cs5984: Information Visualization Chris North Trees 2 cs5984: Information Visualization Chris North

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

Containment Approach

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

Treemaps

Treemaps Balanced trees

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

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)

Cushion Treemaps Van Wijk

Squared Treemaps Wattenberg Van Wijk

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

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

Today Stasko, “Sunburst”, web Marcus, Marty

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

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