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Commentary

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

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Commentary

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  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 toInformation Visualization for HCI Shaun P. Morrissey 10 March 2007

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

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

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

  6. Visualization Issues • Type • Scientific • Information • 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. Perception: Eye Structure • 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 • Optic disc: blind spot. Area through which blood vessels enter eye, where nerve processes from sensory retina meet and exit from eye • 100k cones inside 2 degrees (100 points on head of a pin) • At 10 degrees, down by 100 in density • At edge of field, fist sized objects • Saccadic motion

  8. Rods/Cones

  9. Perception: Luminance/Brightness &Contrast Illusions

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

  11. Bipolar receptor cells. 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 Rods/Cones Cones

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

  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. Brown is what?

  15. Colors and Coding • Berlin & Kay, 1981 studied 100 languages • Post & Greene, 1986, consistent color naming • Suggests color coding only good for about six-eight categories Pink Purple Orange Gray White Black Green, Yellow Yellow, Green Red Blue Brown 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) )

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

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

  18. Pre-Attentive Processing (images) http://www.intelligententerprise.com/showArticle.jhtml;jsessionid=1ZEZHJBWGTV0OQSNDLPCKHSCJUNN2JVN?articleID=31400009&pgno=2

  19. Pre-attentive images

  20. Visual Currying

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

  22. Dials galore

  23. Dials galore

  24. And NOW, The SHOW!

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

  26. TreeMaps:Space Filling

  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. 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. Themescape

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

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

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

  33. Chernoff Faces

  34. Stars (variant on glyphs)

  35. Piles/Columns of Glyphs

  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. Example: The Perspective Wall

  38. Example: Fisheye Magnification Functions

  39. Example: Fisheye view transformations

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

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