Interaction Models I Marti Hearst (UCB SIMS) SIMS 213, UI Design & Development March 9, 1999.
1 SIMS 247: Information Visualization and Presentation Marti Hearst Oct 24, 2005.
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Transcript of 1 SIMS 247: Information Visualization and Presentation Marti Hearst Oct 24, 2005.
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Motivation: Standard time plots are very compelling, but can only display a limited amount of data
Timebox widgets for interactive explorationHochheiser and Shneiderman ‘02
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Usability studies
• 24 Computer Science students completed various tasks using different but semantically equivalent input mechanisms:– Timebox queries– Fill-in– Range sliders
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Study 1
• Fully specified tasks. (“During days 22-23, are there more stocks between 69-119, 59-109, or 49-99”)– Form fill in fastest– Range sliders second.– Timeboxes last.
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Study 2
• More open-ended tasks.• Compare:
– Timeboxes with graphical output– Forms with graphical output– Forms with tabular output
• No statistically significant difference.
(Were the users already familiar with timeboxes?)
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Visualization for Analysis• Carlis & Konstan, UIST 1998
• For: data that is both periodic and serial– Time students spend on different activities– Tree growth patterns
• Time: which year• Period: yearly
– Multi-day races such as the Tour de France– Calendars arbitrarily wrap around at end of month– Octaves in music
• Problem: How to find patterns along both dimensions?
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Carlis & Konstan, UIST 1998.
•All 112 foods, alphabetical
•Color corresponds to food type
•Rings rather than blots to aid visibility
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Analyzing Complex Periodic Data
Carlis & Konstan, UIST 1998.
•12 most common foods
•Consumption values for each month appear as spikes
•Each food has its own color
•Boundary line (in black) shows when season begins/ends
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Analyzing Complex Periodic Data
Carlis & Konstan, UIST 1998.
•Different use of the viz in the chimp domain
•2 chimps (red and blue)
•Length of line is size of the group they travel with
•Top spiral is average size
•Bottom spiral is max size
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Carlis & Konstan
• An excellent example of infoviz– Provides clarity about information that is not
otherwise possible– Makes excellent use of visual principles
• Color, size, position all used properly• Different features are easy to discriminate, do not
interfere with one another
– Applicable to many different types of problems• Different levels of complexity
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Video WorkbenchSteele, Hearst, Rowe ‘98
http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf
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Video WorkbenchSteele, Hearst, Rowe ‘98
http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf
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Video WorkbenchSteele, Hearst, Rowe ‘98http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf
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Video WorkbenchSteele, Hearst, Rowe ‘98http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf
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Video WorkbenchSteele, Hearst, Rowe ‘98http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf
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Usability in Video Interfaces
• Christel & Moraveji ’04. Finding the Right Shots: Assessing Usability and Performance of a Digital Video Library Interface.
• Hauptman & Christel ’04 . Successful Approaches in the TREC Video Retrieval Evaluations.
• Christel, M., Moraveji, N., and Huang, C. ’04 Evaluating Content-Based Filters for Image and Video Retrieval.