Visualizing Hierarchical Time Series with a Focus+Context Approach

An approach to convey the hierarchical structure of multiple time series


What is...?

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. Our approach extends a Streamgraph visualization to convey this hierarchical structure. Based on a focus+context technique, our method allows time series exploration at different granularities (e.g., from overview to details).

Poster | Extended abstract | Video

E. Cuenca, A. Sallaberry, F. Y. Wang, P. Poncelet. Visualizing Hierarchical Time Series with a Focus+Context Approach. IEEE Information Visualization Conference (InfoVis 2017), 2017.

Datasets available

  • Sentiment analysis of political events:
    • 2016 US presidential election day
    • 2013 Australian presidential period
  • Sentiment analysis of sporting events:
    • 2016 UEFA Champions league final
    • 2014 Rugby union match
  • Other datasets:
    • Music genre evolution

Visualize an example


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