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Information Visualization: Trees

Learn about tree structures in information visualization, including navigation strategies, multi-dimensional data visualization, and different types of trees such as DAG and hierarchical trees. Explore examples of tree applications like book libraries, family trees, and NCAA March Madness. Understand approaches for structural analysis and navigation, including tree views, hyperbolic trees, 3D ConeTrees, and TreeMap visualizations.

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Information Visualization: Trees

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  1. Information Visualization:Trees Chris North cs3724: HCI

  2. Info Visualization Review • Multi-dimensional data vis • Navigation strategies

  3. Trees (Hierarchies) • What is a tree? • DAG, one parent per node • items (can have attributes) + structure • Data structure: parent ptr, array of children, LM child+RS • Size: #nodes = bheight • ResultSet -> Tree? • categorical • Parent ptr • Path name

  4. Examples • Example trees: • book libraries, folders, family trees, threaded msgs • NCAA march madness!!!! • Aisles, websites, org charts • Tasks: • search, drill down, browsings • Structural analysis, parents, children, • Least common ancestor

  5. 2 Approaches • Connection • node & link • E.g. TreeView widget • Containment • node in node • E.g. Venn diagram A B C A B C

  6. Detail Only • Dos: tree • Whats the problem?

  7. TreeView Widget • Good for directed search tasks • Good for text labeled nodes • Not good for learning structure • No attributes • Apx 50 items visible • Lose path to root for deep nodes • Scroll bar! • Error rate high • Fitt’s Law? • Too many small distant things

  8. Mac Finder

  9. Overview+Detail • Maryland

  10. Focus+Context • Hyperbolic Tree (star tree) • Radial; shrink with distance to center • Drag to navigate • Scalability? • Xerox PARC, Inxight • http://startree.inxight.com/

  11. Miniaturization • Disk Tree • Xerox PARC

  12. 3D • ConeTrees • Rotate subtrees • Pro: • Con: • Xerox PARC

  13. Ugh!

  14. 2 Approaches • Connection • node & link • E.g. TreeView widget • Containment • node in node • E.g. Venn diagram A B C A B C

  15. Zooming • TreeMaps • Slice and Dice, space filling • Node size & color encodes data attribute • Zoom on subtrees • Good for fixed-height trees • Scalability? • Maryland • http://www.cs.umd.edu/hcil/treemap3/

  16. “Squarified” TreeMap • http://www.research.microsoft.com/~masmith/all_map.jpg

  17. Cushion TreeMaps • Cushion TreeMaps • Free file directory browser • Van Wijk • http://www.win.tue.nl/sequoiaview/ • Map of the Market • http://www.smartmoney.com/marketmap/

  18. Radial Containment • SunBurst • Radial slicing • Animated zooming • Focus+Context • Georgia Tech

  19. Sunburst vs. Treemap • + Faster learning time: like pie chart • + Details outward, instead of inward • + Focus+context zooming • - Not space filling • - More space used by non-leaves • All leaves on 1-D space, perimeter • Treemap: 2-D space for leaves • - Smaller scalability?

  20. Multiple Foci? • Focus on 2 distant regions simultaneously • Microsoft Research

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