• DocumentCode
    3705612
  • Title

    StreamVisND: Visualizing relationships in streaming multivariate data

  • Author

    Shenghui Cheng; Yue Wang; Dan Zhang; Zhifang Jiang;Klaus Mueller

  • Author_Institution
    Visual Analytics and Imaging Lab, Computer Science Department, Stony Brook University and SUNY Korea
  • fYear
    2015
  • Firstpage
    191
  • Lastpage
    192
  • Abstract
    In streaming acquisitions the data changes over time. ThemeRiver and line charts are common methods to display data over time. However, these methods can only show the values of the variables (or attributes) but not the relationships among them over time. We propose a framework we call StreamVisND that can display these types of streaming data relations. It first slices the data stream into different time slices, then it visualizes each slice with a sequence of multivariate 2D data layouts, and finally it flattens this series of displays into a parallel coordinate type display. Our framework is fully interactive and lends itself well to real-time displays.
  • Keywords
    "Data visualization","Layout","Streaming media","Pollution","Correlation","Silicon","Computer science"
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology (VAST), 2015 IEEE Conference on
  • Type

    conf

  • DOI
    10.1109/VAST.2015.7347673
  • Filename
    7347673