• DocumentCode
    29454
  • Title

    An Efficient Framework for Generating Storyline Visualizations from Streaming Data

  • Author

    Tanahashi, Yuzuru ; Chien-Hsin Hsueh ; Kwan-Liu Ma

  • Author_Institution
    VIDI Res. Group, Univ. California, Davis, CA, USA
  • Volume
    21
  • Issue
    6
  • fYear
    2015
  • fDate
    June 1 2015
  • Firstpage
    730
  • Lastpage
    742
  • Abstract
    This paper presents a novel framework for applying storyline visualizations to streaming data. The framework includes three components: a new data management scheme for processing and storing the incoming data, a layout construction algorithm specifically designed for incrementally generating storylines from streaming data, and a layout refinement algorithm for improving the legibility of the visualization. By dividing the layout computation to two separate components, one for constructing and another for refining, our framework effectively provides the users with the ability to follow and reason dynamic data. The evaluation studies of our storyline visualization framework demonstrate its efficacy to present streaming data as well as its superior performance over existing methods in terms of both computational efficiency and visual clarity.
  • Keywords
    data visualisation; humanities; inference mechanisms; computational efficiency; data management scheme; data streaming; layout computation; layout construction algorithm; layout refinement algorithm; storyline visualization framework; storyline visualization generation; visual clarity; Algorithm design and analysis; Data visualization; Feeds; Layout; Optimization; Social network services; Visualization; Storyline visualization; layout algorithms; streaming data; time-varying data;
  • fLanguage
    English
  • Journal_Title
    Visualization and Computer Graphics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1077-2626
  • Type

    jour

  • DOI
    10.1109/TVCG.2015.2392771
  • Filename
    7015617