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

نویسندگان

  • Oliver Rübel
  • Sean Ahern
  • E. Wes Bethel
  • Mark D. Biggin
  • Hank Childs
  • Estelle Cormier-Michel
  • Angela H. DePace
  • Michael B. Eisen
  • Charless C. Fowlkes
  • Cameron G. R. Geddes
  • Hans Hagen
  • Bernd Hamann
  • Min-Yu Huang
  • Soile V. E. Keränen
  • David W. Knowles
  • Cris L. Luengo Hendriks
  • Jitendra Malik
  • Jeremy S. Meredith
  • Peter Messmer
  • Prabhat
چکیده

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.

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عنوان ژورنال:
  • Procedia computer science

دوره 1 1  شماره 

صفحات  -

تاریخ انتشار 2010