1. Visualizing the Cosmos: Smoke or Mirrors? Designing Visualization Imagery David Bock National Center for Supercomputing Applications University of Illinois, Champaign-Urbana

2. Visualization Imagery Some Questions Some Questions How can we accurately represent ever-increasing and complex datasets? What is our artistic criteria for designing visualization imagery? So what, if any, are the boundaries between art and science?

3. Visualization Imagery Data Management Data Management Artistic Design Choices Artistic Design Choices

4. Visualization Imagery Data Management – Big Data Data Management – Big Data More computational power Increases in simulation scope, dimensionality Leads to very large datasets Difficult to represent entire dataset

5. Visualization Imagery Data Management – Non-uniform grids Data Management – Non-uniform grids Days of simple uniform grids coming to an end…

6. Visualization Imagery Data Management – Non-uniform grids Data Management – Non-uniform grids Adaptive Mesh Refinement (AMR) How do we represent varying levels of refinement? New grid structures - new visualization techniques

7. Visualization Imagery Data Management – Data to Image Data Management – Data to Image Minimize dataflow from data to image Avoid multiple steps, reduce round-off errors Avoid multiple software systems Render data directly

8. Visualization Imagery Data Management – Data to Image Data Management – Data to Image Accurately integrate different “primitives” Leverage existing software system Make visualization techniques deployable Elegant development environment

9. Visualization Imagery Data Management – a solution Data Management – a solution Perform mapping during rendering step Develop “shading models” for data Encapsulate visualization tasks in shaders Simple scene containing only data bounding box

10. Visualization Imagery Rendering Process Typical Rendering Process InputMappingRenderingOutput Visualization Package Hardware Render Animation Package Custom Renderer GeometryImageryData

11. Visualization Imagery Visualization Shading RenderMan Visualization Shader Imagery Visualization Shader Custom Visualization Software/Libraries Data

12. Visualization Imagery Visualization Shading Visualization Shading Some examples

13. Visualization Imagery Visualization Shading Visualization Shading Video example

14. Visualization Imagery Artistic design – Questions Artistic design – Questions How do we represent simulation results? Do we have any artistic leeway? What motivates our design decisions? Criteria for designing visualization imagery?

15. Visualization Imagery Artistic design – Benefit to scientist Artistic design – Benefit to scientist Model verification

16. Visualization Imagery Artistic design – Benefit to scientist Artistic design – Benefit to scientist Quantitative vs. Qualitative Analysis

17. Visualization Imagery Artistic design – Benefit to scientist Artistic design – Benefit to scientist Imagery for publication

18. Visualization Imagery Artistic design – How does it look? Artistic design – How does it look? Principles of animation – Appeal Do I find the representation engaging? Choosing elements Colors, color maps, materials Viewpoints, camera paths

19. Visualization Imagery Artistic design – Represent what? Artistic design – Represent what? Learn the science, listen to the scientist The “mind’s eye” of the scientist Visual language descriptions Einstein imagined concepts visually first

20. Visualization Imagery Artistic design – Represent what? Artistic design – Represent what? Be creative, experiment, research new techniques Avoid confinement to software packages Each simulation is a unique story Combine techniques, show relationships

21. Visualization Imagery Artistic design – Represent what? Artistic design – Represent what? Be creative, experiment, research new techniques Video example

22. Visualization Imagery Artistic design – Represent what? Artistic design – Represent what? “Simrealistic” – photorealistic data representations Simulate visually what results simulate mathematically Leverage the physical domain, existing visual paradigms Multiple perspectives and representations

23. Visualization Imagery Artistic design – Simrealistic imagery Artistic design – Simrealistic imagery An example

24. Visualization Imagery Conclusion Conclusion Reduce data-handling, avoid multiple steps Data to image – visualization shading Let the scientist stake out initial boundary Creative techniques and appeal “Simrealistic” imagery