national computational science alliance introduction to visualization alan b. craig, ph.d. materials...
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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 ApplicationsUniversity of Illinois at Urbana-Champaign
June 3, 2010
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National Computational Science AllianceDr. Alan M. Shih
What Is Visualization?!
•Visualization existed before the invention of computers
•Representation of information allowing us to perceive such information visually
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National Computational Science Alliance
Early Representation
• The Cave of Lascaux, France
~15,000 years old
- Tells a story
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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.
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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.
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National Computational Science Alliance
Why do we do it?
• Because we NEED to...
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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
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National Computational Science AllianceDr. Alan M. Shih
Data Sources
• Computational Sciences– Computational Fluid Dynamics
– Computational Structured Mechanics
– Computational Chemistry
– Computational …..
• Observed Data– Wind Tunnels
– Field Observations
– Space Probes
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National Computational Science Alliance
What is Visualization
• Choice of appropriate representation
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National Computational Science AllianceDr. 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
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National Computational Science AllianceDr. 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 themNumbers, LOTS of them
• May not be able to see, much less interpret, all of the results.
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National Computational Science AllianceDr. Alan M. Shih
Visualization of Data
• Try to envision the domain in your mind
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National Computational Science AllianceDr. Alan M. Shih
Visualization of Data
• But, with some modifications to the images...
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National Computational Science AllianceDr. Alan M. Shih
Visualization of Data
• Interpolated vs. Non-interpolated
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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
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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...
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National Computational Science AllianceDr. 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
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National Computational Science Alliance
Qualitative vs. Quantitative
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National Computational Science Alliance
A Wonderful Example
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National Computational Science Alliance
Static vs. Time Varying
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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
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National Computational Science AllianceDr. 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:
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National Computational Science AllianceDr. Alan M. Shih
Representation Techniques
Texture Mapping
Visualization Stein, Robert, Baker, Polly, NCSA, ongoingSponsored by ARL
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National Computational Science AllianceDr. 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, LafeVisualization Shih, Alan, MSU, 1993
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National Computational Science AllianceDr. Alan M. Shih
Representation Techniques
• False Color
• Height/Deformation
Researchers and visualizationHaber, Bob; Lee, Hae-Sung; Koh, Hyun; NCSA, 1989
Researchers Kovacic, David A., Romme, William H., Despain, Don G.Visualization
Craig, Alan; NCSA, 1990
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National Computational Science AllianceDr. 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
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National Computational Science AllianceDr. Alan M. Shih
Representation Techniques
Data from Aerodynamics and Acoustics of Rotorcraft, W. J. McCroskey, Principal InvestigatorAnimation: FAST Particle Traces: UFAT
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National Computational Science AllianceDr. Alan M. Shih
Scientific Visualization
Damage Structure
Researcher Namburu, Raju, CEWESVisualization Boch, David; Heiland, Randy; Baker, Polly; NCSA Stephens, Mike; CEWES
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National Computational Science Alliance
Scientific Visualization
Damage Structure -- Animation
Researcher Namburu, Raju, CEWESVisualization Boch, David; Heiland, Randy; Baker, Polly; NCSA Stephens, Mike; CEWES
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National Computational Science AllianceDr. Alan M. Shih
Beyond Visual
• Virtual Reality Environment– ImmersaDesk
– Cave
– Fully immersive sphere
• Haptic Devices
• Senses of hearing and smelling
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National Computational Science AllianceDr. 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
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National Computational Science AllianceDr. 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.
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National Computational Science Alliance
Visualization Tools
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National Computational Science AllianceDr. Alan M. Shih
Visualization Tools
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National Computational Science AllianceDr. Alan M. Shih
Layers of Information
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National Computational Science AllianceDr. Alan M. Shih
Contour Surface & Volume Visualization
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National Computational Science AllianceDr. Alan M. Shih
Composite Representation
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National Computational Science AllianceDr. 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
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National Computational Science AllianceDr. Alan M. Shih
Red-Blue Stereo Visualization
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National Computational Science AllianceDr. Alan M. Shih
Animations