1. Information Visualization
Chap. 11
November 25 , 2008
CDS 301
Fall, 2008
Jie Zhang
Copyright ©

2. Information Visualization
FFmpeg file hierarchy:
5 layers,
42 folders,
785 files
MPEG: Moving Pictures Expert Group
Codec: coding/decoding
FFMPEG: Fast Forward MPEG
gif: Graphics Interchange Format
png: Portable Network Graphics

3. Infovis versus Scivis Scientific Visualization (Scivis)
Visualize physical Data: continuous quantities over compact domain
Information Visualization (Infovis)
Visualize abstract data: texts over an information system
E.g., computer file systems, databases, documents, stocks etc
Visualization: “form a mental model of the subject” 3

4. Outline 11.1. Introduction 11.2. What is Infovis?
11.3. Infovis versus Scivis
11.4. Table Visualization (by )
Visualization of Relations
Tree Visualization (by )
Graph Visualization (by )
11.6. Multivariate Data Visualization (by )
11.7. Text Visualization (by ) 4

5. Dataset Dataset of Scientific Visualization (Scivis)
Data Domain: consists of sampling points and cells which form a geometric grid over a compact region
Data attribute: numerical quantities of different dimensions
Interpolation functions: reconstruct a piecewise continuous signal over the cells in the grid 5

6. Data Domain
Data Domain: Infovis does not have spatial placement: no points, no cells.
Space placement is referred to as layout, which is subjective
Data are sampled on data sets or tuples
Different data sets have relations 6

7. Data Domain
Scivis
Infovis 7

8. Dataset
Data attributes: Infovis has more data types than numerical values
Data Type
Attribute Domain
Operations
Examples
nominal
Unordered set
Comparison
(=)
Text, references, syntax elements
ordinal
Ordered set
Ordering
(=, <, >)
Ratings (e.g., bad, average, good)
discrete
Integer
Integer arithmetic
Line of code
continuous
real
Real arithmetic
Code metrics 8

9. Dataset Data attributes can be classified into Value data
Relational data, e.g., association, reference, contain 9

10. Interpolation
Infovis is inherently discrete, and can not carry out the interpolation 10

11. Summary Scivis Infovis Data Domain spatial, compact
non-spatial, abstract
Attribute Type
numerical
any data type
Data Points
Samples over the domain
Tuples of attributes without spatial locaiton
Cells
Support interpolation
Describe relations
Interpolation
Piecewise continuous
inexistent 11

12. Information Visualization
(continued)
Information Visualization
Chap. 11
Nov. 25, 2008 12

13. Table Visualization 13

14. Table Visualization 14

15. Table Visualization 15

16. Tree Visualization 16

17. Tree Visualization 17

18. Tree Visualization 18

19. Tree Visualization 19

20. Tree Visualization 20

21. Tree Visualization 21

22. Tree Visualization 22

23. Tree Visualization 23

24. Graph Visualization 24

25. Graph Visualization 25

26. Graph Visualization 26

27. Graph Visualization 27

28. Graph Visualization 28

29. Graph Visualization 29

30. Multivariate Data Visualization30

31. Multivariate Data Visualization31

32. Multivariate Data Visualization32

33. Text Visualization 33

34. Text Visualization 34

35. Text Visualization 35

36. Text Visualization 36

37. End of Chap. 11 37