Abstract
Providing Geographical Information Systems (GIS) with the mechanisms for processing geographical data based on their semantic abstraction is a task that at present is carried out in a number of research given their scope of applications. Tackling this issue may help to solve many problems of geographical data like its heterogeneity, since the SIG could process geographical data focusing on their meaning and not on their syntax and/or structure, thus reducing the Man-Machine semantic gap. An important aspect for achieving these objectives is the establishment of an automatic way of correspondence between geographical data and their conceptualization in a Domain Ontology. In this work, we propose a new type of Ontology, a Data-Representation Ontology. We also propose a new method for the automatic generation of the Data-Representation Ontology from geographical data and his interrelationships with the Domain Ontology. For this we use pattern classification techniques and a dissimilarity measure. The experiments showed that once the Data-Representation Ontology was generated, the classifier using dissimilarities could correctly classify all the data.
Chapter PDF
Similar content being viewed by others
References
Leung, Y.: Knowledge Discovery in Spatial Data. Springer, Heidelberg (2010)
Visser, U.: Intelligent Information Integration for the Semantic Web. LNCS. Springer, Heidelberg (2004)
Kavouras, M., Kokla, M., Tomai, E.: Comparing categories among geographic ontologies. In: Computers & Geosciences, Special Issue, Geospatial Research in Europe: AGILE 2003 (2003)
Schwering, A., Raubal, M.: Spatial relations for semantic similarity measurement. In: Akoka, J., Liddle, S.W., Song, I.-Y., Bertolotto, M., Comyn-Wattiau, I., van den Heuvel, W.-J., Kolp, M., Trujillo, J., Kop, C., Mayr, H.C. (eds.) ER Workshops 2005. LNCS, vol. 3770, pp. 259–269. Springer, Heidelberg (2005)
Hakimpour, F.: Using Ontologies to Resolve Semantic Heterogeneity for Integrating Spatial Database Schemata. PhD thesis Zurich University (2003)
Hess, G.N., Iochpe, C.: Ontology-driven resolution of semantic heterogeneities in gdb conceptual schemas. In: Proceedings of the GEOINFO 2004: VI Brazilian Symposium on GeoInformatics (2004)
Fonseca, F.T.: Ontology-Driven Geographic Information Systems, The University of Maine (2001)
ESDIG. Diccionario del Espacio Digital Geografico ESDIG (2010), http://infoteca.semarnat.gob.mx/website/diccionario/diccionario_d.html (cited 2010 Enero)
Pekalska, E., Duin, R.P.W.: The dissimilarity representation for pattern recognition. Foundations and Applications 64 (2005)
Lehmann, F.: Semantic networks. Computers Math. Applic. 23, 1–50 (1992)
Minsky, M.: A framework for representing knowledge. In: Winston, P.H. (ed.) The Psychology of Computer Vision. McGraw-Hill, New York (1975)
Gruber, T.: Ontolingua: A mechanism to support portable ontologies. Stanford University, Stanford (1992)
Studer, S., Benjamins, R., Fensel, D.: Knowledge Engineering: Principles and Methods. Data and Knowledge Engineering (1998)
Guarino, N.: Formal Ontology and Information Systems. In: Proceedings of FOIS 1998. National Research Council, LADSEB–CNR (1998)
Fix, E., Hodges, J.L.: Discriminatory analysis, nonparametric discrimination: Consistency properties. Technical Report 4, USAF School of Aviation Medicine, Randolph Field, Texas (1951)
Backhaus, K., et al.: Multivariate analysis methods. In: An application-oriented introduction. Springer, Berlin (2000)
IDERC: Infraestructura de Datos Espaciales de la República de Cuba (2010), http://www.iderc.co.cu/ (cited 2010 Marzo)
ESRI: ESRI Home Page (2010), http://www.esri.com/ (cited 2010 Enero)
Egenhhofer, M.J.: A model for detailed binary topological relationships. Geomatica 47(3&4) (1993)
Larin-Fonseca, R., Garea-Llano, E.: Topological Relations as Rule for Automatic Generation of Geospatial Application Ontology. In: Proceedings of VII Jornadas para el Desarrollo de Grandes Aplicaciones de Red (2010) (in press)
Duin, R.P.W., et al.: DisTools A Matlab Toolbox for Pattern Recognition Delft Pattern Recognition Research, Faculty EWI - ICT, Delft University of Technology, The Netherlands (2009), http://prtools.org
Duin, R.P.W., et al.: PRTools4 A Matlab Toolbox for Pattern Recognition Version 4.1.5. Delft Pattern Recognition Research, Faculty EWI - ICT, Delft University of Technology, The Netherlands (2009), http://prtools.org
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fonseca, R.L., Garea Llano, E. (2010). Automatic Representation of Semantic Abstraction of Geographical Data by Means of Classification. In: Bloch, I., Cesar, R.M. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2010. Lecture Notes in Computer Science, vol 6419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16687-7_73
Download citation
DOI: https://doi.org/10.1007/978-3-642-16687-7_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16686-0
Online ISBN: 978-3-642-16687-7
eBook Packages: Computer ScienceComputer Science (R0)