Framework of a Visualization System

Reference Chapter 2, [Brod92]

Introduction

Definition:

Outside of computer graphics, two standard defintions of visualization are as follows:

• making visible, especially to one's mind (thing not visible to the eye) [OED69]
• forming a mental image of something (thing not present to the sight, an abstraction, etc.) [WEB70]

Within computer graphics the term scientific visualization is defined more specifically, e.g., as follows:

• the use of computer imaging technology as a tool for comprehending data obtained by simulation or physical measurement [Haber90]
• techniques that allow scientists and engineers to extract knowledge from the results of simulations and computations [Niel90]

To produce a framework for visualization systems, the definition and scope must be described. Then the framework is developed in terms of a sequence of models.

Scope

To fully describe the process of scientific visualization as being one that provides insight, the complete cycle of acessing, processing, and display of data needs to be addressed.

High Level Models

Creative Thinking

There are four stages in creative thinking: Preparation, Incubation, Illumination, and Verification. Data Visualization systems assist in Preparation (using a Data Visualization system for data "brain storming") and Verification (using a Data Visualization system to verify a tentative hypothesis about the data).

Scientific Investigation

The following model of scientific investigation has been proposed:

The investigator uses insight to formulate a hypothesis, collect data, build a model, compute a simulation, view and interpret the data, and iterate.

Model of Visualization

Other Considerations

• Data accuracy and errors: The system must be able to handle data accuracy and errors. Some of these may be artifacts of the experimental data and some may be artifacts of the visualization process. It is extremely important to guard against errors introduced by the visualization system.
• Annotation: The system must allow the users to annotate the images and animations.
• Distributed Architecture: The visualization system may be part of a distributed system, e.g., a workstation on a network with other workstations and/or supercomputers. Some of the system modules may execute on other machines.
• Responsiveness: The response time of the system must be such as to prevent user impatience and disgust. For complex data sets and images certain tradeoffs may have to be made with current technology. For example, a crudely shaded image might be show quickly and then later the user can request a high quality image.
• Human-Computer Interface: These involve cognitive and perceptual issues.

HyperVis Table of Contents