Additionally, scientific visualization for the pre-processing of data sets and the integration of massive amounts of computational results is an essential tool of the computational scientist. This multi-disciplinary activity has given rise to a new way of conducting research. Many mathematical and scientific investigations involve large-scale computer simulations, which in turn require a special class of tools for calibration, debugging and interpretation of results. Scientific visualization is currently finding increasing use in many areas of mathematics, engineering and science. Applications of visualization in these areas include data set preparation, model calibration, code debugging, code performance analysis and interpretation and presentation of results.
Visualization is especially useful for interrogating large data sets.
Scientific visualization uses computer graphics tools, but has a different aim. Traditionally, the field of computer graphics has dealt with problems surrounding the construction of an image on a computer screen and issues such as geometric projection and shading algorithms. Scientific visualization is more closely aligned with the areas of image processing, image enhancement and pattern detection. Scientific visualization uses fundamental computer graphics techniques to display a data set or the result of a computational simulation. These displays often take the form of a flat raster map, a color-coded surface, a vector field or a translucent isosurface.