Amit Chourasia Visualization Scientist Visualization Services Presented at : SCEC-CME All Hands Meeting Jun 2006 Scientific Visualization in Seismology
Viz Highlights – Terashake2.1 Movie
Colored SA Maps
Self Contoured SA Maps
Prototype SCEC Viz portal
Current Work “Earthworks effort” -Viz on demand through web On the fly viz
Past Work SCEC data used for IEEE Vis 2006 contest Cover for GRL Movies being used in Teacher Training Movies part of National Geographic’s Documentary Movies shown at TV/Internet News Movies shown at key meetings/conferences...
Insight? Purpose of Visualization is insight But, what exactly is insight? How can it be measured? Ref: North. C., Towards measuring Visualization Insight, CGA, May/June 2006 Some important characteristics of Insight are Complex Deep Qualitative Unexpected Relevant
Lets take a look at Insight Complex - involving all or large amounts of data in a synergistic way, not simple data values. (Whittier Narrows effect) Deep – it builds up over time, accumulating and building up on itself to create depth. It often generates further questions. (Movie stack for different simulations, comparison movies) Qualitative – is not exact, can be uncertain and subjective, and can have multiple levels of resolution. (Input wave super shear) Unexpected – is often unpredictable, serendipitous and creative. (Sun bursts patterns, reflection in ocean) Relevant – is deeply embedded in the data domain, connecting the data to existing domain knowledge and giving relevant meaning. It goes beyond dry analysis, to relevant domain impact. (Coupling surface information like fault lines, freeways, topography, etc)
Our Focus Enable science through visualization
Collaboration What is missing ? What are features of interest ? How can features be extracted ? Tell us your visual interpretations and conceptions of simulations.
Software Tools Vista (SDSC/NPACI) Mesh Viewer (SDSC/NPACI) DeskVox Autodesk’s Maya & Image Studio Adobe’s suite (After Effects, Photoshop, Illustrator) Other tools that’ll work
Simulations What happens ? Where ( Place + Time) ? How it happens ? Why? Visualization Science Monitering-On the Fly Diagnosis after completion
Future Directions Visualization Monitering Diagnosis / Analysis Feature Driven Multivariate Replicable Quick Integrated Web based? Automated Caution: What is left out? What is distilled? Ensure detail and significant features are not lost.
People Visualization Services Steve Cutchin Alex Decastro Amit Chourasia Patrick Yau (Former Intern)
Hope you are still awake! ?- Drop a line: amit sdsc.edu