1. AMIT CHOURASIA VISUALIZATION SCIENTIST VISUALIZATION SERVICES SAN DIEGO SUPERCOMPUTER CENTER PRESENTED AT : NEES 5 TH ANNUAL MEETING, JUN 20 TH SNOWBIRD UTAH Shake Table Data Visualization

2. Data Source 2 Observed: Sensors (600 channels) Data Attributes Time varying Multivariate Heterogeneous Original Footage

3. Study Goal 3 Integrate the observed data into visual domain Asses the requirements and applicability to Structural Engineering Demonstrate such a system to Structural Engineers Disseminate information about the state-of-the-art research in structural engineering

4. Motivation: Understanding Data 4 Large amount of numbers don’t make much sense to humans Visual information can encode large amount of numbers to gain insight Low Bandwidth High Bandwidth

5. Quest for Visual Representation 5 Desirable Attributes Intuitive (trainable) Highlights feature of interest Color: Perceptual or Rainbow style? Compact Unambiguous

6. Dirty Data Issues 6 Data comprised of 117 channels 5000+ timesteps @ 50 hz ~ 100 sec Data Formating and Translation

7. 3D Model 7 Movie: 3d Model

8. Deformation Model 8 Movie: Deformation

9. Renderings 9 Original videoCombinedPerspective npr

10. Camera Match 10 MatchCheck Match

11. Lessons Learned 11 The visual system should include the capability of real-time interaction with deformation of a textured 3D model; incorporate contextual elements when possible; represent sensor locations and properties Animation packages can be successfully utilized for scientific visualization. They are flexible and extensible for quick prototyping. The visual results are highly realistic with high fidelity. Proper registration of data and metadata is important. Without registration, features like camera matching and compositing can be guesswork at best. Matching environmental light is still a challenge. The visualized results are valuable tools for dissemination of information and suitable for both a broader scientific and non-scientific community.

12. Visualization Issues 12 Domain knowledge Multivariate data representation Temporal coherence Precision Loss (compression, etc…) Interaction vs. batch Perceptual Issues Personal Bias (author & viewer)

13. Video Recap 13

14. Acknowledgements 14 Steve Cutchin Mike Rossmasler (Viz Intern) Ruben Soto-Alcauter (NEES-IT Intern) Andrew Collier (NEES-IT Intern) Jose Restrepo Marios Panagiotou Lelli Van Den Einde Anke Kamrath Study was funded by SDSC

15. WEB: HTTP://VISSERVICES.SDSC.EDU/HTTP://VISSERVICES.SDSC.EDU/ REFERENCE: CHOURASIA, A. (2007) “DIGITAL RECREATION OF A SEVEN STORY BUILDING SHAKE DURING AN EARTHQUAKE”, ACM CROSSROADS, 13-3, 2007 15 Thanks for your patience ? -