Microtheories for Spatial Data Infrastructures - Accounting for Diversity of Local Conceptualizations at a Global Level

  • Stephanie Duce
  • Krzysztof Janowicz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6292)

Abstract

The categorization of our environment into feature types is an essential prerequisite for cartography, geographic information retrieval, routing applications, spatial decision support systems, and data sharing in general. However, there is no a priori conceptualization of the world and the creation of features and types is an act of cognition. Humans conceptualize their environment based on multiple criteria such as their cultural background, knowledge, motivation, and particularly by space and time. Sharing and making these conceptualizations explicit in a formal, unambiguous way is at the core of semantic interoperability. One way to cope with semantic heterogeneities is by standardization, i.e., by agreeing on a shared conceptualization. This bears the danger of losing local diversity. In contrast, this work proposes the use of microtheories for Spatial Data Infrastructures, such as INSPIRE, to account for the diversity of local conceptualizations while maintaining their semantic interoperability at a global level. We introduce a novel methodology to structure ontologies by spatial and temporal aspects, in our case administrative boundaries, which reflect variations in feature conceptualization. A local, bottom-up approach, based on non-standard inference, is used to compute global feature definitions which are neither too broad nor too specific. Using different conceptualizations of rivers and other geographic feature types, we demonstrate how the present approach can improve the INSPIRE data model and ease its adoption by European member states.

Keywords

Ontology Geo-Semantics Semantic Heterogeneity 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Kuhn, W.: Semantic engineering. In: Navratil, G. (ed.) Research Trends in Geographic Information Science, pp. 63–74. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  2. 2.
    Fisher, P.: Sorites paradox and vague geographies. Fuzzy Sets and Systems 113, 7–18 (2000)CrossRefGoogle Scholar
  3. 3.
    Smith, B., Mark, D.M.: Do mountains exist? towards an ontology of landforms. Environment and Planning B: Planning and Design 20(2), 411–427 (2003)CrossRefGoogle Scholar
  4. 4.
    Mark, D.M.: Toward a theoretical framework for geographic entity types. In: Campari, I., Frank, A.U. (eds.) COSIT 1993. LNCS, vol. 716, pp. 270–283. Springer, Heidelberg (1993)Google Scholar
  5. 5.
    Bennett, B., Mallenby, D., Third, A.: An ontology for grounding vague geographic terms. In: Formal Ontology in Information Systems - Proceedings of the Fifth International Conference (FOIS 2008), vol. 183, pp. 280–293. IOS Press, Amsterdam (2008)Google Scholar
  6. 6.
    Smith, B., Mark, D.M.: Ontology and geographic kinds. In: International Symposium on Spatial Data Handling, Vancouver, Canada, pp. 308–320 (1998)Google Scholar
  7. 7.
    Frank, A.: A linguistically justified proposal for a spatiotemporal ontology. In: Kuhn, W., Worboys, M.F., Timpf, S. (eds.) COSIT 2003. LNCS, vol. 2825. Springer, Heidelberg (2003)Google Scholar
  8. 8.
    Egenhofer, M., Mark, D.M.: Naive geography. In: Kuhn, W., Frank, A.U. (eds.) COSIT 1995. LNCS, vol. 988, pp. 1–15. Springer, Heidelberg (1995)Google Scholar
  9. 9.
    Bishr, Y.: Overcoming the semantic and other barriers to gis interoperability. International Journal of Geographical Information Science 12(4), 299–314 (1998)CrossRefGoogle Scholar
  10. 10.
    Comber, A., Fisher, P.: What is land cover? Environment and Planning B: Planning and Design 32, 199–209 (2005)CrossRefGoogle Scholar
  11. 11.
    Kuhn, W.: Geospatial semantics: Why, of what and how? Journal of Data Semantics III, 1–24 (2005)CrossRefGoogle Scholar
  12. 12.
    Lund, H.G.: Definitions of forest, deforestation, afforestation, and reforestation. Technical report, Forest Information Services (2009), http://home.comcast.net/~gyde/DEFpaper.htm
  13. 13.
    Janowicz, K., Maue, P., Wilkes, M., Schade, S., Scherer, F., Braun, M., Dupke, S., Kuhn, W.: Similarity as a quality indicator in ontology engineering. In: Eschenbach, C., Grueninger, M. (eds.) 5th International Conference on Formal Ontology in Information Systems (FOIS 2008), pp. 92–105. IOS Press, Amsterdam (2008)Google Scholar
  14. 14.
    Uschold, M.: Creating, integrating and maintaining local and global ontologies. In: Horn, W. (ed.) Proceedings of 14th European Conference on Artificial Intelligence (ECAI 2000). IOS Press, Amsterdam (2000)Google Scholar
  15. 15.
    McCarthy, J.: Generality in artificial intelligence. Communications of the ACM 30, 1030–1035 (1987)MATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Wachsmuth, I.: The concept of intelligence in ai. Prerational Intelligence – Adaptive Behavior and Intelligent Systems without Symbols and Logic 1, 43–55 (2000)Google Scholar
  17. 17.
    Smith, B., Casati, R.: Naive physics: An essay in ontology. Philosophical Psychology 7/2, 225–244 (1994)Google Scholar
  18. 18.
    Grau, B., Kazakov, Y., Sattler, U.: A logical framework for modularity of ontologies. In: 20th International Joint Conference on Artificial Intelligence, pp. 183–196 (2007)Google Scholar
  19. 19.
    Bateman, J., Borgo, S., Luettich, K., Masolo, C., Mossakowski, T.: Ontological modularity and spatial diversity. Spatial Cognition and Computation 7, 97–128 (2007)Google Scholar
  20. 20.
    Hois, J., Bhatt, M., Kutz, O.: Modular ontologies for architectural design. In: Ferrario, R., Oltramari, A. (eds.) Formal Ontologies Meet Industry, pp. 66–78. IOS Press, Amsterdam (2009)Google Scholar
  21. 21.
    Kokla, M., Kavouras, M.: Fusion of top-level and geographic domain ontologies based on context formation and complementarity. International Journal of Geographical Information Science 15, 679–687 (2001)CrossRefGoogle Scholar
  22. 22.
    Kavouras, M., Kokla, M.: A method for the formalization and integration of geographic categorizations. International Journal of Geographical Information Science 16, 439–453 (2002)CrossRefGoogle Scholar
  23. 23.
    Guha, R., Mccool, R., Fikes, R.: Contexts for the semantic web. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 32–46. Springer, Heidelberg (2004)Google Scholar
  24. 24.
    Janowicz, K.: The role of place for the spatial referencing of heritage data. In: The Cultural Heritage of Historic European Cities and Public Participatory GIS Workshop, The University of York, UK, September 17-18 (2009)Google Scholar
  25. 25.
    Küsters, R.: Non-Standard Inferences in Description Logics. In: Küsters, R. (ed.) Non-Standard Inferences in Description Logics. LNCS (LNAI), vol. 2100, p. 33. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  26. 26.
  27. 27.
    Hovy, E.: Comparing Sets of Semantic Relations in Ontologies. In: The Semantics of Relationships: An Interdisciplinary Perspective. Kluwer Publishers, Dordrecht (2002)Google Scholar
  28. 28.
    Brodaric, B., Gahegan, M.: Distinguishing instances and evidence of geographical concepts for geospatial database design. In: Egenhofer, M.J., Mark, D.M. (eds.) GIScience 2002. LNCS, vol. 2478, pp. 22–37. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  29. 29.
    Egenhofer, M.: Toward the semantic geospatial web. In: GIS 2002: Proceedings of the 10th ACM international symposium on Advances in geographic information systems, pp. 1–4. ACM, New York (2002)CrossRefGoogle Scholar
  30. 30.
    Lakoff, G., Johnson, M.: Metaphors We Live By. University Of Chicago Press, Chicago (1980)Google Scholar
  31. 31.
    McCarthy, J., Buvac, S.: Formalizing context (expanded notes) (1996)Google Scholar
  32. 32.
    Janowicz, K., Kessler, C., Schwarz, M., Wilkes, M., Panov, I., Espeter, M., Baeumer, B.: Algorithm, implementation and application of the sim-dl similarity server. In: Fonseca, F., Rodríguez, M.A., Levashkin, S. (eds.) GeoS 2007. LNCS, vol. 4853, pp. 128–145. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  33. 33.
    Janowicz, K., Wilkes, M.: SIM-DL_A: A novel semantic similarity measure for description logics reducing inter-concept to inter-instance similarity. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M., Simperl, E. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 353–367. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  34. 34.
    Taylor, M., Stokes, R.: Up the creek: What is wrong with the definition of a river in new south wales? Environment and Planning Law Journal 22(3), 193–211 (2005)Google Scholar
  35. 35.
    Taylor, M.P., Stokes, R.: When is a river not a river? consideration of the legal definition of a river for geomorphologists practising in new south wales, australia. Australian Geographer 36(2), 183–200 (2005)CrossRefGoogle Scholar
  36. 36.
    Kuhn, W.: Ontologies in support of activities in geographical space. International Journal of Geographical Information Science 15(7), 613–631 (2001)CrossRefGoogle Scholar
  37. 37.
    Masolo, C., Borgo, S., Gangemi, A., Guarino, N., Oltrami, A.: Ontology library deliverable d18. Technical report, ISTC-CNR (2003)Google Scholar
  38. 38.
    Kuhn, W.: A functional ontology of observation and measurement. In: Janowicz, K., Raubal, M., Levashkin, S. (eds.) GeoS 2009. LNCS, vol. 5892, pp. 26–43. Springer, Heidelberg (2009)Google Scholar
  39. 39.
    Cohen, W., Borgida, A., Hirsh, H.: Computing least common subsumers in description logics. In: Proceedings of the 10th National Conference on Artificial Intelligence, pp. 754–760. MIT Press, Cambridge (1992)Google Scholar
  40. 40.
    Baader, F., Sertkaya, B., Turhan, A.Y.: Computing the least common subsumer w.r.t. a background terminology. Journal of Applied Logic 5(3), 392–420 (2007)MATHCrossRefMathSciNetGoogle Scholar
  41. 41.
    Janowicz, K., Wilkes, M., Lutz, M.: Similarity-based information retrieval and its role within spatial data infrastructures. In: Cova, T.J., Miller, H.J., Beard, K., Frank, A.U., Goodchild, M.F. (eds.) GIScience 2008. LNCS, vol. 5266, pp. 151–167. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  42. 42.
    Janowicz, K., Schade, S., Bröring, A., Keßler, C., Maue, P., Stasch, C.: Semantic enablement for spatial data infrastructures. Transactions in GIS 14(2), 111–129 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Stephanie Duce
    • 1
  • Krzysztof Janowicz
    • 2
  1. 1.Department of Languages and SystemsUniversity Juame ISpain
  2. 2.Department of GeographyThe Pennsylvania State UniversityUSA

Personalised recommendations