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Visualization Design

Visualization Design. cs5984: Information Visualization Chris North. Spotfire. Simple Visualization Model. Data. View Port. Visual Mapping. Data Table. Attributes. Types: Quantitative Ordinal Nominal/Categorical. Items (aka: cases, tuples, data points, …). Visual Mapping.

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Visualization Design

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  1. Visualization Design cs5984: Information Visualization Chris North

  2. Spotfire

  3. Simple Visualization Model Data View Port Visual Mapping

  4. Data Table Attributes • Types: • Quantitative • Ordinal • Nominal/Categorical Items (aka: cases, tuples, data points, …)

  5. Visual Mapping • Define a Space • Map: data  marks • Map: data attributes  graphical mark attributes • Year  X • Length  Y • Popularity  size • Subject  color • Award?  shape

  6. Ranking Visual Attributes • Position • Length • Angle, Slope • Size • Color Increased accuracy for quantitative data -Cleveland

  7. Visualization Design Process Primary Inputs: • Data • User Task • Compare, known item search, patterns, outliers,… • Scale • # items • dimensionality • User characteristics • Standards/guidelines • System resources • Bag of tricks: • View types • Interaction strategies Design Visualization

  8. Design Principles • 5 HCI Metrics: • User performance *** • Error rate • User satisfaction • Learning time • retention

  9. Interactivity • Interaction to handle increased scale • Direct Manipulation • Visual representation • Rapid, incremental, reversible actions • Pointing instead of typing • Immediate, continuous feedback • Encourage exploration

  10. Increase Data Density • Calculate data/pixel “A pixel is a terrible thing to waste.”

  11. Eliminate “Chart Junk” • How much “ink” is used for non-data? • Reclaim empty space (% screen empty) • Attempt simplicity(e.g. am I using 3djust for coolness?)

  12. Information Visualization Mantra • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand E.g. Spotfire

  13. Query Previews • http://www.cs.umd.edu/~egemen/demo.html

  14. Data Space • Multi-dimensional: databases,… • 1D: timelines,… • 2D: maps,… • 3D: volumes,… • Hierarchies/Trees: directories,… • Networks/Graphs: web, communications,… • Document collections: digital libraries,…

  15. Assignment • Read for Tues: • Inselberg “Multidimensional detective” (parallel coordinates) book p107 (margaret, josh s) • Kandogan “Star Coordinates” web (matt c, fanye) • Read for Thurs: • Rao “Table Lens” p343,597 (marty e, purvi) • Feiner “Worlds within Worlds” p96 (scott m, ?) • Find some interesting data • Send me your picture

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