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LarsHarrie

Lars Harrie

Professor

LarsHarrie

Towards knowledge-based geovisualisation using Semantic Web technologies : a knowledge representation approach coupling ontologies and rules

Author

  • Weiming Huang
  • Lars Harrie

Summary, in English

Geovisualisation is a knowledge-intensive art in which both providers and users need to possess a wide range of knowledge. Current syntactic approaches to presenting visualisation information lack semantics on the one hand, and on the other hand are too bespoke. Such limitations impede the transfer, interpretation, and reuse of the geovisualisation knowledge. In this paper, we propose a knowledge-based approach to formally represent geovisualisation knowledge in a semantically-enriched and machine-readable manner using Semantic Web technologies. Specifically, we represent knowledge regarding cartographic scale, data portrayal and geometry source, which are three key aspects of geovisualisation in the contemporary web mapping era, coupling ontologies and semantic rules. The knowledge base enables inference for deriving the corresponding geometries and portrayals for visualisation under different conditions. A prototype system is developed in which geospatial linked data are used as underlying data, and some geovisualisation knowledge is formalised into a knowledge base to visualise the data and provide rich semantics to users. The proposed approach can partially form the foundation for the vision of web of knowledge for geovisualisation.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • eSSENCE: The e-Science Collaboration

Publishing year

2020

Language

English

Pages

976-997

Publication/Series

International Journal of Digital Earth

Volume

13

Issue

9

Document type

Journal article

Publisher

Taylor & Francis

Topic

  • Other Earth and Related Environmental Sciences
  • Information Systems

Keywords

  • Geovisuaisation
  • knowledge representation
  • ontologies
  • semantic rules
  • Semantic Web

Status

Published

ISBN/ISSN/Other

  • ISSN: 1753-8947