DATA The Legacy of NEES Shirley J Dyke

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

Oregon State 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 of California Los Angeles Rensselaer Polytechnic Institute University of California San Diego University of Nevada Reno University of Texas Austin Lehigh University

Outline Introduction The Legacy The Data The Challenges

NEES Facilities

Growing Community of NEES Researchers

NEEShub (@ nees. org)

NEEShub Execute remote software tools as if they were here N 3 DV launches on project X data View NEES project X N 3 DV screen is inserted in User’s web browser

The Legacy

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

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

The Legacy… The building codes that govern design procedures are grounded in experiments and the measurements that are acquired Often hundreds of tests are needed to convince the code committees to make changes

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

Real-time Monitoring Instrumenting the built & natural environments Courtesy of Jennifer Rice and Bill Spencer Courtesy of Luca Giacosa

Simulation of Systems Open tools ◦ multi-scale models ◦ hybrid simulation ◦ human systems

The Data

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!

The Data security has been the norm

The Data

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

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

Databases: Collections of Data

The Challenges

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

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

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

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

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

Thank you!

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. ”