Tree-Maps: A Space-Filling Approach to the Visualization of Hierarchical Information Structures

1. Tree-Maps: A Space-Filling Approach to the Visualization of Hierarchical Information Structures Brian Johnson Ben Shneiderman (HCIL TR 91-06) Steve Betten February 14, 2001

2. Outline of Paper • Introduction • Comparison of methods • Example: directory tree • Treemap method • Algorithms • Coping with size • Future research directions

3. Introduction • Motivation: large hierarchical data • Methods • Spatial versus textual methods • Interactive versus static methods • Objectives • Efficient space utilization, interactivity, comprehension, aesthetics • Hierarchical data: structure and content • Treemap emphasis on structure and leaves

4. Comparison of Methods • Motivating example • Viewing large file system hierarchies • Existing methods • Listings, outlines, tree diagrams • General problems • Navigational difficulty • Hidden content information • Text display of content information • Treemap

5. Comparison: Existing Methods • Listings (e.g. Unix ls, DOS dir) • Good: detailed content information • Bad: navigation difficulty with explicit paths or manual traversal • Outlines (e.g., Unix du, Windows explorer) • Good: display of both structure and content • Bad: navigation difficulty; only a few lines of nodes show at a time • Listing and Outlines • Bad: required display space is linearly proportional to number of nodes

6. Comparison: Existing Methods (Continued) • Tree diagrams • Good • Effectiveness and pleasantness for small hierarchies • Bad • Inefficient space utilization • Connections between nodes • 50% of display is background • Only partial success of zooming and panning • Lack of content information in large hierarchies • Cluttering from text • For visual cues, insufficient size of nodes

7. Comparison: Treemap • Good • Efficient utilization of display area • Implicit display of structure • No need to draw separate internal nodes • More space for leaves and visual content cues • Overview of entire hierarchy • Rapid movement to any node • Preservation of context • Required display space is proportional to square root of number of nodes

8. Example: Directory Tree • Problems with existing methods • Outline (Windows explorer): too many lines • Tree diagram (Open Windows File Manager): wasted space • Venn diagram: wasted space • Treemap (nested and non-nested) • Easy identification of largest files on entire file system • Easy identification of application, system, text, picture, and archive files

9. Treemap Method • Structural information: partitioning • Weight (degree of interest) for each node • Properties • Node overlap only with ancestors or descendents • Node display area proportional to weight • Node weight  sum of children's weights • Structural information • Implicitness via slice-and-dice • Explicitness via additional nesting

10. Treemap Method (Continued) • Content information • Visual cues: color, texture, blinking • Popup windows that display content • Auditory cues that precede popup windows • User control of properties that decreases on-screen complexity

11. Algorithms • Drawing of treemap • Tracking of cursor movement • Interactive display of node details

12. Coping with Size • Average case analysis: pixels per file • Problem of small nodes not displaying • Possible solutions: magnification, zooming • Insignificance (can usually ignore them)

13. Future Research Directions • Alternative partitioning methods • Top-down • Visual cues for numeric and non-numeric content information • Dynamic views (animation over time) • Stock portfolio • Node operations • Zooming, marking, selecting, searching

14. Favorite Sentence • Beard: “Users are never lost because they can see the complete information space.” • Expression of primary goal of treemap • Use of 2D graphics and implicit internal nodes • Display of entire hierarchy at once (structure) • Significant visual cues for most nodes (content) • Solution to previous navigation and content problems

15. Contributions • Demonstration of application and effectiveness of treemap • Provision of worthwhile direction for future research • Alternative partitioning methods • Applications: stock (Smartmoney) • Propagation of treemap concept • Widely cited paper from 1991 IEEE Visualization conference

16. Critique • Good • Definition of problem domain • Comparison to existing methods • Concrete and relevant example • Algorithms • Bad • Lack of emphasis on the difficulty of comparing rectangles with different aspect ratios • Future research

17. Academia 1992: stock portfolio visualization 1994: decision making 1994: satellite management 1999: cushion treemap; squarified treemap 2000: parameterized rectangles 2000: TreeMap2000 2000: pivot by size; pivot by position Industry DiskMapper SeeDiff software code viewer Storyspace hypertext authoring system Tcl/Tk widget Smartmoney PeopleMap Peets Coffee Treemap Developments

18. Link Recommendations • UMD HCIL history of treemap • www.cs.umd.edu/hcil/treemaps • TreeMap2000 • www.cs.umd.edu/hcil/treemaps/treemap2000 • Demo comparison of five treemap partitioning algorithms • www.columbia.edu/~mmw111/treemap/layout.html