Skip to main content
eScholarship
Open Access Publications from the University of California

Coupling visualization and data analysis for knowledge discovery from multi-dimensional scientific data

  • Author(s): Rübel, Oliver
  • Ahern, Sean
  • Bethel, E. Wes
  • Biggin, Mark D.
  • Childs, Hank
  • Cormier-Michel, Estelle
  • DePace, Angela
  • Eisen, Michael B.
  • Fowlkes, Charless C.
  • Geddes, Cameron R.
  • Hagen, Hans
  • Hamann, Bernd
  • Huang, Min-Yu
  • Keränen, Soile E.
  • Knowles, David W.
  • Hendriks, Cris Luengo
  • Malik, Jitendra
  • Meredith, Jeremy
  • Messmer, Peter
  • Prabhat, -
  • Ushizima, Daniela
  • Weber, Gunther H.
  • Wu, Kesheng
  • et al.
Abstract

Knowledge discovery from large and complex scientific data is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the growing number of data dimensions and data objects presents tremendous challenges for effective data analysis and data exploration methods and tools. The combination and close integration of methods from scientific visualization, information visualization, automated data analysis, and other enabling technologies —such as efficient data management— supports knowledge discovery from multi-dimensional scientific data. This paper surveys two distinct applications in developmental biology and accelerator physics, illustrating the effectiveness of the described approach.

Many UC-authored scholarly publications are freely available on this site because of the UC Academic Senate's Open Access Policy. Let us know how this access is important for you.

Main Content
Current View