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Synchronising geometric representations for map mashups using relative positioning and Linked Data

Huang, Weiming LU ; Mansourian, Ali LU ; Abdolmajidi, Ehsan LU ; Xu, Haiqi and Harrie, Lars LU orcid (2018) In International Journal of Geographical Information Science 32(6). p.1117-1137
Abstract

Map mashups, as a common way of presenting geospatial information on the Web, are generally created by spatially overlaying thematic information on top of various base maps. This simple overlay approach often raises geometric deficiencies due to geometric uncertainties in the data. This issue is particularly apparent in a multi-scale context because the thematic data seldom have synchronised level of detail with the base map. In this study, we propose, develop, implement and evaluate a relative positioning approach based on shared geometries and relative coordinates to synchronise geometric representations for map mashups through several scales. To realise the relative positioning between datasets, we adopt a Linked Data–based technical... (More)

Map mashups, as a common way of presenting geospatial information on the Web, are generally created by spatially overlaying thematic information on top of various base maps. This simple overlay approach often raises geometric deficiencies due to geometric uncertainties in the data. This issue is particularly apparent in a multi-scale context because the thematic data seldom have synchronised level of detail with the base map. In this study, we propose, develop, implement and evaluate a relative positioning approach based on shared geometries and relative coordinates to synchronise geometric representations for map mashups through several scales. To realise the relative positioning between datasets, we adopt a Linked Data–based technical framework in which the data are organised according to ontologies that are designed based on the GeoSPARQL vocabulary. A prototype system is developed to demonstrate the feasibility and usability of the relative positioning approach. The results show that the approach synchronises and integrates the geometries of thematic data and the base map effectively, and the thematic data are automatically tailored for multi-scale visualisation. The proposed framework can be used as a new way of modelling geospatial data on the Web, with merits in terms of both data visualisation and querying.

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Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
geometry synchronisation, Linked Data, Map mashups, multiple representation, relative positioning
in
International Journal of Geographical Information Science
volume
32
issue
6
pages
1117 - 1137
publisher
Taylor & Francis
external identifiers
  • scopus:85042925886
ISSN
1365-8816
DOI
10.1080/13658816.2018.1441416
language
English
LU publication?
yes
id
2a5b4942-ed19-494a-a72f-29c80e619fc2
date added to LUP
2018-03-14 18:02:28
date last changed
2021-10-06 01:42:49
@article{2a5b4942-ed19-494a-a72f-29c80e619fc2,
  abstract     = {<p>Map mashups, as a common way of presenting geospatial information on the Web, are generally created by spatially overlaying thematic information on top of various base maps. This simple overlay approach often raises geometric deficiencies due to geometric uncertainties in the data. This issue is particularly apparent in a multi-scale context because the thematic data seldom have synchronised level of detail with the base map. In this study, we propose, develop, implement and evaluate a relative positioning approach based on shared geometries and relative coordinates to synchronise geometric representations for map mashups through several scales. To realise the relative positioning between datasets, we adopt a Linked Data–based technical framework in which the data are organised according to ontologies that are designed based on the GeoSPARQL vocabulary. A prototype system is developed to demonstrate the feasibility and usability of the relative positioning approach. The results show that the approach synchronises and integrates the geometries of thematic data and the base map effectively, and the thematic data are automatically tailored for multi-scale visualisation. The proposed framework can be used as a new way of modelling geospatial data on the Web, with merits in terms of both data visualisation and querying.</p>},
  author       = {Huang, Weiming and Mansourian, Ali and Abdolmajidi, Ehsan and Xu, Haiqi and Harrie, Lars},
  issn         = {1365-8816},
  language     = {eng},
  month        = {06},
  number       = {6},
  pages        = {1117--1137},
  publisher    = {Taylor & Francis},
  series       = {International Journal of Geographical Information Science},
  title        = {Synchronising geometric representations for map mashups using relative positioning and Linked Data},
  url          = {http://dx.doi.org/10.1080/13658816.2018.1441416},
  doi          = {10.1080/13658816.2018.1441416},
  volume       = {32},
  year         = {2018},
}