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cs5984: Information Visualization Chris North
Trees 2 cs5984: Information Visualization Chris North
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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
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Containment Approach
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Treemaps (Shneiderman)
Slice and Dice Alternate horizontal and vertical cuts for levels Node area node attribute Zoom onto nodes Space-Filling Structure + 3 attributes Area, color, label
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Treemaps
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Treemaps Balanced trees
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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
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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 child space as % of node space using size and direction Draw Treemap (child, child space, direction)
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Cushion Treemaps Van Wijk
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Squared Treemaps Wattenberg Van Wijk
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Treemaps on the Web Map of the Market: People Map: Coffee Map:
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DiskMapper
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Today Stasko, “Sunburst”, web Marcus, Marty
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Assignment Spring Break! Read for Tues (Mar 13)
Beaudoin, “Cheops”, web Satya, Sumithra Furnas, “Fisheye View”, book pg 311
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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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