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Weiming Huang

Weiming Huang


Weiming Huang

Multiple Representation for Geospatial Linked Data


  • Weiming Huang
  • Eidur Eidsson
  • Lars Harrie


  • Ali Mansourian
  • Petter Pilesjö
  • Lars Harrie
  • Ron van Lammeren

Summary, in English

Current techniques for visualising geospatial Linked Data are limited in terms of multiple representation, which has been studied for decades by cartographers and
considered as a prerequisite for deriving appropriate geovisualisation applications. In order to alleviate this issue, this paper presents a work in progress, in which the multiple representation geospatial data are released as Linked Data, and linked to the Linked Data gazetteer GeoNames. In the study, we use extended INSPIRE draft RDF vocabularies to explicitly link multiple representations and their visualisation scales. The results show that the released multiple representation geospatial Linked Data can effectively enrich the geometric information for the test data in GeoNames, and provide better visualisation performance.


  • Dept of Physical Geography and Ecosystem Science
  • Centre for Geographical Information Systems (GIS Centre)
  • eSSENCE: The e-Science Collaboration

Publishing year





Geospatial Technologies for All : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden

Document type

Conference paper


Association of Geographic Information Laboratories for Europe


  • Computer Science
  • Environmental Sciences
  • Other Engineering and Technologies not elsewhere specified


  • Geovisualisation
  • Linked Data
  • Multiple representation
  • INSPIRE RDF vocabularies
  • Scale




  • ISBN: 978-3-319-78208-9