Cherri Pancake NACSE (Oregon State University) pancake@nacse.org

1. The George E. Brown Jr. Network for Earthquake Engineering Simulation (NEES)How Cyberinfrastructure is Revolutionizing Earthquake Engineering Cherri Pancake NACSE (Oregon State University) pancake@nacse.org

2. Goal of NEES: Re-Engineer the Nature of EE • Extend national capacity for EE through new facilities • Unique large-scale physical experimentation • Integration of numerical and physical experiments • Integrate them with an IT infrastructure that • Captures and preserves all relevant information • Enables remote participation in real-time • Facilitates re-use of knowledge gained from experiments • Enhances effectiveness of EE researchers

3. Unique Laboratory Facilities Equipment Site 1 Earth.Eng. Researchers Equipment Site 2 Practitioners Equipment Site 3 Emergency Communities . . . Equipment Site 15 Other Site A User Communities Other Site B NEES: Distributed Resources and Users Data Repositories & Computational Resources NEES Consortium K-14 Education NEESgrid

4. NEES’s Complex, Distributed Organization • NEES, 2000-2004 • 17 projects, proposed and funded independently • 15 equipment sites: construct EE facilities • “System integration” team: develop NEESgrid • “Consortium development” team: create not-for-profit to manage system • NEES, 2004-2014 • NEES Consortium, Inc. will operate and manage • 15 equipment sites • Centralized data/network center • Distributed IT services at the sites

5. Focus: Exploit IT So Researchers Can… • Control and observe experiments from remote sites • Reduce requirement for on-site presence • Gain more from experiments • Exploit technology to enhance human observation • Share experiments with colleagues/students • Broaden participation in experiments • Extend useful lifetime of experimental processes • Exploit corpus of experiment results • Facilitate re-use of previous experimentation • Support integration of computational and experimental modeling

6. Telepresence: The Raw Ingredients • Sensor data: raw, filtered, graphical summaries • 10s to 100s of devices operating concurrently • Eventually must scale to 1000s of devices • Data streams from remotely operable cameras and microphones • 10s of devices at eye level, suspended from roof, and underwater • Includes some ultra high-resolution images • Use of computation to merge/analyze real-time data streams • Eventually will use simulation to “play what-if” and change course of experiment

7. Without attention to usability ... • Usability essentials: • Seamless synchronization of data streams • “Intelligent” choice of what to display • No requirement for user to download software • First experience “pays off” for later ones

8. Data Reuse: The Raw Ingredients • Extremely large quantities of data must be archived and made publicly available • Storage requirements for video/images will dwarf others • Diverse data formats must be integrated • Synchronization markers must be added • Most instruments have no concept of “time” • Metadata will be critical ingredient • Need to be standardized, but no appropriate standards exist • Must rely on EE researchers for much input • Must be possible to compare experimental data with data from simulations

9. Engineering NEES for Usability • 3 examples from the Tsunami Wave Basin • Experiment Design • Metadata Creation • Experiment Replay • Caveat: still in “early release” stage

10. Example 1: Experiment Design • Researchers shouldn’t have to visit site just to get familiar with it • Key needs • Learn about facility layout, capabilities • See details about equipment and instruments • Plan layout of models/specimens and instruments • Plan locations of cameras • Learn about setups that worked well for other researchers • Tsunami Wave Basin approach • Create accurate virtual model of lab • Animated walkthroughs for newcomers • Virtual lab tool for experiment design

11. Example 1: Experiment Design • Virtual wave basin is “better than being there” • See future facilities • Fly above scene • “Try out” positions • Study setups from past tests

12. Example 2: Metadata Creation • Metadata is critical to the NEES concepts of sharing and reuse • Key issues • Who defines the format? • Who creates the metadata for experiments? • What are the incentives for providing high-quality metadata? • Tsunami Wave Basin approach • Minimize the amount of metadata users must enter • Ensure that user is only entering metadata relevant to his/her role • Provide simple-to-use tools that catch as many potential errors as possible

13. generated automatically entered by lab tech entered by PI Where TWB Metadata Will Come From Metadata about sensor settings for a particular configuration position of sensor sensor calibrations sensor setup

14. Tsunami Analysis: Experimental and Numerical Modeling of Forces on a Vertical Surface Generated by a Solitary Wave by Karl T. Miller Project Supervisor: Daehyun Yoon Professor of Civil Engineering Supported by: National Science Foundation Award No. CMS-51234321 and George E. Brown, Jr., Network for Earthquake Engineering Simulation (NEES) Tsunami Wave Basin, Oregon State University  National Science Foundation Award No. CMS-0145332 Report No. KM-R-95 Carrot-and-Stick Approach • Stick • Users will be required to enter key metadata before experiment can begin • Part of agreement with PIs • Carrot • Metadata will be used to automatically generate lab reports • Previously, this was tediously done by hand We’re asking users to type minimal info ahead of time, rather than typing more after-the-fact

15. Example 3: Experiment Replay • Long-term archiving of experimental data is central to NEES • Key needs • Ability to understand what experimenter was trying to do • Access to all details of instrumentation and experiment design • Ability to accurately “replay” what happened • Ability to search data using fuzzy criteria, e.g. • Experiments with “similar results” • Experiments “like this one” • Tsunami Wave Basin approach • Search-and-query tool that “understands” experiments • Lab notebook style tool for viewing data • Easy downloading

16. Example 3: Experiment Replay • Lab notebook provides access to everything (even operator comments)

17. Lessons Learned – Biggest Challenges • First-ever IT infrastructure is central to NEES concept • Key challenges have to do with the human element • Diverse users • Broad range of skill sets and familiarity with advanced IT • Broad spectrum of needs • Little experience with data/facilities sharing • Extremely high expectations (!) • Ultimate success/failure rides on whether users can access facilities and data in ways that are • “Natural” • Useful • Safe

18. Recommendation 1:All projects should engage 3 key communities • IT experts • Knowledge of what is possible, how to exploit IT advances • Domain experts • Knowledge of current practice, what’s appropriate, pitfalls • Users • Understanding of priorities & what makes infrastructure usable IT experts Domain experts Research users Educational users Extrapolating to Cyberinfrastructure Cyberstructure is fundamentally a “human problem”

19. Lessons Learned – Priorities Are Key • NEES computer scientists put initial emphasis on IT challenges • Telepresence • Collaboration technology • Security • Earthquake engineers have made it clear that their priorities are the human challenges • Reliability • System must be “production-level” (not research product) • Data accessibility • Mechanisms must be flexible and useful for daily tasks • Usability • User doesn’t need special expertise or software

20. Extrapolating to Cyberinfrastructure Recommendation 2:All infrastructure should be developed with incremental roll-outs and reviews • Lots of projects to develop prototypes • Yield concepts & new technologies • Subset selected to proceed to initial deployment stage • Products useful to limited communities or domains • Chosen few are carried to full production stage • Robust, full-featured products for broad use