• DocumentCode
    2391878
  • Title

    A scalable architecture for visual data exploration

  • Author

    Decker, Jonathan ; Godwin, Alex ; Livingston, Mark A. ; Royle, Denise

  • fYear
    2009
  • fDate
    12-13 Oct. 2009
  • Firstpage
    221
  • Lastpage
    222
  • Abstract
    Intelligence analysts in the areas of defense and homeland security are now faced with the difficult problem of discerning the relevant details amidst massive data stores. We propose a component-based visualization architecture that is built specifically to encourage the flexible exploration of geospatial event databases. The proposed system is designed to deploy on a variety of display layouts, from a single laptop screen to a multi-monitor tiled-display. By utilizing a combination of parallel coordinates, principal components plots, and other data views, analysts may reduce the dimensionality of a data set to its most salient features. Of particular value to our target applications are understanding correlations between data layers, both within a single view and across multiple views. Our proposed system aims to address the limited scalability associated with coordinated multiple views (CMVs) through the implementation of an efficient core application which is extensible by the end-user.
  • Keywords
    computer displays; data visualisation; graphical user interfaces; security; visual databases; component-based visualization architecture; coordinated multiple views; data layer; data set dimensionality reduction; defense security; geospatial event databases; homeland security; intelligence analysts; massive data stores; multi-monitor tiled display; parallel coordinates; principal components plots; scalable architecture; single laptop screen; visual data exploration; Data analysis; Data visualization; Displays; Information analysis; Laboratories; Principal component analysis; Risk analysis; Scalability; Terrorism; Visual analytics; Coordiated Multiple Views; Ultrascale Visualization; Visual Analytics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology, 2009. VAST 2009. IEEE Symposium on
  • Conference_Location
    Atlantic City, NJ
  • Print_ISBN
    978-1-4244-5283-5
  • Type

    conf

  • DOI
    10.1109/VAST.2009.5333451
  • Filename
    5333451