Multiple Representation for Geospatial Linked Data
(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:
https://lup.lub.lu.se/record/805b22be-05bb-4ea2-bf53-68f13d1151ba
- author
- Huang, Weiming LU ; Eidsson, Eidur and Harrie, Lars LU
- organization
- publishing date
- 2018
- 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 : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden - short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden
- editor
- Mansourian, Ali ; Pilesjö, Petter ; Harrie, Lars and van Lammeren, Ron
- pages
- 6 pages
- publisher
- 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
- 2021-01-20 13:24:52
@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}}, booktitle = {{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}}, editor = {{Mansourian, Ali and Pilesjö, Petter and Harrie, Lars and van Lammeren, Ron}}, isbn = {{978-3-319-78208-9}}, keywords = {{Geovisualisation; Linked Data; Multiple representation; INSPIRE RDF vocabularies; Scale}}, language = {{eng}}, publisher = {{Association of Geographic Information Laboratories for Europe}}, title = {{Multiple Representation for Geospatial Linked Data}}, url = {{https://agile-online.org/conference_paper/cds/agile_2018/shortpapers/112%20AGILE%202018_Huang%20et%20al..pdf}}, year = {{2018}}, }