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