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Exploring Tree Visualization Techniques and Treemap Algorithms in Information Visualization

This document provides an in-depth analysis of various tree visualization approaches including connection, containment, and methods for visualizing structure versus attributes. It specifically focuses on treemaps, discussing techniques like slice and dice, balanced trees, and space-filling representations. The evaluation of treemaps highlights their efficiency in representing quantitative attributes and combines structures with multiple attributes for enhanced clarity. The document also references tools and resources for practical application of these visualization methods, including links to relevant web projects.

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Exploring Tree Visualization Techniques and Treemap Algorithms in Information Visualization

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  1. Trees 2 cs5984: Information Visualization Chris North

  2. 2 Approaches • Connection (node & link) • Containment (node in node) • Structure vs. attributes • Attributes only (multi-dimensional viz) • Structure only (1 attribute, e.g. name) • Structure + attributes A B C A B C

  3. Containment Approach

  4. Treemaps (Shneiderman) • Slice and Dice • Alternate horizontal andvertical cuts for levels • Node area  node attribute • Zoom onto nodes • Space-Filling • Structure + 3 attributes • Area, color, label

  5. Treemaps

  6. Treemaps Balanced trees

  7. Treemaps • ~ 1000 nodes • Quantitative attributes • Good combination of structure + attributes • For unbalanced trees, structure more difficult • Learning time: 20 min • Evaluation: major performance boost over outliner • Bad aspect ratios: long narrow rectangles • Large scale or deep causes solid black

  8. Treemap Algorithm • Calculate sizes: • Recurse to children • My size = sum children sizes • Draw Treemap (node, space, direction) • Draw node rectangle in space • Alternate direction • For each child: • Calculate childspace as % of node space using size and direction • Draw Treemap (child, child space, direction)

  9. Cushion Treemaps • Van Wijk

  10. Squared Treemaps • Wattenberg • Van Wijk

  11. Treemaps on the Web • Map of the Market: http://www.smartmoney.com/marketmap/ • People Map: http://www.truepeers.com/ • Coffee Map: http://www.peets.com/tast/11/coffee_selector.asp

  12. DiskMapper • http://www.miclog.com/dmdesc.htm

  13. Today • Stasko, “Sunburst”, web • Marcus, Marty

  14. Assignment • Spring Break! • Read for Tues (Mar 13) • Beaudoin, “Cheops”, web • Satya, Sumithra • Furnas, “Fisheye View”, book pg 311

  15. Projects • Data Structure Viz Tool • Data Structure Viz Evaluation • Biotech Viz • Network Traffic Viz • High-Dimensional Parameter Space Viz • Chat Log Viz • Web Snap • List Viz / Menu UI • Data Density and Distraction

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