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when quoting this document, please refer to the following
URN: urn:nbn:de:0030-drops-14132
URL: http://drops.dagstuhl.de/opus/volltexte/2008/1413/

Ebert, David S. ; Hagen, Hans ; Joy, Kenneth I. ; Keim, Daniel A.

07291 Summary -- Scientific Visualization

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Abstract

Scientific visualization (SV) is concerned with the use of computer-generated images to aid the understanding, analysis and manipulation of data. Since its beginning in the early 90's, the techniques of SV have aided scientists, engineers, medical practitioners, and others in the study of a wide variety of data sets including, for example, high performance computing simulations, measured data from scanners (CAT, MR, confocal microscopy), internet traffic, and financial records. One of the important themes being nurtured under the aegis of Scientific Visualization is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes and simulations involving voluminous data sets across diverse scientific disciplines. Since vision dominates our sensory input, strong efforts have been made to bring the mathematical abstraction and modeling to our eyes through the mediation of computer graphics. This interplay between various application areas and their specific problem solving visualization techniques was emphasized in the proposed seminar.

BibTeX - Entry

@InProceedings{ebert_et_al:DSP:2008:1413,
  author =	{David S. Ebert and Hans Hagen and Kenneth I. Joy and Daniel A. Keim},
  title =	{07291 Summary -- Scientific Visualization},
  booktitle =	{Scientific Visualization},
  year =	{2008},
  editor =	{David S. Ebert and Hans Hagen and Kenneth I. Joy and Daniel A. Keim},
  number =	{07291},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Internationales Begegnungs- und Forschungszentrum f{\"u}r Informatik (IBFI), Schloss Dagstuhl, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2008/1413},
  annote =	{Keywords: Markov chains, numerical methods, web information retrieval, performance evaluation, intrusion detection, aggregation-disaggregation methods}
}

Keywords: Markov chains, numerical methods, web information retrieval, performance evaluation, intrusion detection, aggregation-disaggregation methods
Freie Schlagwörter (deutsch): graph-oriented decomposition
Seminar: 07291 - Scientific Visualization
Issue date: 2008
Date of publication: 10.04.2008


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