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Identifying Integral-Separable Dimension Pairs

Identifying Integral-Separable Dimension Pairs. Zaixian Xie Mar 15, 2006. What are them?. Are BC more similar?. Are AB more similar?. What are them?. Integral display dimensions: Two or more attributes of a visual objects are perceived not independently. (e.g. x-size and y-size)

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Identifying Integral-Separable Dimension Pairs

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  1. Identifying Integral-Separable Dimension Pairs Zaixian Xie Mar 15, 2006

  2. What are them? Are BC more similar? Are AB more similar?

  3. What are them? • Integral display dimensions: Two or more attributes of a visual objects are perceived not independently. (e.g. x-size and y-size) • Separable display dimensions: People tend to make separable judgments about each graphical attribute. (size and gray scale)

  4. How to use them a. Integral Dimensions: x-size: price; y-size: score b. Separable Dimensionssize: price; gray-scale: score Task: Please search cars with low price and high score! Which figure makes it easier? Conclusion: Separable dimensions are more suitable for describing independent multiple data attributes on glyphs to visualize multivariate data.

  5. Experiment Design Since x-size and y-size are perceived integrally, B and C are perceived as more similar. X and Y are two visual dimensions to test Since y-size and gray-scale are perceived independently, A and B are perceived as more similar because of the same y-size.

  6. Experiment Design • Dimensions to Test • x-size • y-size • color • gray scale • orientation • shape (circle, square)

  7. Experiment Design • Dimension Pairs to Test • color vs. shape • orientation vs. color • orientation vs. gray scale • x-size vs. color • x-size vs. gray scale • x-size vs. orientation • x-size vs. shape (circle, square) • y-size vs. x-size

  8. Experiment Design • 23 Participants • 14 graduate students • 15 beginners on visualization

  9. Experiment Result

  10. Experiment Result • Analysis on the number of questions on which each user answer ‘a’ (separable dimensions) • average: 4.44 • variance: 2.53

  11. Conclusion • We should map more separable dimensions to multiple data attributes of glyphs • A continuum of integral-separable is more accurate to present the fact. • Difference exists among subjects.

  12. Improvement on Experiment • More strict environment to control display time. • Exchange the two dimensions of the pairs. • Looking for the relationship between culture, gender and experiment result.

  13. Questions or Comments

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