelli D., Mainguenaud M.: Cigales, A visual Query Language for geographical Information System: the User Interface, Journal of Visual Languages and Computing, Vol 5, Academic press, (1994), 113–132CrossRefGoogle Scholar
  4. 4.
    Claramunt C, Mainguenaud M.,: A Revisited Database Projection Operator for network Facilities in a GIS, Informatica, 23, (1999), 187–201Google Scholar
  5. 5.
    Guting, R. H., GRAL: An extensible relational database system for geometric applications. In Proceedings of the 15th International Conference on Very Large Data Bases, VLDB, 22–26 August Amsterdam, The Netherlands, (1989)Google Scholar
  6. 6.
    Haas, L., Cody, W. F., Exploiting extensible DBMS in integrated GIS. In Proceedings of the 2nd International Symposium on Large Spatial Database, Gunther, O. and Schek, H.-J. Eds, Springer-Verlag, Zurich, Lecture Notes in Computer Science, n‡ 525, (1991)Google Scholar
  7. 7.
    Egenhofer M., Spatial-Query-by-Sketch, IEEE Symposium on Visula Languages (VL), Boulder, Colorado, USA, 3–6 September, (1996)Google Scholar
  8. 8.
    Larue, T., Pastre, D. and Viémont, Y., Strong integration of spatial domains and operators in a relational database system. In Advances in Spatial Databases, Abel, D. J. and Ooi, B. C. Eds., Springer-Verlag, Singapore, Lecture Notes in Computer Science n‡ 692, (1993)Google Scholar
  9. 9.
    Mainguenaud, M., Consistency of geographical information system results. Computers, Environment and Urban Systems, Vol. 18, Pergamon Press, (1994), 333–342CrossRefGoogle Scholar
  10. 10.
    Meyer B., Beyond Icons: Towards New Metaphors for Visual Query Languages for Spatial Information Systems. Ineterfaces to database Systems (IDS92), Glasgow, UK, 1–3 July (1992)Google Scholar
  11. 11.
    Peuquet DJ: A Concepetual Framework and Comparison of Spatial Data Models, Cartographica, Vol 21 (4), (1984) 66–113Google Scholar
  12. 12.
    Smith TR, Menon S, Star JL, Ester JE: Requirements and Principles for the Implementation and Construction of Large Scale GIS, Int. Journal of Geographical Information System, Vol 1, n‡1, (1987), 13–31CrossRefGoogle Scholar
  13. 13.
    Stemple, D., Sheard, T. and Bunker, R., Abstract data types in databases: Specification, Manipulation and Access. In Proceedings of the 2nd Int. Conference on Data Engineering, Los Angeles, USA, 6–8 Feb (1986)Google Scholar
  14. 14.
    Ullman JD: Principles of Database and Knowledge-base Systems, Computer Science Press, Maryland, (1988)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Michel Mainguenaud
    • 1
  1. 1.Laboratoire Perception, Systeme et InformationInstitut National des Sciences Appliquees (INSA)France

Personalised recommendations