1. Scientific Information and
Data Visualization
CDS 301
Fall, 2008
Jie Zhang
Copyright ©

2. Introduction Visualization What? To be seen Why? To be understood
How? A pipeline
What? Most effective way human takes in information, digest information, making decision, and being creative
Why? One picture is worth 1000 words
How? A pipeline approach: acquisition, filtering, mapping and rendering

3. What?
Visualization is the process of presenting data in a visual form that allows rapid understanding and finding
Data visualization is at the crossroads of mathematics, computer science, cognitive and perception science, engineering, and physics.
Cave painting, drawing, diagram, bar charts, histograms, correlation plots
Figure:

4. Why? Provide “insights”
Answers to concrete questions about a given problem
Facts about a given problem that we are not aware of
Scientific insights
Understanding observations
Testing existing theories
Forming new hypothesis
Predictions
What is science? Physics, Chemistry, Biology, Psychology, Socialology
What is the scientific process? reasoning

5. Simulation of Galaxy Interaction
C:\teaching\resources\Visulization_Astronomy\VIDEO_TSVTS_17_1_VOB using Windows Media Player

6. Space Weather: the Process
It starts from an eruption from the Sun.
Prediction depends on how it propagates

7. Space Weather: the Systems

8. Space Weather: effects
On Communication and Navigation

9. Stereoscopic Technique
C:\teaching\2008\2008_CDS301\presentation\ch1_introduction\ _195.mov

10. Interactive Visualization

11. Info Canvas
C:\teaching\2008\2008_CDS301\resource\7infocanvas.mov

12. How? A Conceptual Pipeline Data Acquisition Filtering Mapping
Rendering
From dataset to visual representation
Data visualization (scivis)
Information visualization (infovis)
Raw dataset -> prepared dataset -> visual representation -> and draw visual representation
Terminology: narrow and broad definitions

13. Text Book Required: “Data Visualization: Principles and Practice”
by Alexandru C. Telea, 2008
Supplement:
“Information Visualization: Perception for Design”
By Colin Ware, 2004
“Information Visualization: Beyond the Horizon”
By Chaomei Chen, 2004
“Introduction to Scientific Visualization”
By Helen Wright, 2007

14. Content Introduction (Ch 1) From Graphics to Visualization (Ch 2)
Data Presentation (Ch 3)
Visualization Pipeline (Ch 4)
Scalar Visualization (Ch 5)
Vector Visualization (Ch 6)
Tensor Visualization (Ch 7)
Domain-Modeling Techniques (Ch 8)
Image Visualization (Ch 9)
Volume Visualization (Ch 10)
Information Visualization (Ch 11)
Human Perception (Daniel Carr)
OpenGL (Fernando Camelli)

15. Assignment and Grade Homework (25%) 6 - 8 homework or mini-projects
A comprehensive research project
Exams
One mid-term (20%)
one final (25%)
Attendance (5%)

16. Programming Tools
C/C++
OpenGL
Matlab
IDL (Interactive Data Language)

17. Contact
Office Hour: 3 – 4 PM, Thursday
or by appointment