Advertisement

Dynamic Models of Geographic Environment using Ontological Relations

  • Miguel MartinezEmail author
  • Serguei Levachkine
Conference paper
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

The geographic environment contains different types of entities: for instance, cars, considered as geographical objects, as well as entities such as storms, considered as geographical phenomena. With these entities occurs something commonly called events. These represent the dynamics of a geographical environment. If these entities are modeled based on an object-oriented approach, only properties and relations between other entities are considered, but the dynamic aspects are not. However, if they are modeled based on an event-oriented approach, the semantic relations of the dynamic aspects are indispensably needed to model the environment, considering instantly changed geographic entities, properties and relations as well as the subsequent effects they may cause to the environment and to other entities. We use Ontology Relations to explicitly describe changes in the properties and relations of geographic entities modified by events. A proposed algorithm generates a semantic chain that represents a whole episode about events over different duration time intervals.

Keywords:

Dynamic environment Ontology Events Semantics Time interval 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    . Campos J and Hornsby K (2004) Temporal constraints between cyclic geographic events. In: Proceedings of GeoInfo 2004, Campos do Jordao, Brazil, November 22-24Google Scholar
  2. 2.
    Car A and Frank A (1995) Formalization of conceptual models for GIS using GOFER. J Computers, Environment, and Urban Systems 19: 89–98CrossRefGoogle Scholar
  3. 3.
    Claramunt C and Theriault M (1995) Managing time in GIS: an event-oriented approach. In: Clifford J and Tzunhilin A (eds) Recent Advances in Temporal Databases, Berlin: Springer-Verlag, pp 23–42CrossRefGoogle Scholar
  4. 4.
    Claramunt C and Theriault M (1996) Toward semantics for modeling spatio-temporal processes within GIS. In: Kraak M and Molenaar M (eds) Proceedings of 7th International Symposium on Spatial Data Handling, Delft, NL, Taylor & Francis Ltd, pp 47-63Google Scholar
  5. 5.
    Gruber TR (1993) Toward Principles for the Design of Ontologies Used for Knowledge Sharing. In: Formal Ontology in Conceptual Analysis and Knowledge Representation, International Workshop on Formal Ontology, Guarino N and Poli R (eds), Kluwer Academic Publishers, In press, Padova, Italy, pp 101–124, 1993Google Scholar
  6. 6.
    Hornsby K (2001) Temporal zooming, Transactions in GIS, 5(3): 255–272CrossRefGoogle Scholar
  7. 7.
    Hornsby K and Egenhofer M Modeling moving objects over multiple granularities. Special issue on Spatial and Temporal Granularity, Annals of Mathematics and Artificial Intelligence. Kluwer Academic Press. 36:177-194.Google Scholar
  8. 8.
    Langran G (1992) Time in geographical information systems. London: Taylor and FrancisGoogle Scholar
  9. 9.
    Martinez M, Moreno M, Torres M and Levashkine S (2007) Adding topological semantic content to spatial databases, IF&GIS 2007, Springer-Verlag, St. PetersburgGoogle Scholar
  10. 10.
    McCarthy JM and Hayes PJ (1969) Some philosophical problems from the standpoint of artificial intelligence. In: Reading in Artificial Intelligence, pp 431–453, Tioga Publishing Co., Palo Alto, CAGoogle Scholar
  11. 11.
    Peuquet DJ (2001) Making space for time: Issues in space-time data representation. J GeoInformatica 5(1): 11–32CrossRefGoogle Scholar
  12. 12.
    Prior AN (1957) Time and Modality. Oxford: Clarendon PressGoogle Scholar
  13. 13.
    Raper J (2000) Multidimensional geographic information science. London and New York: Taylor and FrancisCrossRefGoogle Scholar
  14. 14.
    Raubal M (2001) Human way finding in unfamiliar buildings: a simulation with a cognizing agent. J Cognitive Processing 2-3: 363–388Google Scholar
  15. 15.
    Worboys MF and Hornsby K (2004) From objects to events: GEM, the geospatial event modelGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Centre for Computing Research, National Polytechnic InstituteIntelligent Processing of Geospatial Information LaboratoryMexicoMexico

Personalised recommendations