scientific visualization

caused by two mixing fluids. pollen grains with confocal microscope. Scientific visualization (also spelled scientific visualisation) is an interdisciplinary branch of science concerned with the visualization of scientific phenomena. It is also considered a subset of computer graphics, a branch of computer science. The purpose of scientific visualization is to graphically illustrate scientific data to enable scientists to understand, illustrate, and glean insight from their data. Research into how people read and misread various types of visualizations is helping to determine what types and features of visualizations are most understandable and effective in conveying information.

caused by two mixing fluids. pollen grains with confocal microscope. Scientific visualization (also spelled scientific visualisation) is an interdisciplinary branch of science concerned with the visualization of scientific phenomena. It is also considered a subset of computer graphics, a branch of computer science. The purpose of scientific visualization is to graphically illustrate scientific data to enable scientists to understand, illustrate, and glean insight from their data. Research into how people read and misread various types of visualizations is helping to determine what types and features of visualizations are most understandable and effective in conveying information. ==History== of Napoleon's March. One of the earliest examples of three-dimensional scientific visualisation was Maxwell's thermodynamic surface, sculpted in clay in 1874 by James Clerk Maxwell. This prefigured modern scientific visualization techniques that use computer graphics. Notable early two-dimensional examples include the flow map of Napoleon's March on Moscow produced by Charles Joseph Minard in 1869; the "coxcombs" used by Florence Nightingale in 1857 as part of a campaign to improve sanitary conditions in the British Army; and the dot map used by John Snow in 1855 to visualise the Broad Street cholera outbreak. == Data visualization methods== Criteria for classifications: dimension of the data method textura based methods geometry-based approaches such as arrow plots, streamlines, pathlines, timelines, streaklines, particle tracing, surface particles, stream arrows, stream tubes, stream balls, flow volumes and topological analysis ===Computer simulation=== Computer simulation is a computer program, or network of computers, that attempts to simulate an abstract model of a particular system. Computer simulations have become a useful part of mathematical modelling of many natural systems in physics, and computational physics, chemistry and biology; human systems in economics, psychology, and social science; and in the process of engineering and new technology, to gain insight into the operation of those systems, or to observe their behavior. The simultaneous visualization and simulation of a system is called visulation. Computer simulations vary from computer programs that run a few minutes, to network-based groups of computers running for hours, to ongoing simulations that run for months. The scale of events being simulated by computer simulations has far exceeded anything possible (or perhaps even imaginable) using the traditional paper-and-pencil mathematical modeling: over 10 years ago, a desert-battle simulation, of one force invading another, involved the modeling of 66,239 tanks, trucks and other vehicles on simulated terrain around Kuwait, using multiple supercomputers in the DoD High Performance Computing Modernization Program. ===Interface technology and perception=== Interface technology and perception shows how new interfaces and a better understanding of underlying perceptual issues create new opportunities for the scientific visualization community. Gregory M. Nielson, Hans Hagen and Heinrich Müller (1997). Scientific Visualization: Overviews, Methodologies, and Techniques. IEEE Computer Society. Clifford A. Pickover (ed.) (1994). Frontiers of Scientific Visualization. New York: John Wiley Inc. Lawrence J. Rosenblum (ed.) (1994). Scientific Visualization: Advances and challenges. Academic Press. Will Schroeder, Ken Martin, Bill Lorensen (2003). The Visualization Toolkit. Kitware, Inc. Leland Wilkinson (2005). The Grammar of Graphics, Springer.

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