A Survey, Classification and Analysis of Perceptual Concepts and their Application for the Effective Visualisation of Complex In

Information visualisation has become increasingly important in science, engineering and commerce as a tool to convey and explore complex sets of information. This paper introduces a visualisation schema which uses visual attributes as the principle components of a visualisation. We present a new classification of visual attributes according to information accuracy, information dimension and spatial requirements and obtain values for the information content and information density of each attribute. The classification applies only to the perception of quantitative information and initial results of experiments suggest that it can not be extended to other visual processing tasks such as preattentive target detection. The classification in combination with additional guidelines given in this paper provide the reader with a useful tool for creating visualisations which convey complex sets of information more effectively.

• Type: Conference
• Year: 2004
• Where: APVIS
• Authors: Burkhard Wünsche
• Keywords: APVIS 2004, APVIS 2007, Complex Sets, Information Visualisation, Visual Attributes