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Visual Overview Strategies

Visual Overview Strategies. cs5984: Information Visualization Chris North. Homework 1. Grading: +,  , -, 0 Tablelens + Shows all attributes simultaneously (overview) Sorting: relates 1 attribute  Many attributes Spotfire + multiple representations (scatter, 3D, bar, histo, …)

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Visual Overview Strategies

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  1. Visual Overview Strategies cs5984: Information Visualization Chris North

  2. Homework 1 • Grading: +, , -, 0 • Tablelens • + Shows all attributes simultaneously (overview) • Sorting: relates 1 attribute  Many attributes • Spotfire • + multiple representations (scatter, 3D, bar, histo, …) • + details-on-demand better than Tablelens F+C • - scatterplot 2D occlusion problem • Scatter: relates 1 attribute  1 attribute • Strategy: • First: Tablelens for overview • Then: Spotfire for detail analysis

  3. Visual Overview Design Goals • Visual: take advantage of human visual processing • Information Rich: show as much as you can! (while maintaining a clean design) • Interaction Affordances: enable quick access to details • E.g. Zooming, Overview+Detail, Focus+Context

  4. Visual Overview Advantages Helps solve the Keyhole Problem: • Map, organization (spatial layout of concepts) • What information is (not) available? • Adds context info, relationships • Enables direct access • Encourages exploration • HCI metrics: • Improves user performance, learning time, error rates, retention, satisfaction • Studies, e.g. Beard & Walker, Chimera, North, etc.

  5. Strategy • Strategy 1: Display everything! • Only works for small scale • Strategy 2: Reduce scale to fit screen • Reduce items • Reduce attributes • Reduce value “size”

  6. Strategies • Filtering • Aggregation / Abstraction • Reduced Representation

  7. Filtering • Filter attributes • Scatterplot: selects 2 attributes, ignores rest • Filter items • VIDA (Visual Info Density Adjuster): show high priority items, representative set (video) • Human-Eye View: focused info density

  8. Aggregation • Aggregate items • Grouping several items into one (e.g. SQL “group by”) • Snap-Together Visualization: overview+detail, drill down • Semantic zooming • Pad++ (Abstraction) • Lifelines? • NetViz • Aggregate attributes • Star Coordinates

  9. Reduced Representation • Stasko, “Information Mural”, web • sanjini, luhui

  10. Assignment - Trees • Read for Tues • Rao, “Hyperbolic Tree”, book pg 382 • Joy, maulik • Kumar, “Multi-level DQ and Pruning”, book pg 295 • Read for Thurs • Johnson, “Treemaps”, book pg 152 • Stasko, “Sunburst”, web • Marcus, marty • Project groups meet with me early next week

  11. Homework #2 • Due: Thurs March 1 (1 week) • Visualization Design • Visualizing timed paths • (the bus schedule problem!)

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