Using shape to visualize multivariate data

  • Authors:

  • Christopher D. Shaw;James A. Hall;Christine Blahut;David S. Ebert;D. Aaron Roberts

  • Affiliations:

  • Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada S4S 0A2;Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada S4S 0A2;Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada S4S 0A2;Computer Science and Electrical Engineering Department, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD;NASA Goddard Space Flight Center, Mailstop 692.0, Greenbelt, MD

  • Venue:
  • 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
  • Year:
  • 1999

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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