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Weiming Huang

Forskare

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

Författare

  • 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.

Avdelning/ar

  • Institutionen för naturgeografi och ekosystemvetenskap
  • eSSENCE: The e-Science Collaboration

Publiceringsår

2020

Språk

Engelska

Sidor

976-997

Publikation/Tidskrift/Serie

International Journal of Digital Earth

Volym

13

Issue

9

Dokumenttyp

Artikel i tidskrift

Förlag

Taylor & Francis

Ämne

  • Other Earth and Related Environmental Sciences
  • Information Systems

Nyckelord

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

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 1753-8947