Topic 214

Visualization: mapping by Simon

Scientific visualization, sometimes referred to in shorthand as SciVis, is the representation of data graphically as a means of gaining understanding and insight into the data. It is sometimes referred to as visual data analysis. This allows the researcher to gain insight into the system that is studied in ways previously impossible.

It is important to differentiate between scientific visualization and presentation graphics. Presentation graphics is primarily concerned with the communication of information and results in ways that are easily understood. In scientific visualization, we seek to understand the data. However, often the two methods are intertwined.

From a computing perspective, SciVis is part of a greater field called visualization. This involves research in computer graphics, image processing, high performance computing, and other areas. The same tools that are used for SciVis may be applied to animation, or multimedia presentation, for example.

As a science, scientific visualization is the study concerned with the interactive display and analysis of data. Often one would like the ability to do real-time visualization of data from any source. Thus our purview is information, scientific, or engineering visualization and closely related problems such as computational steering or multivariate analysis. The approaches developed are general, and the goal is to make them applicable to datasets of any size whatever while still retaining high interactivity. As an emerging science, its strategy is to develop fundamental ideas leading to general tools for real applications. This pursuit is multidisciplinary (concerning morals of other users) in that it uses the same techniques across many areas of study.

Visualization, in the presentation sense, is not a new phenomenon. It has been used in maps, scientific drawings, and data plots for over a thousand years. Mapping is a form of visualization.

The main reasons for scientific visualization(mapping) are the following: it will compress a lot of data into one picture (data browsing), it can reveal correlations between different quantities both in space and time, it can furnish new space-like structures beside the ones which are already known from previous calculations, and it opens up the possibility to view the data selectively and interactively in `real time'.

By following the formation and the deformation as well as the motions of these structures in time, one will gain insight into the complicated dynamics. As was mentioned before, you also want to integrate our simulation codes into a visualization environment in order to analyze the data 'real time' and to by-pass the need to store every intermediate result for later analysis.

This is possible by means of processing in which the simulation is distributed over a set of high-performance computers and the actual visualization is done on a graphical distributive workstation. It is also very useful to have the possibility to interactively change the simulation parameters and immediately see the effect of this change through the new data. This process is called computational steering and it will increase the effective use of CPU time.

Classification of visualization techniques is often based on the dimension of the domain of the quantity that is visualized, i.e. the number of independent variables of the domain on which the quantity acts, and on the type of the quantity, i.e. scalar, vector, or tensor .

The rise of the "Information Age" and the ascendancy of Computer Graphics come together in the area of information visualization, where interactive graphical interfaces are used for revealing structure, extracting meaning, and navigating large and complex information worlds.

Increasing amounts of data and information and the availability of fast digital network access (e.g., in the information highway environment) have created a demand for querying, accessing, and retrieving information and data. However, information technology will not transform business, science, medicine, engineering, and education if the users cannot use it easily and efficiently. Technology must come to the users, taking their needs into account. If we do not involve the users, we will develop useless systems. One of the concerns of this field is the human-information interface, and how advances in interactive computer graphics hardware, mass storage, and data visualization could be used to visualize information.

The success of visualization not only depends on the results which it produces, but also depends on the environment in which it has to be done. This environment is determined by the available hardware, like graphical workstations, disk space, color printers, video editing hardware, and network bandwidth, and by the visualization software. For example, the graphical hardware imposes constraints on interactive speed of visualization and on the size of the data sets which can be handled.

Many different problems encountered with visualization software must be taken into account. The user interface, programming model, data input, data output, data manipulation facilities, and other related items are all important. The way in which these items are implemented determines the convenience and effectiveness of the use of the software package as seen by the scientist. Furthermore, whether software supports distributive processing and computational steering must be taken into account.