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

2. InfoVis at Eindhoven l Started 1998 l 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) l T+C: Cushion treemaps (InfoVis’99) l T+C: Squarified treemaps (Vissym’00) l C: Voronoi diagrams (Vissym’01) l C: Enridged contour maps (Vis’01) l T: Botanical vis (InfoVis’01) l What next?

4. Cushion Treemaps Visualization 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 l Why is my disk full? l What is our product portfolio? l How is this university organized? Fuzzy questions: Visualization needed

6. Treemap (Shneiderman, 1992) A16 B3C3D10 E1F2G2H4I4 E1 F2 C3 H4 I4 G2 Alternating directions, area represents size

7. 1400 files

8. 3060 employees

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

10. Ridges for more insight Binary tree Ridges

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

12. Standard treemap

13. Cushion Treemap

14. H = 0.75 level

15. H = 0.50 level

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

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

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 Squarification algorithm 6 6 aspect ratio: 8/33/2 4/1 6 6 4 9/4 4 9/2 6 6 43 49/27 6 6 4 3 2 etc. 6 6 4 3 2 2 1 6 6 4 3 2 2 1 25/9

22. Result of squarification directory

23. Squarified organization

24. Shaded frames for structure

25. Frames for structure l no maze running for the viewer l depth in structure as frame height l “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 l Cushions help to understand hierarchical spatial tesselations of the plane l How about cushions to visualize Generalized Voronoi Diagrams?

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

31. Cushions and bevels

32. Cushions, bevels, color

33. N= 3 Cushions, bevels, color

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

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

36. Standard visualizations

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

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

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

50. Naive result...

51. Three problems l Continuing branches are hard to see l Long, thin branches emerge l Leaves are messy

52. Smoothed continuing branches

53. Contract long branches

54. Files: Phi-balls (Lintermann,99) One big file Many small files

59. Botanical modeling l Compact, natural visualization l Phyllotaxis = magic! l Many treasures to be discovered l Usability? l Botanical treemaps?

60. My treemap to-do list l Non-rectangular shapes/subdivisions circles, polygons? l Multivariate data color, texture? l Applications genealogy, data mining? l Evaluation