1. From Hierarchies to Polyarchies: Visualizing Multiple Relationships George G. Robertson Microsoft Research George G. Robertson Microsoft Research

2. GVU 11/2000 2 What is the problem?  Hierarchies are very common  20 years of hierarchy visualization R&D  Significant problems remain  New problems appearing (Multiple Hierarchies)  Hierarchies are very common  20 years of hierarchy visualization R&D  Significant problems remain  New problems appearing (Multiple Hierarchies)

3. GVU 11/2000 3 Current Approaches Many 2D and 3D hierarchy visualizations  Each works for some tasks and some scales  Very few have had user testing Windows Tree Control  Many observed problems Many 2D and 3D hierarchy visualizations  Each works for some tasks and some scales  Very few have had user testing Windows Tree Control  Many observed problems

4. GVU 11/2000 4 What’s wrong with this picture?

5. GVU 11/2000 5 Problems: Fitting Data  Extreme aspect ratio (broad and shallow)  May be multiple hierarchies  Scaling issues  Extreme aspect ratio (broad and shallow)  May be multiple hierarchies  Scaling issues

6. GVU 11/2000 6 Problems: Cognitive Overhead  Loss of context  Or loss of detail  Separate detail/overview  extra overhead  Multiple focus is difficult  Which item is open?  Loss of context  Or loss of detail  Separate detail/overview  extra overhead  Multiple focus is difficult  Which item is open?

7. GVU 11/2000 7 Basic View Strategies Two view (separate detail/overview views) Distorted view  Distorted data: fisheye  Distorted space: 3D, hyperbolic Focus in Context (integrated view) Two view (separate detail/overview views) Distorted view  Distorted data: fisheye  Distorted space: 3D, hyperbolic Focus in Context (integrated view)

8. GVU 11/2000 8 Basic Visualization Approaches Indentation  Tree control  Fisheye Containment  Treemaps  Pad++ Indentation  Tree control  Fisheye Containment  Treemaps  Pad++ Clustering  Galaxy of News  ThemeScape  Hot Sauce Geographic  Floor plans  Street maps Clustering  Galaxy of News  ThemeScape  Hot Sauce Geographic  Floor plans  Street maps Node-link diagrams  2D diagrams  SemNet  Cone Tree  Fisheye Cone Tree  Hyperbolic viewer  FSN  XML3D Node-link diagrams  2D diagrams  SemNet  Cone Tree  Fisheye Cone Tree  Hyperbolic viewer  FSN  XML3D

9. GVU 11/2000 9 Smalltalk File Browser - 1979  Xerox PARC 1979

10. GVU 11/2000 10 Fisheye Views – 1986  Furnas, Bell Labs report 1981, CHI’86

11. GVU 11/2000 11 SemNet - 1986  Fairchild, Poltrock, & Furnas, MCC  Semantic network 3D visualization  Fairchild, Poltrock, & Furnas, MCC  Semantic network 3D visualization

12. GVU 11/2000 12 Cone Tree - 1991  Robertson, Mackinlay & Card, Xerox PARC, CHI’91  Limits:  10 levels  1000 nodes  Up to 10,000  Robertson, Mackinlay & Card, Xerox PARC, CHI’91  Limits:  10 levels  1000 nodes  Up to 10,000

13. GVU 11/2000 13 Cone Tree – 10,000 nodes  Performance problems and Visual clutter

14. GVU 11/2000 14 Fisheye Cone Tree  Adding Fisheye solves problems

15. GVU 11/2000 15 TreeMap - 1991  Johnson & Shneiderman, U. Maryland, Vis’91  Space filling  ~3000 objects  MicroLogic’s DiskMapper  Johnson & Shneiderman, U. Maryland, Vis’91  Space filling  ~3000 objects  MicroLogic’s DiskMapper

16. GVU 11/2000 16 FSN - 1992  Tesler, SGI, 1992  2D layout on 3D surface  Loss of context when examining detail  Hyper-G (Graz; Andrews; InfoVis’95)  Tesler, SGI, 1992  2D layout on 3D surface  Loss of context when examining detail  Hyper-G (Graz; Andrews; InfoVis’95)

17. GVU 11/2000 17 Graphical Fisheye - 1992  Sarkar & Brown, DEC SRC, CHI’92

18. GVU 11/2000 18 Rubber Sheet - 1993  Sarkar & Snibbe, Brown, UIST’93

19. GVU 11/2000 19 Spiral Visualization - 1994  Mackinlay, Robertson, & DeLine, Xerox PARC, UIST’94  Large DAGs  Only shows current path  Mackinlay, Robertson, & DeLine, Xerox PARC, UIST’94  Large DAGs  Only shows current path

20. GVU 11/2000 20 Hyperbolic Browser - 1994  Lamping & Rao, Xerox PARC, UIST’94  Projected onto circle  1000’s of nodes  Lamping & Rao, Xerox PARC, UIST’94  Projected onto circle  1000’s of nodes

21. GVU 11/2000 21 Continuous Zoom - 1995  Bartram et al, Simon Fraser, UIST’95)

22. GVU 11/2000 22 Fsviz - 1995  Carriere and Kazman, Waterloo, InfoVis’95  Up to 5000 nodes with no occlusion  Carriere and Kazman, Waterloo, InfoVis’95  Up to 5000 nodes with no occlusion

23. GVU 11/2000 23 Butterfly - 1995  Mackinlay, Xerox PARC, CHI’95

24. GVU 11/2000 24 Aaaamon.dll Edb500.dll Label.exe Oakley.dll Tapi.dll Wavemsp.dll Index View - 1995  T. Masui, Sharp, UIST95  Vertical picks focus  Horizontal controls zoom  T. Masui, Sharp, UIST95  Vertical picks focus  Horizontal controls zoom Aaaamon.dll Edb500.dll Label.exe Oakley.dll Tapi.dll Wavemsp.dll Ksproxy.ax Label.exe Lmrt.dll Aaaamon.dll Edb500.dll Label.exe Oakley.dll Tapi.dll Wavemsp.dll Ksproxy.ax Ksuser.dll Label.exe Legacy.inf Lmrt.dll Aaaamon.dll Edb500.dll Label.exe Oakley.dll Tapi.dll Wavemsp.dll Ksproxy.ax Ksqmf.ax Ksuser.dll Ksvpintf.ax Label.exe Lanman.drv Legacy.inf Linkinfo.dill Lmrt.dll

25. GVU 11/2000 25 H3 - 1997  Munzner, Stanford Univ., InfoVis’97  Projected onto sphere  20,000 nodes  Munzner, Stanford Univ., InfoVis’97  Projected onto sphere  20,000 nodes

26. GVU 11/2000 26 Reconfigurable Disk Tree - 1998  Jeong and Pang, UC Santa Cruz, InfoVis’98  Number of identifiable nodes: 3000 – 4000  Jeong and Pang, UC Santa Cruz, InfoVis’98  Number of identifiable nodes: 3000 – 4000

27. GVU 11/2000 27 Disk Tree - 1998  Chi et al, Xerox PARC, CHI’98  Compact 2D representation  Chi et al, Xerox PARC, CHI’98  Compact 2D representation

28. GVU 11/2000 28 Sunburst - 2000  Stasko & Zhang, Georgia Tech, InfoVis 2000  Radial space-filling  Techniques for viewing more detail  Stasko & Zhang, Georgia Tech, InfoVis 2000  Radial space-filling  Techniques for viewing more detail

29. GVU 11/2000 29 Visualization Taxonomy - 1994 Noik (Graphics Interface’94)  Implicit (use of perspective)  Continuous focus and context  Filtered (removing items of low interest)  Discrete focus and context  Distorted (size, shape, position of elements)  Adorned (color, texture) Noik (Graphics Interface’94)  Implicit (use of perspective)  Continuous focus and context  Filtered (removing items of low interest)  Discrete focus and context  Distorted (size, shape, position of elements)  Adorned (color, texture)

30. GVU 11/2000 30 Unresolved Problems  Multiple focus

31. GVU 11/2000 31 Folding Paper - proposal

32. GVU 11/2000 32 Multiple Focus in 3D - proposal

33. GVU 11/2000 33 InfoBowl - proposal

34. GVU 11/2000 34 Unresolved Problems  Multiple focus  Multiple hierarchies  Multiple focus  Multiple hierarchies

35. GVU 11/2000 35 Multiple Hierarchies  One hierarchy changing over time  Time Tube  Taxonomy visualization  MultiTrees (shared subtrees)  XML3D  Polyarchy (multiple intersecting hierarchies)  One hierarchy changing over time  Time Tube  Taxonomy visualization  MultiTrees (shared subtrees)  XML3D  Polyarchy (multiple intersecting hierarchies)

36. GVU 11/2000 36 Time Tube - 1998  Chi et al., Xerox PARC, CHI’98

37. GVU 11/2000 37 Taxonomy Visualization - 2000  Graham et al., Napier Univ. IJHCS 2000

38. GVU 11/2000 38 MultiTrees - 1994  Furnas & Zacks, Bell Core, CHI’94  DAG’s with shared subtrees  Furnas & Zacks, Bell Core, CHI’94  DAG’s with shared subtrees

39. GVU 11/2000 39 XML3D - 2000  Munzner, Stanford, IJHCS 2000

40. GVU 11/2000 40 Polyarchy Visualization Problem: People and Resources Example Multiple Hierarchies Exist  Direct reporting  Cost or Profit Center  Location  Implicit relationships Multiple Hierarchies Exist  Direct reporting  Cost or Profit Center  Location  Implicit relationships But only one hierarchy is shown

41. GVU 11/2000 41 Show Other Hierarchies Find: Daniel Robbins  Naming hierarchy is default  Allow maintainer to define hierarchies  Show search results in current view  Morph between views  Naming hierarchy is default  Allow maintainer to define hierarchies  Show search results in current view  Morph between views

42. GVU 11/2000 42 Visualization Opportunities  Perceptual cues to provide pattern information  User can search or browse  Show hierarchies an object participates in  Show relationships between hierarchies  Show relationships between objects  Perceptual cues to provide pattern information  User can search or browse  Show hierarchies an object participates in  Show relationships between hierarchies  Show relationships between objects

43. GVU 11/2000 43 One Selection, One Hierarchy

44. GVU 11/2000 44 Visual Pivot – Other Hierarchies

45. GVU 11/2000 45 Relationships Between People

46. GVU 11/2000 46 Relationships Between Multiple People

47. GVU 11/2000 47 Unresolved Problems  Multiple focus  Multiple hierarchies  Evaluate hierarchy visualizations  Multiple focus  Multiple hierarchies  Evaluate hierarchy visualizations

48. GVU 11/2000 48 Polyarchy Visualization User Studies  Study 1: Mockup of visual pivot  Issues list guided development of prototype  Study 2: Prototype: 2D vs 3D  Visual Pivot animation was misleading  Animation Speeds were too slow  Study 1: Mockup of visual pivot  Issues list guided development of prototype  Study 2: Prototype: 2D vs 3D  Visual Pivot animation was misleading  Animation Speeds were too slow

49. GVU 11/2000 49 Polyarchy Visualization User Studies  Study 3: Animation Styles and Speeds  Six animation styles: Picked two best  Twice as fast as study 2: Still too slow  Study 4: Prototype: 2D vs 3D  Identified most effective animation style  Identified best speed range  Study 3: Animation Styles and Speeds  Six animation styles: Picked two best  Twice as fast as study 2: Still too slow  Study 4: Prototype: 2D vs 3D  Identified most effective animation style  Identified best speed range

50. GVU 11/2000 50 Two Styles of Visual Pivot  Sliding  Rotating  Sliding  Rotating

51. GVU 11/2000 51 Visual Pivot Styles Sliding versus Rotating

52. GVU 11/2000 52 Visual Pivot Styles Learning Effects

53. GVU 11/2000 53 Visual Pivot Speed

54. GVU 11/2000 54 Unresolved Problems  Multiple focus  Multiple hierarchies  Evaluate hierarchy visualizations  Get the solutions out to real users!  Multiple focus  Multiple hierarchies  Evaluate hierarchy visualizations  Get the solutions out to real users!

55. GVU 11/2000 55 Summary Use perception to reduce cognitive overhead Need continued research to solve problems  Help user focus on multiple items of interest without losing context  Multiple hierarchies and other relationships  Handle larger scale Evaluate  Iterate  get results out Use perception to reduce cognitive overhead Need continued research to solve problems  Help user focus on multiple items of interest without losing context  Multiple hierarchies and other relationships  Handle larger scale Evaluate  Iterate  get results out