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Trees and Cushions

Trees and Cushions. Jack van Wijk Eindhoven University of Technology Treemap Workshop, May 31, 2001 HCIL, University of Maryland. InfoVis at Eindhoven. Started 1998 Focus: Trees and graphs Large data sets

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Trees and Cushions

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  1. Trees and Cushions Jack van Wijk Eindhoven University of Technology Treemap Workshop, May 31, 2001 HCIL, University of Maryland

  2. InfoVis at Eindhoven • Started 1998 • Focus: • Trees and graphs • Large data sets • Use of computer graphics knowledge (textures, geometry, shading) to generate more effective visualizations

  3. Trees (T) and Cushions (C) • T+C: Cushion treemaps (InfoVis’99) • T+C: Squarified treemaps (Vissym’00) • C: Voronoi diagrams (Vissym’01) • C: Enridged contour maps (Vis’01) • T: Botanical vis (InfoVis’01) • What next?

  4. Cushion TreemapsVisualization of Hierarchical Information Jarke J. van Wijk Huub van de Wetering Eindhoven University of Technology IEEE InfoVis’99

  5. Insight in structure of large trees • Why is my disk full? • What is our product portfolio? • How is this university organized? Fuzzy questions: Visualization needed

  6. Treemap (Shneiderman, 1992) E1 C3 G2 A16 H4 F2 B3 C3 D10 I4 E1 F2 G2 I4 H4 Alternating directions, area represents size

  7. 1400 files

  8. 3060 employees

  9. How to emphasize structure? • Color? • Linewidth? • Nesting? • Shading? Use shaded geometric model!

  10. Ridges Ridges for more insight Binary tree

  11. + = 2 z = ax + bx + cy + dy + e 2 Ridge + rotated ridge = cushion

  12. Standard treemap

  13. Cushion Treemap

  14. level H = 0.75

  15. level H = 0.50

  16. Demo www.win.tue.nl/sequoiaview May 21 2001: 45,000 downloads

  17. Squarified Treemaps Mark Bruls Kees Huizing Jarke J. van Wijk Eindhoven University of Technology Vissym’00, Amsterdam

  18. Thin rectangles (small leaves high in hierarchy e.g., .cshrc) • hard to compare sizes • hard to point at • waste of pixels • inaccurate size

  19. How to avoid thin rectangles? drop the single direction layout (emphasize structure by other means)

  20. Squarification algorithm 1. Start placing recs in one row 2. stop when aspect ratio stops getting better 3. repeat with remaining area and recs Recursive per level (just like standard treemap algorithm)

  21. 6 6 6 6 6 6 4 3 4 6 6 6 etc. 6 2 2 1 3 4 6 6 Squarification algorithm 6 4 6 6 4 3 4/1 2 aspect ratio: 8/3 3/2 2 1 2 3 4 49/27 9/2 9/4 25/9

  22. Result of squarification directory

  23. Squarified organization

  24. Shaded frames for structure

  25. Frames for structure • no maze running for the viewer • depth in structure as frame height • “remote cousins” are visibly separated by indent

  26. Organization

  27. Directory structure

  28. Visualization of Generalized Voronoi Diagrams Alex Telea, Jarke van Wijk Vissym’01, Ascona

  29. Cushions • Cushions help to understand hierarchical spatial tesselations of the plane • How about cushions to visualize Generalized Voronoi Diagrams?

  30. Generalized Voronoi diagrams N = 1 N = 2 Polygon = area where N seeds are closest

  31. Cushions and bevels

  32. Cushions, bevels, color

  33. N= 3 Cushions, bevels, color

  34. Generalized Voronoi Diagrams • Many other types (different distance measures) • Applications

  35. Enridged Contour Maps Van Wijk & Telea, Vis’01, San Diego • Given: Height field f(x,y) • Required: • Qualitative (where are the ridges) and • Quantitative (how high is this peak) info

  36. Standard visualizations

  37. Enridged height field ... height(f(x, y)) linear mapping non-linear mapping f(x, y)

  38. Height field

  39. Soft, convex ridges

  40. Strong, convex ridges

  41. Soft,concave ridges

  42. Climate (January) Color: Temperature; Height: Precipitation

  43. Climate (July) Color: Temperature; Height: Precipitation

  44. Dense contours (equid. in space)

  45. With ridges...

  46. Hierarchical ridges

  47. Back to Trees:Botanical Visualization of Huge Hierarchies Ernst Kleiberg, Huub van de Wetering, Jarke van Wijk InfoVis’01, San Diego

  48. Idea • Botanical trees are easy to understand, yet contain a lot of branches and leaves • Can we use ideas from botanical modeling for InfoVis?

  49. Strand model (Holton, 1994) • Mimics vascular system • Each leaf is connected to one strand • Branch = bundle of strands • Rules define when a branch is split First try: • Each directory is a branch • Each file is a leaf

  50. Naive result...

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