2. National Computational Science Alliance INTRODUCTION TO VISUALIZATION Alan B. Craig, Ph.D. Materials from: Dr. Alan Shih, Dave Bock, and Alan Craig, plus all the researchers who provided examples National Center for Supercomputing Applications University of Illinois at Urbana-Champaign June 3, 2010

3. National Computational Science Alliance Dr. Alan M. Shih What Is Visualization?! Visualization existed before the invention of computers Representation of information allowing us to perceive such information visually

4. National Computational Science Alliance Early Representation The Cave of Lascaux, France ~15,000 years old - Tells a story

5. National Computational Science Alliance Planetary Orbits Tenth century Inclinations of the planetary orbits as a function of time. Oldest known attempt to show changing values graphically.

6. National Computational Science Alliance 1987 NSF Panel Initiative - Formal Definition "Visualization is a method of computing. It transforms the symbolic into the geometric, enabling researchers to observe their simulations and computations. Visualization offers a method for seeing the unseen. It enriches the process of scientific discovery and fosters profound and unexpected insights.” Richard Hamming: "The purpose of computing is insight, not numbers." Goal of visualization - leverage existing scientific methods by providing new scientific insight through visual methods.

7. National Computational Science Alliance Why do we do it? Because we NEED to...

8. National Computational Science Alliance Purpose of Visualization Self study / analysis –interactive exploration –gain understanding Between Peers –Probing inside the problem domain –Analyzing data –Communicating with peers Presentation to General Public –Overall visualization –Presentation of data –Communicating with general audience

9. National Computational Science Alliance Dr. Alan M. Shih Data Sources Computational Sciences –Computational Fluid Dynamics –Computational Structured Mechanics –Computational Chemistry –Computational ….. Observed Data –Wind Tunnels –Field Observations –Space Probes

10. National Computational Science Alliance What is Visualization Choice of appropriate representation

11. National Computational Science Alliance Dr. Alan M. Shih Computational Sciences We can realize, without physical prototypes –the performance of a design –the possible outcome of a scenario –the physical details that we did not know or notice Benefits –Reduces development cost –Reduces development time –Reduces development risk

12. National Computational Science Alliance Dr. Alan M. Shih Computational Sciences Computers brought about the ability to collect, create, and store more information Is a process of simulating a relevant subset of the laws of nature through a set of equations Yields a set of numeric solutions -- Numbers, LOTS of them May not be able to see, much less interpret, all of the results.

13. National Computational Science Alliance Dr. Alan M. Shih Visualization of Data Try to envision the domain in your mind

14. National Computational Science Alliance Dr. Alan M. Shih Visualization of Data But, with some modifications to the images...

15. National Computational Science Alliance Dr. Alan M. Shih Visualization of Data Interpolated vs. Non-interpolated

16. National Computational Science Alliance Interactive or Batch? Interactive Visualization –Allows the Ability to Control in Real-Time –Limits the Amount of Data to Be Visualized. –Useful for Analysis and Exploration Batch Visualization –High-Quality, Complex Representation –No Control in Real Time. –Useful for Presentation, Communication, high complexity

17. National Computational Science Alliance The Visualization Pipeline Data (simulated or observed) Filter Map to geometry Viewing Attributes Object Attributes Render Display Record Loop to appropriate step...

18. National Computational Science Alliance Dr. Alan M. Shih Computer Art and Scientific Visualization Cox, Donna; Patterson, Robert; Bargar, Robin; Daab, Fred; Moore, Michael; Moorman, Jan; Waegner, Chris; Erickson, Christian; Swing, Chris; Conrad, Renee; Knocke, Joel; Jordan, Robert; Brandys, Mike; Fossum, Barbara; Colby, Don; McNeil, Mike; Bajuk, Mark; Arrott, Matthew; Swanson, Amy Researchers Cerco, Carl; Noel, Mark; CEWES Visualizaiton Stein, Robert; Shih, Alan; NCSA

19. National Computational Science Alliance Qualitative vs. Quantitative

20. National Computational Science Alliance A Wonderful Example

21. National Computational Science Alliance Static vs. Time Varying

22. National Computational Science Alliance Static vs. Time-Varying Data Static –At an particular instance of time –Particular Point of View, etc. Time-Varying Animation –Evolving along the time line –Dynamic Data or Point of View

23. National Computational Science Alliance Dr. Alan M. Shih Representational Techniques Realistic Abstract Researchers Cooper, David; Caterpillar Inc. Visualization Bajuk, Mark; NCSA, 1991 Researchers Cohen, Josef Visualization Cox, Donna, NCSA; Ellson, Rich; Olano, Marc, Eastman Kodak:

24. National Computational Science Alliance Dr. Alan M. Shih Representation Techniques Texture Mapping Visualization Stein, Robert, Baker, Polly, NCSA, ongoing Sponsored by ARL

25. National Computational Science Alliance Dr. Alan M. Shih Representation Techniques Ball & Stick Contour Researchers Treutlein, Herbert; Schulten, Klaus; Physics Department Technical University of Munich Visualization Arrott, Matthew; NCSA, 1987 Researchers Herron, David, Eli Lilly & Co. Visualization Thingvold, Jeffrey A.; Sherman, William; NCSA, 1991 Researcher Taylor, Lafe Visualization Shih, Alan, MSU, 1993

26. National Computational Science Alliance Dr. Alan M. Shih Representation Techniques False Color Height/Deformation Researchers and visualization Haber, Bob; Lee, Hae-Sung; Koh, Hyun; NCSA, 1989 Researchers Kovacic, David A., Romme, William H., Despain, Don G. Visualization Craig, Alan; NCSA, 1990

27. National Computational Science Alliance Dr. Alan M. Shih Representation Techniques Particulate/ Trace Iso-surfaces Researchers Wilhelmson, Robert; Brooks, Harold; Jewett, Brian; Shaw, Crystal; Wicker, Louis; Department of Atmospheric Science and NCSA Visualization Arrott, Matthew; Bajuk, Mark; Thingvold, Jeffrey; Yost, Jeffery; Bushell, Colleen; Brady, Dan; Patterson, Bob Produced by the Visualization Services and Development Group, NCSA

28. National Computational Science Alliance Dr. Alan M. Shih Representation Techniques Data from Aerodynamics and Acoustics of Rotorcraft, W. J. McCroskey, Principal Investigator Animation: FAST Particle Traces: UFAT

29. National Computational Science Alliance Dr. Alan M. Shih Scientific Visualization Damage Structure Researcher Namburu, Raju, CEWES Visualization Boch, David; Heiland, Randy; Baker, Polly; NCSA Stephens, Mike; CEWES

30. National Computational Science Alliance Scientific Visualization Damage Structure -- Animation Researcher Namburu, Raju, CEWES Visualization Boch, David; Heiland, Randy; Baker, Polly; NCSA Stephens, Mike; CEWES

31. National Computational Science Alliance Dr. Alan M. Shih Beyond Visual Virtual Reality Environment –ImmersaDesk –Cave –Fully immersive sphere Haptic Devices Senses of hearing and smelling

32. National Computational Science Alliance Dr. Alan M. Shih Challenging Issues in SciVis Visualization of Large Data Sets –How to deal with exabytes of data? Remote Visualization –What is the best way to visualize large data sets on remote mainframe? Interactive Computation –How to monitor and steer ongoing simulations? Representation Techniques –How to represent the data that shows more information and shows it more clearly and accurately? Immersive Technologies

33. National Computational Science Alliance Dr. Alan M. Shih Summary The advent of computer capacity and power push the envelope of computational sciences and scientific visualization (SciVis) SciVis has revolutionized the way we do sciences SciVis provides scientists a process to probe into enormously large data sets, perceive incredible details of the domain, and discover unexpected insights. Challenging issues in SciVis evolve, but we will continue to face them, solve the problems, and face future challenges.

34. National Computational Science Alliance Visualization Tools

35. National Computational Science Alliance Dr. Alan M. Shih Visualization Tools

36. National Computational Science Alliance Dr. Alan M. Shih Layers of Information

37. National Computational Science Alliance Dr. Alan M. Shih Contour Surface & Volume Visualization

38. National Computational Science Alliance Dr. Alan M. Shih Composite Representation

39. National Computational Science Alliance Dr. Alan M. Shih Stereo Visualization Red-Blue Glasses –Lost color Shutter Glasses –60 Hz –Synchronized with projected images Polarized Glasses –Linear (Horizontal/Vertical) –Circular (CW/CCW) –Synchronized with projected images

40. National Computational Science Alliance Dr. Alan M. Shih Red-Blue Stereo Visualization

41. National Computational Science Alliance Dr. Alan M. Shih Animations