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Uncertainty visualization of multi-providers cartographic integration.

Authors :
Berjawi, Bilal
Duchateau, Fabien
Chesneau, Élisabeth
Favetta, Franck
Seccia, Geoffrey
Cunty, Claire
Miquel, Maryvonne
Laurini, Robert
Source :
Journal of Visual Languages & Computing. Dec2014, Vol. 25 Issue 6, p995-1002. 8p.
Publication Year :
2014

Abstract

Multiple cartographic providers propose services displaying points of interests (POI) on maps. However, the provided POIs are often incomplete and contradictory from one provider to another. Previous works proposed solutions for detecting correspondences between spatial entities that refer to the same geographic object. Although one can visualize the result of the integration of corresponding entities, users do not have any information about the quality of this integration. In this paper, we propose a solution to visualize the uncertainty inherent to a spatial integration algorithm. We present an integration process that identifies three levels of confidence for spatial and terminological integration results. Based on perceptual tests, we select visual variables to portray these three levels of confidence and we choose a visualization strategy. A prototype has been implemented to present the benefits of our proposal in a use-case scenario. This work has been realized within the framework of UNIMAP 1 1 UNIMAP: http://liris.cnrs.fr/unimap (July 2014). project. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1045926X
Volume :
25
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Visual Languages & Computing
Publication Type :
Academic Journal
Accession number :
99900309
Full Text :
https://doi.org/10.1016/j.jvlc.2014.10.033