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Interpreting Heterogeneous Geospatial Data Using Semantic Web Technologies

  • Timo Homburg
  • Claire Prudhomme
  • Falk Würriehausen
  • Ashish Karmacharya
  • Frank Boochs
  • Ana Roxin
  • Christophe Cruz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9788)

Abstract

The paper presents work on implementation of semantic technologies within a geospatial environment to provide a common base for further semantic interpretation. The work adds on the current works in similar areas where priorities are more on spatial data integration. We assert that having a common unified semantic view on heterogeneous datasets provides a dimension that allows us to extend beyond conventional concepts of searchability, reusability, composability and interoperability of digital geospatial data. It provides contextual understanding on geodata that will enhance effective interpretations through possible reasoning capabilities. We highlight this through use cases in disaster management and planned land use that are significantly different. This paper illustrates the work that firstly follows existing Semantic Web standards when dealing with vector geodata and secondly extends current standards when dealing with raster geodata and more advanced geospatial operations.

Keywords

Heterogeneity Interoperability SDI CIP GeoSPARQL R2RML Semantification 

Notes

Acknowledgements

This project was funded by the German Federal Ministry of Education and Research (https://www.bmbf.de/en/index.html Project Reference: 03FH032IX4).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Timo Homburg
    • 1
  • Claire Prudhomme
    • 1
  • Falk Würriehausen
    • 1
  • Ashish Karmacharya
    • 1
  • Frank Boochs
    • 1
  • Ana Roxin
    • 2
  • Christophe Cruz
    • 2
  1. 1.Mainz University of Applied SciencesMainzGermany
  2. 2.Université de BourgogneDijonFrance

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