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 communications
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01592614
Contributor : Erick Cuenca <>
Submitted on : Monday, September 25, 2017 - 11:06:54 AM
Last modification on : Friday, September 13, 2019 - 4:20:03 PM
Long-term archiving on : Tuesday, December 26, 2017 - 1:02:31 PM

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Erick Cuenca Pauta, Arnaud Sallaberry, Florence Wang, Pascal Poncelet. Visualizing Hierarchical Time Series with a Focus+Context Approach. INFOVIS@VIS, Oct 2017, Phoenix, United States. Conference on Scientific Visualization, Information Visualization and Visual Analytics, 2017. ⟨lirmm-01592614⟩

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