1. A Quick Guide to Information Visualization
Yingcai Xiao

2. Visualization
Representing
data as
computer graphics.

3. Scientific, Engineering and Information Visualization
Scientific Visualization: Scientific Data
Engineering Visualization: Measurement Data
Information Visualization: Abstract Data

4. Scientific and Engineering Visualization
Scientific & Measurement Data are physical data representing physical properties (temperature, pressure, wind speed, tension, …) of the physical world.
Scientific Visualization & Engineering Visualization are commonly used to represent the physical world.

5. Information Visualization
Abstract Data are usually non-physical data representing social information in the society: population, traffic, movie rating, …
Information Visualization is commonly used to represent social information

6. Abstract Data
Visualization through computer graphics are done in space (screen) and time (animation).
We need to study the spatial and temporal characteristics of abstract data.

7. Spatial Characteristics of Abstract Data
Some has location association: population, traffic, …
Some don’t have location association: movie rating.
Most of them don’t have spatial continuity, therefore, can’t be interpolated.

8. Temporal Characteristics of Abstract Data
Some have temporal continuity: population
Some have temporal continuity at certain time scale: traffic flow on a city street with signal lights.

9. Characteristics of Abstract Data
Some are high dimensional: GDP factors.
Some are physical data but with characteristics closer to abstract data than most physical data: genomic data.

10. Challenges of Information Visualization
One of the main challenges of Information Visualization is that most abstract data have no spatial continuity, hence, not interpolatible.
Some even do not have any spatial association, for example, movie rating.

11. Data Structures & Algorithms
Data tables (database, spreadsheet).
Algorithms:
Charts, maps, animations, parallel coordinates, application specific methods (collision diagrams).

12. Charts

13. Charts
Take advantage of the fact that most abstract data has no spatial correlation, arrange graphics in any spatial order which makes it easy for users to analyze data values.

14. Charting Methods
Column/Bar, Line/Area, Pie/Doughnut, Treemap/Sunburst, Histogram, Box-Whisker, Scatter/Bubble, Waterfall, Funnel, Stock, Surface, Radar,
Combo

15. Charting Tools
Spreadsheet charting tools
Capstone Project Evaluation.xlsx
Insert->Charts:
Column/Bar, Line/Area, Pie/Doughnut, Treemap/Sunburst, Histogram, Box-Whisker, Scatter/Bubble, Waterfall, Funnel, Stock, Surface, Radar, Combo

16. Charting Tools Online charting tools Google charts:
API:

17. Maps

18. Maps
Maps are used to display geographical related information: population, traffic, road map, …
GIS: geographical information systems

19. Mapping Tools

20. Mapping Tools

21. Animation

22. Animation
Take advantage of the fact that some abstract data have temporal continuity, animate data with time-sequences of graphics.
All charts and maps can be animated.

23. Animation
Sounding of PI
Music Visualization:
Line Riders - Beethoven's 5th

24. Animation Tools http://www.gapminder.org

25. Animation Tools

26. High-dimensional Data
Parallel Coordinates

27. High dimensional data can’t be mapped to a 3D or 2D space directly.
Professor Alfred Inselberg introduced Parallel Coordinate in 1959.

28. High Dimensional Data
In traditional coordinate systems, axes are perpendicular, a data point is represented as a graphical point (a dot) in the space.

29. High Dimensional Data
In parallel coordinate systems, axes are parallel to each other, a data point is represented as a graphical line (a polyline) in the space.

30. High Dimensional Data
Parallel Coordinates in 3D
ChrisSuma-Thesis.pdf

31. Data Sources

32. Data Source
(over 500 data sets with visualization)

33. Data Source

34. NIH Data
Visible Human Project

35. Tools & APIs

36. Listing

37. Google Tools & APIs http://www.visualisingdata.com/resources/

38. Census Data Tools https://www.census.gov/library/visualizations.html

39. Bokeh API https://bokeh.pydata.org/en/latest/
“Bokeh is an interactive visualization library that targets modern web browsers for presentation. It is good for:
Interactive visualization in modern browsers
Standalone HTML documents, or server-backed apps
Expressive and versatile graphics
Large, dynamic or streaming data
Easy usage from python (or Scala, or R, or...)
No JS required

40. Bokeh API https://bokeh.pydata.org/en/latest/docs/gallery.html#gallery

41. Parallel Coordinate Apps & APIs
Xdat.org

42. Other Info Vis Apps & APIs

43. Info Vis Examples

44. Info Vis Examples

45. Summary Information Visualization Abstract Data
Spatial and Temporal Characteristics
Visualization Methods
Data Sources
Programming APIs