• DocumentCode
    2218654
  • Title

    Sunfall: A Collaborative Visual Analytics System for Astrophysics

  • Author

    Aragon, Cecilia R. ; Bailey, Stephen J. ; Poon, Sarah ; Runge, Karl J. ; Thomas, Rollin C.

  • Author_Institution
    Lawrence Berkeley Nat. Lab., Berkeley
  • fYear
    2007
  • fDate
    Oct. 30 2007-Nov. 1 2007
  • Firstpage
    219
  • Lastpage
    220
  • Abstract
    Computational and experimental sciences produce and collect ever- larger and complex datasets, often in large-scale, multi-institution projects. The inability to gain insight into complex scientific phenomena using current software tools is a bottleneck facing virtually all endeavors of science. In this paper, we introduce Sunfall, a collaborative visual analytics system developed for the Nearby Supernova Factory, an international astrophysics experiment and the largest data volume supernova search currently in operation. Sunfall utilizes novel interactive visualization and analysis techniques to facilitate deeper scientific insight into complex, noisy, high-dimensional, high-volume, time-critical data. The system combines novel image processing algorithms, statistical analysis, and machine learning with highly interactive visual interfaces to enable collaborative, user-driven scientific exploration of supernova image and spectral data. Sunfall is currently in operation at the Nearby Supernova Factory; it is the first visual analytics system in production use at a major astrophysics project.
  • Keywords
    astronomical image processing; data analysis; data visualisation; graphical user interfaces; learning (artificial intelligence); statistical analysis; Nearby Supernova Factory; Sunfall; astrophysics; collaborative visual analytics system; data analysis; image processing algorithms; interactive data visualization; machine learning; software tools; spectral data; statistical analysis; user-driven scientific exploration; visual interfaces; Astrophysics; Data visualization; Image processing; International collaboration; Large-scale systems; Machine learning algorithms; Production facilities; Software tools; Time factors; Visual analytics; Data and knowledge visualization; astrophysics; scientific visualization; visual analytics; visual exploration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology, 2007. VAST 2007. IEEE Symposium on
  • Conference_Location
    Sacramento, CA
  • Print_ISBN
    978-1-4244-1659-2
  • Type

    conf

  • DOI
    10.1109/VAST.2007.4389026
  • Filename
    4389026