1. 1 SIMS 247: Information Visualization and Presentation Marti Hearst Oct 24, 2005

2. 2 Today Finish temporal visualization Serial information visualization Video visualization

3. 3 Searching Time Sequence Data

4. 4 Motivation: Standard time plots are very compelling, but can only display a limited amount of data Timebox widgets for interactive exploration Hochheiser and Shneiderman ‘02

5. 5 Idea: Query the data! (See video)

6. 6 Usability studies 24 Computer Science students completed various tasks using different but semantically equivalent input mechanisms: –Timebox queries –Fill-in –Range sliders

7. 7 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.

8. 8 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?)

9. 9 Compare to Wattenberg’s Time Graph Sketch

10. 10 Visualizing Serial Data

11. 11 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?

12. 12 Analyzing Complex Periodic Data Carlis & Konstan, UIST 1998.

13. 13 Carlis & Konstan, UIST 1998. All 112 foods, alphabetical Color corresponds to food type Rings rather than blots to aid visibility

14. 14 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

15. 15 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

16. 16 Analyzing Complex Periodic Data Carlis & Konstan, UIST 1998. Analyzing properties of sound

17. 17 Analyzing Complex Periodic Data Carlis & Konstan, UIST 1998.

18. 18 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

19. 19 Video Visualization

20. 20 MediaBrowser Drucker et al. ‘04 http://research.microsoft.com/~sdrucker/interest.htm

21. 21 SmartSkip Drucker et al. ‘01 http://research.microsoft.com/~sdrucker/interest.htm

22. 22 SmartSkip Drucker et al. ‘01 http://research.microsoft.com/~sdrucker/interest.htm

23. 23 SmartSkip Drucker et al. ‘01 http://research.microsoft.com/~sdrucker/interest.htm

24. 24 Video Workbench Steele, Hearst, Rowe ‘98 http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf

25. 25 Video Workbench Steele, Hearst, Rowe ‘98 http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf

26. 26 Video Workbench Steele, Hearst, Rowe ‘98 http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf

27. 27 Video Workbench Steele, Hearst, Rowe ‘98 http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf

28. 28 Video Workbench Steele, Hearst, Rowe ‘98 http://bmrc.berkeley.edu/research/publications/1999/153/steele.pdf

29. 29 DIVA MacKay & Lafon ’98 http://www-ihm.lri.fr/~mbl/DIVA/chi98-paper/introduction.html http://www-ihm.lri.fr/~mbl/DIVA/chi98-paper/introduction.html

30. 30 DIVA MacKay & Lafon ’98 http://www-ihm.lri.fr/~mbl/DIVA/chi98-paper/introduction.html http://www-ihm.lri.fr/~mbl/DIVA/chi98-paper/introduction.html

31. 31 DIVA MacKay & Lafon ’98 http://www-ihm.lri.fr/~mbl/DIVA/chi98-paper/introduction.html http://www-ihm.lri.fr/~mbl/DIVA/chi98-paper/introduction.html

32. 32 DIVA MacKay & Lafon ’98 http://www-ihm.lri.fr/~mbl/DIVA/chi98-paper/introduction.html http://www-ihm.lri.fr/~mbl/DIVA/chi98-paper/introduction.html

33. 33 Media Streams Davis ‘95

34. 34 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.

35. 35 Usability in Video Interfaces

36. 36 Usability in Video Interfaces