Wavelet-based visualization of time-varying data on graphs

Paola Valdivia, Fabio Dias, Fabiano Petronetto, Cláudio T. Silva, L. G. Nonato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Visualizing time-varying data defined on the nodes of a graph is a challenging problem that has been faced with different approaches. Although techniques based on aggregation, topology, and topic modeling have proven their usefulness, the visual analysis of smooth and/or abrupt data variations as well as the evolution of such variations over time are aspects not properly tackled by existing methods. In this work we propose a novel visualization methodology that relies on graph wavelet theory and stacked graph metaphor to enable the visual analysis of time-varying data defined on the nodes of a graph. The proposed method is able to identify regions where data presents abrupt and mild spacial and/or temporal variation while still been able to show how such changes evolve over time, making the identification of events an easier task. The usefulness of our approach is shown through a set of results using synthetic as well as a real data set involving taxi trips in downtown Manhattan. The methodology was able to reveal interesting phenomena and events such as the identification of specific locations with abrupt variation in the number of taxi pickups.

Original languageEnglish (US)
Title of host publication2015 IEEE Conference on Visual Analytics Science and Technology, VAST 2015 - Proceedings
EditorsMin Chen, Gennady Andrienko
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781467397834
DOIs
StatePublished - Dec 4 2015
Event10th IEEE Conference on Visual Analytics Science and Technology, VAST 2015 - Chicago, United States
Duration: Oct 25 2015Oct 30 2015

Publication series

Name2015 IEEE Conference on Visual Analytics Science and Technology, VAST 2015 - Proceedings

Other

Other10th IEEE Conference on Visual Analytics Science and Technology, VAST 2015
CountryUnited States
CityChicago
Period10/25/1510/30/15

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Keywords

  • Time-varying data
  • graph wavelets
  • stacked graph visualization

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Cite this

Valdivia, P., Dias, F., Petronetto, F., Silva, C. T., & Nonato, L. G. (2015). Wavelet-based visualization of time-varying data on graphs. In M. Chen, & G. Andrienko (Eds.), 2015 IEEE Conference on Visual Analytics Science and Technology, VAST 2015 - Proceedings (pp. 1-8). [7347624] (2015 IEEE Conference on Visual Analytics Science and Technology, VAST 2015 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VAST.2015.7347624