Geospatial information integration based on the conceptualization of geographic domain

ABSTRACT

Geospatial information integration is not a trivial task. An integrated view must be able to describe various heterogeneous data sources and its interrelation to obtain shared conceptualizations. Up-to-date, there are different and public ontologies for many domains and applications. Ontology engineering is rapidly becoming a mature discipline, which has produced various tools and methodologies for building and managing ontologies. However, even with a clearly defined engineering methodology, building a large ontology remains a challenging, time-consuming and error-prone task, since it forces ontology builders to conceptualize their expert knowledge explicitly and to re-organize it in typical ontological categories such as concepts, properties and axioms. In this paper, an approach to conceptualize the geographic domain is described. As a result of this conceptualization, we propose a semantic method for geospatial information integration. This consists of providing semantic descriptions, which explicitly describe the properties and relations of geographic objects represented by concepts, while the behavior describes the objects semantics. Summing up, this work presents a methodology allowing integrate and share geospatial information. It provides feasible solutions towards these and other related issues such as compact data by alternative structures of knowledge representation and avoids the ambiguity of these terms, using a geographic domain conceptualization. The general vision of the paper is to establish the basis to implement semantic processing oriented to geospatial data. Future works are focused on designing intelligent geographic information systems (iGIS).

REFERENCES

• 1: Gruber, T. R., and Olsen, G. R. 1994. An Ontology for Engineering Mathematics. Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning, 258--269.
• 2: Guarino, N. 1998. Formal Ontology and Information Systems. In Proceedings of the 1st International Conference on Formal Ontologies in Information Systems (FOIS 1998), 3--15.
• 3: Xiao, H., Cruz, I. F., and Hsu, F. 2004. Semantic Mappings for the Integration of XML and RDF Sources. In Workshop on Information Integration on the Web (IIWeb 2004).
• 4: Torres, M. 2007. Representación Ontológica basada en Descriptores Semánticos aplicada a Objetos Geográficos. Ph. D. Thesis in Spanish.
• 5: Douglas B. Lenat , R. V. Guha, Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1989
• 6: Uschold, M., and Grüninger, M. 1996. Ontologies: Principles, Methods and Applications. Knowledge Engineering Review 11(2), 93--155.
• 7: Grüninger, M., and Fox, M. S. 1995. Methodology for the design and evaluation of ontologies. Proceedings of the Workshop on Basic Ontological Issues in Knowledge Sharing IJCAI'95. Montreal, Canada, 7.3--7.13.
• 8: Bernaras, A., Laresgoiti, I., and Corera, J. 1996. Building and reusing ontologies for electrical network applications. Proceedings of European Conference on Artificial Intelligence. Budapest, Hungary. John Wiley & Sons, 298--302.
• 9: Fernández, M., Gómez, A., and Juristo, N. 1997. METHONTOLOGY: From Ontological Art Towards Ontological Engineering. Symposium on Ontological Engineering of AAAI. Standford University, California, 33--40.
• 10: Swartout, B., Ramesh, P., Knight, K., and Russ, T. 1997. Toward Distributed Use of Large-Scale Ontologies. Symposium on Ontological Engineering of AAAI. Stanford University, California, 138--148.
• 11: Steffen Staab , Rudi Studer , Hans-Peter Schnurr , York Sure, Knowledge Processes and Ontologies, IEEE Intelligent Systems, v.16 n.1, p.26-34, January 2001 [doi>10.1109/5254.912382]
• 12: Guarino, N., and Welty, C. 1995. A Formal Ontology of Properties. Lecture Notes in Artificial Intelligence, Vol. 1937. Springer-Verlag, Berlin, Germany, 97--112.
• 13: Bishr, Y. and Kuhn, W. 2000. Ontology-Based Modeling of Geospatial Information. Proceedings of 3rd AGILE Conference on Geographic Information Science, Helsinki, Finland, 24--27.
• 14: Torres, M., Quintero, R., Levachkine, S., Guzmán, G., and Moreno, M. 2008. Towards a methodology to conceptualize the geographic domain. Lecture Notes in Artificial Intelligence, Vol. 5317. Springer-Verlag, Berlin, Germany, 111--122.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods

General Terms:
Languages, Theory

Keywords:
axiomatic relationships, conceptualization, geo-ontologies, iGIS