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  1. Proceedings of the 1999 workshop on new paradigms in information visualization and manipulation in conjunction with the eighth ACM internation conference on Information and knowledge management (NPIVM '99)
  2. Using shape to visualize multivariate data
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Information visualization using a new focus+context technique in combination with dynamic clustering of information space
Visualization of high-dimensional model characteristics
Dimensional anchors: a graphic primitive for multidimensional multivariate information visualizations
Using shape to visualize multivariate data
Human-guided simple search: combining information visualization and heuristic search
Temporal, geographical and categorical aggregations viewed through coordinated displays: a case study with highway incident data
Virtual environments for geographic visualization: potential and challenges
Audio-visual data mapping for GIS-based data: an experimental evaluation
Hypercept: behavioural linkage in hypertext environments
Navigation in huge information hierarchies application to network management
Conceptualizing bandwidth allocation in network management
Almost: exploring program traces
Interactive video cubism
Exploration of large image collections using virtual reality devices
Application redirection: hosting Windows applications in 3D
3DIVS: 3-dimensional immersive virtual sculpting

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Article

Using shape to visualize multivariate data

Content Provider ACM Digital Library
Author Roberts, D. Aaron Shaw, Christopher D. Blahut, Christine Ebert, David S. Hall, James A.
Abstract This paper describes our recent findings in the area of using glyph shape to display one or two data dimensions in the visualization of 3D scalar and vector fields In our glyph-based visualization system, each glyph represents a data point in 3D space Visual attributes such as size, orientation, color and transparency can be mapped to data dimensions in the 3D space We are exploring the use of glyph shape as a display dimension, using superquadric superellipses as a means of supplying a parameterizable shape A basic factor in effectively using shape for quantitative visualization is determining how many (and which) superellipse shapes people can distinguish Since the superquadric shape's parameter set is not perceptually linear, we conducted a user study to which shapes people can generally distinguish The findings show that with large superellipses, about 22 separate shapes can be distinguished on average These results provide the foundation for exploring how effective superellipses may be in quantitative shape visualization.
Starting Page 17
Ending Page 20
Page Count 4
File Format PDF
ISBN 1581132549
DOI 10.1145/331770.331777
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 1999-11-01
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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