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Automatic Expansion of Spatial Ontologies for Geographic Information Retrieval

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations (IPMU 2018)

Abstract

One of the most prominent scenarios for capturing implicit knowledge from heterogeneous data sources concerns the geospatial data domain. In this scenario, ontologies play a key role for managing the totality of geospatial concepts, categories and relations at different resolutions. However, the manual development of geographic ontologies implies an exhausting work due to the rapid growth of the data available on the Internet. In order to address this challenge, the present work describes a semi-automatic approach to build and expand a geographic ontology by integrating the information provided by diverse spatial data sources. The generated ontology can be used as a knowledge resource in a Geographic Information Retrieval system. As a main novelty, the use of OWL 2 as an ontology language allowed us to model and infer new spatial relationships, regarding the use of other less expressive languages such as RDF or OWL 1. Two different spatial ontologies were generated for two specific geographic regions by applying the proposed approach, and the evaluation results showed their suitability to be used as geographic-knowledge resources in Geographic Information Retrieval contexts.

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Notes

  1. 1.

    MBR is an expression of the maximum extents of a 2-dimensional object (e.g. point, line, polygon). MBRs are frequently used as an indication of the general position of a geographic feature.

  2. 2.

    http://geoknow.eu.

  3. 3.

    http://www.w3.org/TR/rdf-concepts.

  4. 4.

    http://www.w3.org/OWL.

  5. 5.

    http://linkedgeodata.org.

  6. 6.

    http://www.geonames.org. GeoNames is an open access geographic database that contains more than eight million place names from all countries in the world.

  7. 7.

    http://wordnet.princeton.edu.

  8. 8.

    http://www.openstreetmap.org. OSM is a collaborative project inspired by Wikipedia that emerged to create an editable and free world map where, instead of editing articles as in Wikipedia, users edit geographic entities.

  9. 9.

    http://www.w3.org/TR/owl2-overview.

  10. 10.

    http://protege.stanford.edu.

  11. 11.

    http://www.geonames.org/ontology/ontology_v3.1.rdf.

  12. 12.

    http://www.opengeospatial.org/standards/wkt-crs.

  13. 13.

    http://jaryard.com/projects/osm4j/.

  14. 14.

    http://github.com/Esri/geometry-api-java.

  15. 15.

    http://population.city/cuba/marianao.

  16. 16.

    http://population.city/mexico/acapulco-de-juarez.

  17. 17.

    http://www.iderc.cu.

  18. 18.

    http://www.iderc.cu/geoserver/web.

  19. 19.

    OOPS! (OntOlogy Pitfall Scanner!). http://oops.linkeddata.es.

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Acknowledgments

This work has been partially supported by FEDER and the State Research Agency (AEI) of the Spanish Ministry of Economy and Competition under grant MERINET: TIN2016-76843-C4-2-R (AEI/FEDER, UE).

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Correspondence to José M. Perea-Ortega .

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Puebla-Martínez, M.E., Perea-Ortega, J.M., Simón-Cuevas, A., Romero, F.P. (2018). Automatic Expansion of Spatial Ontologies for Geographic Information Retrieval. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 854. Springer, Cham. https://doi.org/10.1007/978-3-319-91476-3_54

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  • DOI: https://doi.org/10.1007/978-3-319-91476-3_54

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