Visualizing Hierarchical Time Series with a Focus+Context Approach

Abstract : Multiple time series are present in many domains such as medicine, finance, and manufacturing for analytical purposes. When dealing with several time series scalability problem overcome. To solve this problem, multiple time series can be organized into a hierarchical structure. In this work, we introduce a Streamgraph-based approach to convey this hierarchical structure. Based on a focus+context technique, our visualization allows time series exploration at different granularities (e. g., from overview to details). A demo is available at http://advanse.lirmm.fr/hierarchical/.
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Poster
INFOVIS, Oct 2017, Phoenix, United States. IEEE VIS 2017, 2017, 〈http://ieeevis.org〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01592614
Contributeur : Erick Cuenca <>
Soumis le : lundi 25 septembre 2017 - 11:06:54
Dernière modification le : jeudi 11 janvier 2018 - 06:27:21
Document(s) archivé(s) le : mardi 26 décembre 2017 - 13:02:31

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  • HAL Id : lirmm-01592614, version 1

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Erick Cuenca, Arnaud Sallaberry, Florence Wang, Pascal Poncelet. Visualizing Hierarchical Time Series with a Focus+Context Approach. INFOVIS, Oct 2017, Phoenix, United States. IEEE VIS 2017, 2017, 〈http://ieeevis.org〉. 〈lirmm-01592614〉

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