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Matching Formal and Informal Geospatial Ontologies

  • Heshan DuEmail author
  • Natasha Alechina
  • Mike Jackson
  • Glen Hart
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

The rapid development of crowd-sourcing or volunteered geographic information both challenges and provides opportunities to authoritative geospatial information. Matching geospatial ontologies is an essential element to realizing the synergistic use of disparate geospatial information. We propose a new semi-automatic method to match formal and informal real life geospatial ontologies, at both terminology level and instance level, ensuring that overall information is logically coherent and consistent. Disparate geospatial ontologies are matched by finding a consistent and coherent set of mapping axioms with respect to them. Disjointness axioms are generated in order to facilitate detection of errors. In contrast to other existing methods, disjointness axioms are seen as assumptions, which can be retracted during the overall process. We produce candidates for retraction automatically, but the ultimate decision is taken by domain experts. Geometry matching, lexical matching and cardinality checking are combined when matching geospatial individuals (spatial features).

Keywords

Domain Expert Geospatial Information Biomedical Ontology Ontology Match Local Ontology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Heshan Du
    • 1
    Email author
  • Natasha Alechina
    • 1
  • Mike Jackson
    • 1
  • Glen Hart
    • 2
  1. 1.The University of NottinghamNottinghamUK
  2. 2.Ordnance Survey of Great BritainSouthamptonUK

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