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 Dimensions size: 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 X and Y are two visual dimensions to test Since x-size and y-size are perceived integrally, B and C are perceived as more similar. 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. 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