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Grouping Time-Varying Data for Interactive Exploration

Authors Arthur van Goethem, Marc van Kreveld, Maarten Löffler, Bettina Speckmann, Frank Staals

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Arthur van Goethem
Marc van Kreveld
Maarten Löffler
Bettina Speckmann
Frank Staals

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Arthur van Goethem, Marc van Kreveld, Maarten Löffler, Bettina Speckmann, and Frank Staals. Grouping Time-Varying Data for Interactive Exploration. In 32nd International Symposium on Computational Geometry (SoCG 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 51, pp. 61:1-61:16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2016)


We present algorithms and data structures that support the interactive analysis of the grouping structure of one-, two-, or higher-dimensional time-varying data while varying all defining parameters. Grouping structures characterise important patterns in the temporal evaluation of sets of time-varying data. We follow Buchin et al. [JoCG 2015] who define groups using three parameters: group-size, group-duration, and inter-entity distance. We give upper and lower bounds on the number of maximal groups over all parameter values, and show how to compute them efficiently. Furthermore, we describe data structures that can report changes in the set of maximal groups in an output-sensitive manner. Our results hold in R^d for fixed d.
  • Trajectory
  • Time series
  • Moving entity
  • Grouping
  • Algorithm
  • Data structure


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