STBins: visual tracking and comparison of multiple data sequences using temporal binning

Ji Qi, Vincent Bloemen, Shihan Wang, Jarke van Wijk, Huub van de Wetering

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

While analyzing multiple data sequences, the following questions typically arise: how does a single sequence change over time, how do multiple sequences compare within a period, and how does such comparison change over time. This paper presents a visual technique named STBins to answer these questions. STBins is designed for visual tracking of individual data sequences and also for comparison of sequences. The latter is done by showing the similarity of sequences within temporal windows. A perception study is conducted to examine the readability of alternative visual designs based on sequence tracking and comparison tasks. Also, two case studies based on real-world datasets are presented in detail to demonstrate usage of our technique.

Original languageEnglish
Article number8805450
Pages (from-to)1054-1063
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Volume26
Issue number1
DOIs
Publication statusPublished - Jan 2020

Keywords

  • data sequence
  • time series data
  • Visualization

Cite this

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STBins : visual tracking and comparison of multiple data sequences using temporal binning. / Qi, Ji; Bloemen, Vincent; Wang, Shihan; van Wijk, Jarke; van de Wetering, Huub.

In: IEEE Transactions on Visualization and Computer Graphics, Vol. 26, No. 1, 8805450, 01.2020, p. 1054-1063.

Research output: Contribution to journalArticleAcademicpeer-review

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