DATA: The Legacy of NEES

1. DATA: The Legacy of NEES Shirley J. Dyke NEEScomm Center, Purdue University Professor of Mechanical Engineering Professor of Civil Engineering

2. Oregon State University University of Minnesota University of Illinois- Urbana University of California Berkeley University of California Davis http://nees.org University of Buffalo University of California Santa Barbara Cornell University University of California Los Angeles Rensselaer Polytechnic Institute University of Texas Austin University of Nevada Reno University of California San Diego Lehigh University

3. Outline • Introduction • The Legacy • The Data • The Challenges

4. NEES Facilities

5. Growing Community ofNEES Researchers

6. NEEShub (@ nees.org)

7. NEEShub Execute remote software tools as if they were here N3DV launches on project X data N3DV screen is inserted in User’s web browser View NEES project X

8. The Legacy

9. The Legacy… • Each experiment and simulation performed constitutes an opportunity for us as a community to gain insight and reduce risk. • A data repository populated with high quality data is certain to be a valuable resource for the earthquake engineering community. • Data reuse must be available

10. The Legacy… • Data from experiments and real-world systems provide information for improving modeling capabilities

11. The Legacy… • The building codes that governdesign procedures aregrounded in experiments and the measurements thatare acquired • Often hundreds of tests areneeded to convince the codecommittees to make changes

12. 2020 Vision State-of-art capabilities to support innovative testing, data preservation, and collaboration Cyberinfrastructure resources to support the data structures and visualization methods Improved data collection and information management capabilities

13. Real-time Monitoring • Instrumenting the built & natural environments Courtesy of Jennifer Riceand Bill Spencer Courtesy of Luca Giacosa

14. Simulation of Systems • Open tools • multi-scale models • hybrid simulation • human systems

15. The Data

16. The Broad User Community • Researchers • Practicing Engineers (designers) • Educators • IT Managers • Public-at-Large Each user category has different ways to and reasons for using data!

17. The Data • Data security has been the norm

18. The Data

19. The Data • Measurement data from 1-1000 sensors • 1MB to 1GB • Multiple simultaneous records • 1-10,000 files per project, so far • Images from experiments • Video captured during experiments • Specimen information

20. The Data • Metadata • Testing conditions • Configurations • Sensor descriptions • Annotations about data • Model generation and analysis codes • Analysis tools developed during research

21. Databases: Collections of Data

22. The Challenges

23. Challenges – Manager • The managing organization must deliver the tools for robust and versatile ingestion, storage, curation, visualization of these data. • The data repository must provide • Quality data • Sharing capability • Standards • Security • Provenance • Training

24. Challenges – Users • Sharing and preservation are not in the culture • Sites provide initial data upload within 48 hours • Much time and effort is required to enter metadata • Research teams have 12 months to use the data before it is released publically • Occasional confidentiality issues, no privacy issues

25. Challenges - Users • Recognition of project data as a scholarly contribution • Ensuring proper citations to the data generator

26. Challenges - Community • Policies will enforce data sharing, but this is a “stick” and we are working on the “carrot” • Community requires training in • Data model • Making data accessible • Standards and methods for data archiving • Data preservation

27. Challenges - Community • International • Language • Standards • Culture • Distance • Japan (largest shake table in the world) • China • Korea • European Union • Data bring us all together

28. Thank you!

29. Challenges – of the Future • To achieve the 2020 Vision “Cyberinfrastructure that will facilitate data collection and management to enable rapid and efficient access and distribution of experimental and simulated data is essential.”