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Multiple Representation for Geospatial Linked Data

Huang, Weiming LU ; Eidsson, Eidur and Harrie, Lars LU (2018)
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Geovisualisation, Linked Data, Multiple representation, INSPIRE RDF vocabularies, Scale
host publication
Geospatial Technologies for All
editor
Mansourian, Ali; Pilesjö, Petter; Harrie, Lars; van Lammeren, Ron; ; ; and
pages
6 pages
publisher
AGILE, Association of Geographic Information Laboratories for Europe
ISBN
978-3-319-78208-9
language
English
LU publication?
yes
id
805b22be-05bb-4ea2-bf53-68f13d1151ba
alternative location
https://agile-online.org/conference_paper/cds/agile_2018/shortpapers/112%20AGILE%202018_Huang%20et%20al..pdf
date added to LUP
2019-02-10 08:00:41
date last changed
2019-03-08 02:35:47
@inproceedings{805b22be-05bb-4ea2-bf53-68f13d1151ba,
  abstract     = {Current techniques for visualising geospatial Linked Data are limited in terms of multiple representation, which has been studied for decades by cartographers and <br/>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.},
  author       = {Huang, Weiming and Eidsson, Eidur and Harrie, Lars},
  editor       = {Mansourian, Ali and Pilesjö, Petter and Harrie, Lars and van Lammeren, Ron},
  isbn         = {978-3-319-78208-9},
  keyword      = {Geovisualisation,Linked Data,Multiple representation,INSPIRE RDF vocabularies,Scale},
  language     = {eng},
  pages        = {6},
  publisher    = {AGILE, Association of Geographic Information Laboratories for Europe},
  title        = {Multiple Representation for Geospatial Linked Data},
  year         = {2018},
}