1. 1 Commentary Trouble rather the tiger in his lair than the sage amongst his books, For to you Kingdoms and their armies are things mighty and enduring, To him they are but toys of the moment, to be overturned by the flicking of a finger. Attributed to “Anonymous,” in Tactics of Mistake, Gordon Dickson

2. Introduction to Information Visualization for HCI Shaun P. Morrissey 10 March 2007

3. 3 Shaun P. Morrissey n B.S. Physics, Rensselaer Polytechnic Inst. n M.S., Experimental Particle Physics, Carnegie-Mellon Univ. n M.S., Computer Science, UMass/Lowell n D.Sc. Student, UML, –Visualization Applied to Firewall Security –Prof. Georges Grinstein, IVPR n Emergency Medical Technician (MA, NH, NREMT) –Deputy Chief, Amherst EMS, Amherst, NH n Technical Systems Analyst –Vulnerability –Information Warfare –Air Command & Control –Acquisition Planning

4. 4 Outline n Why? n Visualization –Data Attributes –Scientific vs Information n Perception –Eye structure –Luminance/Brightness - contrast illusions –Color –Change-Blindness –Pre-attentive processing n Dimensionality –1, 2, 3-D and projections –Lossless representations n Examples

5. 5 Randu Example n Jump to Data Desk file –Show visual impact of weaknesses in early IBM 360 linear congruential pseudo-random number generator n Successive triplets of calls are strongly correlated –Point out that verbal description doesn’t mean much, but even your manager will understand [picture]

6. 6 Visualization Issues n Type –Scientific –Information n Data/Attribute Characteristics –Nominal/Categorical –Ordinal –Interval –Ratio/Affine Tam, R. C., Healey, C. G., Flak, B., and Cahoon, P. "Volume Rendering of Abdominal Aortic Aneurysms." In Proceedings IEEE Visualization '97 (Phoenix, Arizona, 1997), pp. 43-50

7. 7 Perception: Eye Structure n Lens focuses light on macula lutea and fovea centralis –Macula lutea: small yellow spot –Fovea centralis: area of greatest visual acuity; photoreceptor cells tightly packed n Optic disc: blind spot. Area through which blood vessels enter eye, where nerve processes from sensory retina meet and exit from eye n 100k cones inside 2 degrees (100 points on head of a pin) n At 10 degrees, down by 100 in density n At edge of field, fist sized objects n Saccadic motion

8. 8 Rods/Cones

9. 9 Perception: Luminance/Brightness & Contrast Illusions

10. 10 Perception: Color in Light Why can an RGB monitor show us Yellow? Na-light 589 nm

11. 11 Rods/Cones n Bipolar receptor cells. n Responsible for color vision and visual acuity. –Numerous in fovea and macula lutea; fewer over rest of retina. –As light intensity decreases so does our ability to see color. –Visual pigment is iodopsin: three types that respond to blue, red and green light –Overlap in response to light, thus interpretations of gradation of color possible: several millions Cones

12. 12 Three Channels L M S L+M+S = Brightness L - M = Red-Green (L+M) - S = Yellow-Blue

13. 13 Color components per frequency Healey, C. G. "Effective Visualization of Large, Multidimensional Datasets." PhD Thesis (1996), Department of Computer Science, University of British Columbia.

14. 14 Brown is what?

15. 15 n Berlin & Kay, 1981 studied 100 languages n Post & Greene, 1986, consistent color naming n Suggests color coding only good for about six-eight categories Colors and Coding Red*, Pink, Purple, Blue, Aqua, Green**, Yellow, Orange, White *Perceptual red was not pure, required some blue ** Two pure greens (514 nm (2/3) and 525 nm (1/3) ) White Black Red Green, Yellow Yellow, Green BlueBrown Pink Purple Orange Gray

16. 16 Change Blindness n Airplane n Dinner n Tourists Samples mentioned above found at: http://www.csc.ncsu.edu/faculty/healey/PP/index.html

17. 17 Pre-attentive Processing http://www.csc.ncsu.edu/faculty/healey/PP/index.html

18. 18 Pre-Attentive Processing (images) http://www.intelligententerprise.com/showArticle.jhtml;jsessionid=1ZE ZHJBWGTV0OQSNDLPCKHSCJUNN2JVN?articleID=31400009&pg no=2

19. 19 Pre-attentive images

20. 20 Visual Currying

21. 21 Pre-Computer Use of Preattentive Processing n Titan Missile Status Panel n Hatch Dive Status

22. 22 Dials galore

23. 23 Dials galore

24. 24

25. 25 Visualizations n Networks –http://www.visualcomplexity.com/vc/http://www.visualcomplexity.com/vc/ –561 network visualizations n Vizit n Text Visualization –http://www.neoformix.com/2007/ATextExplorer.htmlhttp://www.neoformix.com/2007/ATextExplorer.html –http://www.marumushi.com/apps/newsmap/index.cfmhttp://www.marumushi.com/apps/newsmap/index.cfm n Monte Carlo techniques and Scatterplot Matrix

26. 26 TreeMaps: Space Filling

27. 27 Space Filling with fixed partitioning: Quadtree with zooming [Teoh 2002] Figure 2: Data from January 2, 2000 to March 3, 2000. Colored pixels in main window show involved prefixes resolved to first 18 bits. Zoom windows resolve prefixes completely.

28. 28 Quadtree detail Figure 25. [Teoh 2002] Figure 1: Quadtree coding of IP prefixes. Left: Top levels of the tree, and the most significant bits of the IP prefixes represented by each sub-tree (sub-square). 4 lines representing AS numbers surround the square representing the IP prefix space. Right: Actual data. A line is drawn for every IP- AS pair in an OASC.

29. 29 Themescape

30. 30 3D Scatter: Projection Loss Multidimensional Visualization Technique Viewer http://filer.case.edu/~dbh10/eecs466/report.html

31. 31 Worlds within Worlds http://www1.cs.columbia.edu/graphics/projects/AutoVisual/A utoVisual.html#figure_optcompare

32. 32 Lossless Representations: Parallel Coordinates Multidimensional Visualization Technique Viewer http://filer.case.edu/~dbh10/eecs466/report.html Google: Parallel Axes Inselberg

33. 33 Chernoff Faces

34. 34 Stars (variant on glyphs)

35. 35 Piles/Columns of Glyphs

36. 36 Focus + Context: Distortion Leung, Y. K. and Apperley, M. D. 1994. A review and taxonomy of distortion-oriented presentation techniques. ACM Trans. Comput.-Hum. Interact. 1, 2 (Jun. 1994), 126-160. DOI= http://doi.acm.org/10.1145/180171.180173

37. 37 Example: The Perspective Wall

38. 38 Example: Fisheye Magnification Functions

39. 39 Example: Fisheye view transformations

40. 40 Research Agenda: Visual Analytics Document: http://nvac.pnl.gov/docs/RD_Agenda _VisualAnalytics.pdf Website: http://nvac.pnl.gov/agenda.stm