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i247: Information Visualization and Presentation Marti Hearst. Design Choices in Building Basic Graphs. Few on How to Show Information. Few on Showing Information. Few on Showing Information. Few on How to Show Information. Few on How to Show Information. Few on Showing Information.
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i247: Information Visualization and PresentationMarti Hearst Design Choices in Building Basic Graphs
Last time: Class exercise • What did people find?
Example: Titanic Data • The data contains counts of women, men, children, the class of room they had, if they were passengers or crew, and if they survived or not. • What kinds of questions to we want to ask of this data?
Which Properties are Appropriate for Which Information Types?
Position Marks Points Lines Areas Retinal variables Color Size Shape Grayscale Orientation Texture x x x x x x x x x x x x x x x Bertin’s Graphical Vocabulary Adapted from Stone & Zellweger
Key Idea • How should data of various types be encoded into visual features? • Mapping quantities into shapes does not work! • 10 100 • But using extent works well Adapted from Stone & Zellweger
Interpretations of Graphical Vocabulary Some properties can be discriminated more accurately but don’t have intrinsic meaning (Senay & Ingatious 97, Kosslyn, others) • Density (Greyscale) Darker -> More • Size / Length / Area Larger -> More • Position Leftmost -> first, Topmost -> first • Hue no intrinsic meaning; good for highlighting • Slope / Shape • no intrinsic meaning; • good for contrast
Accuracy Ranking of Quantitative Perceptual TasksEstimated; only pairwise comparisons have been validated.(Mackinlay 88 from Cleveland & McGill)
Expressiveness rankings for Info Vis tasks [Bertin, adapted from Spence 2006] Adapted from Stone & Zellweger
Which properties used for what? Few’s Table:
More to come • We’ll also talk about Gestalt properties later, when we discuss perceptual principles in more detail.
Next Time • We’ll also talk about Gestalt properties later, when we discuss perceptual principles in more detail.