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		<doi>10.1109/SIBGRAPI.2019.00014</doi>
		<citationkey>MeninCharDavoNede:2019:ToAlGe</citationkey>
		<title>eSTIMe: Towards an All-in-One Geovisualization Environment for Daily Mobility Analysis</title>
		<format>On-line</format>
		<year>2019</year>
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		<author>Menin, Aline,</author>
		<author>Chardonnel, Sonia,</author>
		<author>Davoine, Paule-Annick,</author>
		<author>Nedel, Luciana,</author>
		<affiliation>Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG, 38000 Grenoble, France</affiliation>
		<affiliation>Univ. Grenoble Alpes, CNRS, Science Po Grenoble, PACTE, 38000 Grenoble, France</affiliation>
		<affiliation>Univ. Grenoble Alpes, CNRS, Science Po Grenoble, PACTE and Grenoble INP, LIG, 38000 Grenoble, France</affiliation>
		<affiliation>Federal University of Rio Grande do Sul, Institute of Informatics, Porto Alegre, Brazil</affiliation>
		<editor>Oliveira, Luciano Rebouças de,</editor>
		<editor>Sarder, Pinaki,</editor>
		<editor>Lage, Marcos,</editor>
		<editor>Sadlo, Filip,</editor>
		<e-mailaddress>aline.menin@univ-grenoble-alpes.fr</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 32 (SIBGRAPI)</conferencename>
		<conferencelocation>Rio de Janeiro, RJ, Brazil</conferencelocation>
		<date>28-31 Oct. 2019</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
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		<versiontype>finaldraft</versiontype>
		<keywords>geovisualization, daily mobility analysis, movement data, geovisual analysis.</keywords>
		<abstract>Daily mobility data describe individual displacements over 24 hours and make up an important source of information to help identify the real rhythm of a city which serve as a support for decision-making regarding transportation policies and other investments. Designing effective geovisualization environment for exploring this data evoke multiple challenges, since the analysis requires a simultaneous exploration of various mobility indicators at different spatial and temporal granular levels. Visual data analysis largely use coordinate \& multiple views (CMV) since they support the combination of space and time, and cartographic and graphic views. In this paper, we propose a multi-screen environment embedding customizable dashboards, which gives the user freedom to arrange views in useful and meaningful ways. We address the well-known issue of time representation by integrating a handheld device as a second screen which holds menus and widgets to communicate with the dashboards, and a movement-based interaction technique to control the time dimension of the data.</abstract>
		<language>en</language>
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