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Burkhard Wünsche University of Auckland, Auckland, New Zealand

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2004 Article

Published in: · Proceeding APVis '04 Proceedings of the 2004 Australasian symposium on Information Visualisation Volume 35 Pages 17-24 Christchurch, New Zealand

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Australian Computer Society, Inc. Darlinghurst, Australia, Australia ©2004 table of contents ISBN:1-920682-17-1

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Table of Contents

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.

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