• DocumentCode
    2017709
  • Title

    EnVision: A Web-Based Tool for Scientific Visualization

  • Author

    Johnson, Gregory P. ; Mock, Stephen A. ; Westing, Brandt M. ; Johnson, Gregory S.

  • Author_Institution
    Univ. of Texas at Austin, Austin, TX
  • fYear
    2009
  • fDate
    18-21 May 2009
  • Firstpage
    603
  • Lastpage
    608
  • Abstract
    Scientific visualization is the process of transforming raw numeric data into a visual form, and is a key element of computational science. While many tools exist, they are unnecessarily difficult to use. This complexity increases time to insight and inhibits casual inquiry. The complexity derives from the need to support arbitrarily formatted data and many visualization algorithms. EnVision addresses both sources of complexity. Its design is predicated on two key insights. First, though the number of data file formats is unbounded, the structure of any one can be described using a small number of parameters. Second, the set of visualization algorithms applicable to a given type of data is small, and the subset used within a specific scientific discipline is smaller. EnVision utilizes domain-specific knowledge and user-directed semi-automation to dramatically simplify data importation and visualization algorithm selection. Its Web-based interface facilitates access to remote hardware resources and provides a collaborative visualization environment.
  • Keywords
    Internet; computational complexity; data visualisation; software tools; user interfaces; EnVision; Web-based interface; Web-based tool; collaborative visualization environment; computational complexity; computational science; data file format; domain-specific knowledge; scientific visualization; user-directed semi-automation; Collaboration; Data analysis; Data visualization; Grid computing; Hardware;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster Computing and the Grid, 2009. CCGRID '09. 9th IEEE/ACM International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3935-5
  • Electronic_ISBN
    978-0-7695-3622-4
  • Type

    conf

  • DOI
    10.1109/CCGRID.2009.80
  • Filename
    5071929