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Multiple Views

Explore the power of multiple views in information visualization to handle complex datasets efficiently. Learn about coordination, brushing-and-linking techniques, and the Snap-Together Visualization concept. Discover how to synthesize various perspectives for a holistic understanding of data. Dive into interactive visualization methods for enhanced insights.

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Multiple Views

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  1. Multiple Views cs5984: Information Visualization Chris North

  2. Review • Many attributes: TableLens, Parallel Coords • Many items: StarCoords, Spotfire • Very Many items: Query Previews • Hard! Why? • Mental Max = 3- or 4-D • Can’t show everything, interaction is key

  3. Today • Roth, “Visage”, web (video) • josh, priya • North, “Snap-Together Visualization”, web

  4. Multiple Views • Problem: Can’t display everything in 1 view • Solution: Mutliple views • Key: Coordination / Tight-coupling • Scale: many attributes • brushing-and-linking • Scale: many items • Overview and detail

  5. Brushing and Linking

  6. Brushing and Linking • Multiple perspectives

  7. Brushing and Linking

  8. Overview and Detail

  9. Overview and Detail • Word • Web

  10. Overview and Detail

  11. Overview and Detail

  12. Synchronized Navigation • E.g. synchronized scrolling

  13. Snap-Together Visualization • Problem: What about other combinations? • Data • Tasks • Views • Coordination • Solution: Snap!

  14. Windows Explorer ++

  15. Web Logs

  16. Census Data

  17. Photo Library

  18. Mailing List

  19. Snap Concept • Put data tables into visualizations • Link actions together • Depends on relationship between tables Flexibility Actions: Actions:

  20. Project • Project Proposal due:  Tues Feb 20 • Mid-Project Report due:  Tues March 20 • Project Presentations:  April 24 - May 1 • Project Paper due:  May 7

  21. Project Proposal • Contribute original research! • Group size: 2 - 4 students • Development, Evaluation • Pick problem, propose solution, timetable

  22. Assignment • Read for Thurs • Plaisant, “Lifelines”, p 285 • chris r., margaret • Mackinlay, “Perspective Wall”, web • sumithra, gowri • Read for Tues • Eick, “SeeSoft”, p 419 • purvi, prasuna • Eick, “Data Visualization Sliders”, p 251 (2 pages)

  23. Next Time: 1-D • Lists • Text • Time series, timelines • Math series, progressions, • Temperature, distance, grading…

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