Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Semantic Modeling for Geographic Information Systems

  • Esteban ZimányiEmail author
  • Christine Parent
  • Stefano Spaccapietra
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_336


Conceptual modeling; Conceptual modeling for Geographic Information System; Conceptual modeling for Spatio-temporal applications; Geographical databases; GIS.


Semantic modeling denotes the activity of designing and describing the structure of a data set using a semantic data model. Semantic data models (also known as conceptual data models) are data models whose aim is to provide designers with modeling constructs and rules that are well suited for representing the user’s perception of data in the application world, abstracting from implementation concerns. They contrast with logical and physical data models, whose aim is to organize data in a way that is easily manageable by a computer. The most popular semantic data models are UML, a de facto standard, and ER (Entity-Relationship), still widely used in many design methodologies and favored by the academic community.

Semantic models were first created in the database community in the 1980s. They started to be...

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Recommended Reading

  1. 1.
    Almeida VT, Güting RH, Behr T. Querying moving objects in SECONDO. In: Proceedings of the 7th International Conference on Mobile Data Management; 2006. p. 47–51.Google Scholar
  2. 2.
    Belussi A, Negri M, Pelagatti G. GeoUML: a geographic conceptual model defined through specialization of ISO TC211 standards. In: Proceedings of the 10th EC GI & GIS Workshop, ESDI State of the Art; 2004.Google Scholar
  3. 3.
    Brodeur J, Bédard Y, Proulx M.J. Modelling geospatial application database using UML-based repositories aligned with international standards in geomatics. In: Proceedings of the 8th ACM Symposium on Adavances in Geographic Information System; 2000. p. 39–46.Google Scholar
  4. 4.
    Caron C, Bédard Y. Extending the individual formalism for a more complete modeling of urban spatially referenced data. Comput Environ Urban Syst. 1993;17(4):337–46.CrossRefGoogle Scholar
  5. 5.
    Chen PP. The entity-relationship model: toward a unified view of data. ACM Trans Database Syst. 1976;1(1):9–36.CrossRefGoogle Scholar
  6. 6.
    Egenhofer MJ, Frank AU. Object-oriented modeling for GIS. J Urban Reg Inf Syst Assoc. 1992;4(2):3–19.Google Scholar
  7. 7.
    Grumbach S, Rigaux P, Scholl M, Segoufin L. The DEDALE prototype. In: Constraint databases. Berlin: Springer; 2000. p. 365–82.zbMATHCrossRefGoogle Scholar
  8. 8.
    Güting RH, Böhlen MH, Erwig M, Jensen CS, Lorentzos NA, Schneider M, Vazirgiannis M. A foundation for representing and querying moving objects. ACM Trans Database Syst. 2000;25(1):1–42.CrossRefGoogle Scholar
  9. 9.
    Khatri V, Ram S, Snodgrass RT. On augmenting database design-support environments to capture the geo-spatio-temporal data semantics. Inf Syst. 2006;31(2):98–133.CrossRefGoogle Scholar
  10. 10.
    Parent C, Spaccapietra S, Zimányi E. Conceptual modeling for traditional and spatio-temporal applications: the MADS approach. New York: Springer; 2006.zbMATHGoogle Scholar
  11. 11.
    Pelekis N, Theodoridis Y, Vosinakis S, Panayiotopoulos T. Hermes – a framework for location-based data management. In: Advances in Database Technology, Proceedings of the 10th International Conference on Extending Database Technology; 2006. p. 1130–34.Google Scholar
  12. 12.
    Rios Viqueira JR, Lorentzos NA, Brisaboa NR. Survey on spatial data modelling approaches. In: Manolopoulos Y, Papadopoulos A, Vassilakopoulos M, editors. Spatial databases: technologies, techniques and trends. Hershey: Idea Group; 2005. p. 1–22.Google Scholar
  13. 13.
    Spaccapietra S, Parent C, Damiani ML, Macedo J, Porto F, Vangenot C. A conceptual view on trajectories. Data Knowl Eng. 2008;65(1):126–46.CrossRefGoogle Scholar
  14. 14.
    Sugumaran V, Storey VC. The role of domain ontologies in database design: an ontology management and conceptual modeling environment. ACM Trans Database Syst. 2006;31(3):1064–94.CrossRefGoogle Scholar
  15. 15.
    Tryfona N, Price R, Jensen CS. Spatiotemporal conceptual modeling. In: Spatiotemporal databases: the chorochronos approach (chapter 3), lecture notes in computer science, vol. 2520. Springer: Berlin; 2003. p. 79–116.Google Scholar
  16. 16.
    Worboys M, Hearnshaw H, Maguire D. Object-oriented data modelling for spatial databases. Int J Geogr Inf Syst. 1990;4(4):369–83.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Esteban Zimányi
    • 1
    Email author
  • Christine Parent
    • 2
  • Stefano Spaccapietra
    • 3
  1. 1.CoDEUniversité Libre de BruxellesBrusselsBelgium
  2. 2.University of LausanneLausanneSwitzerland
  3. 3.EPFLLausanneSwitzerland

Section editors and affiliations

  • Ralf Hartmut Güting
    • 1
  1. 1.Computer ScienceUniversity of HagenHagenGermany