National Institute of Standards and Technology NIST … is an agency in the Technology Administration of the US Department of Commerce. NIST Assets Include: 3,000 employees 1,600 guest researchers $760 million annual budget NIST Laboratories -- National measurement standards - $400 million budget Advanced Technology Program -- $570 million current R&D partnerships with industry Manufacturing Extension Partnership -- 400 centers nationwide to help small manufacturers Baldrige National Quality Award

NIST Laboratories The NIST laboratories provide measurements, standards, and data to U.S. industry to improve competitiveness and build the technology infrastructure. One of the major activities at NIST these days involves strategic planning to plan for the future. We see changes in the R&D and business climates in the US, as well as a shifting demand in NIST expertise form more traditional disciplines to much more multi-disciplinary activities. This is placing strong demands on better and more efficient management of our resources and programs. Focusing Technical Work for Maximum Impact Fewer, larger projects aligned to highest impact areas Strategic planning - changing demands on NIST Leverage resources through external partnerships Utilize unique capabilities outside of NIST to deliver service Work with private sector to develop NIST reference materials Tele-calibration - utilize internet to deliver NIST Services Develop strategic partnerships Measure Impact – Manage for Results Peer review, Customer feedback Analyze economic impact data Track outputs SRMs, Calibrations, technical standards, etc. Focussed NIST 2010 Strategic Planning: External Scan Increased Impact of NIST Programs through better alignment to industry needs Program management vs. project management knowledgeNET NILO/Mirror Function External Partnerships include: External Unique capabilities: step gauge calibrations at Oak Ridge, HIGH flow rate calibrations at Colorado Experimental Engineering Station, Inc. (Reynolds number ~100,000) this last facility would cost $Ms to replicate at NIST. Private Sector Involvement in Reference Material Manufacturing: NTRM Program to deliver NIST Tracable Materials using private sector manufacturers, most major gas manufacturers participate. Tele-Calibrations and Services: Radiation Dose Calibrations done on on-line, remote calibration of high-dose radiation sources against the U.S. national standard via the Internet; offering NIST customers (primarily industry) on-demand calibrations in real time at drastically reduced costs; improving quality of U.S. irradiation processing through expanded coverage digital multimeter (DMM) test service by developing a new Internet-based service to provide traceability for customers’ multifunction calibrators; establishing a web-accessible database for test customers with procedures, software, historical data, and test reports; and providing Internet-based technical assessment for laboratory accreditation. Internet-based collaboration in weld cell programming, remote welding, and process monitoring; and developing improved process models for gas metal arc welding. Strategic Partnerships: e.g. external funding of organic synthesis in molecular electronics research Measurement of Impact: BoA Cross-Cuts, Sematech Scorecard Economic Impact Data Closer Tracking of Calibrations

CSTL/NIST Goals Chemical and Process Information Measurement Standards Establish CSTL as the pinnacle of the national traceability and international comparability structure for measurements in chemistry, chemical engineering and biotechnology, and provide the fundamental basis of the nation’s measurement system Chemical and Process Information Assure that U.S. industry has access to accurate and reliable data and predictive models to determine the chemical and physical properties of materials and processes Measurement Science Anticipate and address next generation measurement needs of the nation, by performing cutting-edge research NIST’s overarching goal is to maximize our impact through: Improvements in productivity Increased access to markets Expanded public benefit through measurements and standards

Growth in monthly use Chemistry WebBook Explosive growth in the need for reliable physical, chemical, biochemical, and materials property data to support process and product optimization and discovery. combinatorial methods high throughput experimentation doubling of the volume of published thermodynamic data in the last 10 yrs 7/1996 Growth in monthly use Chemistry WebBook Millions of Pages 1/2003

Information & Knowledge Management Knowledge Development Information Information Synthesis Data Collection

“...critically evaluated data on well-characterized substances...” Reliable Data Information Reliable Data suitably documented established uncertainty first step in the creation of information core of NIST mission “...critically evaluated data on well-characterized substances...” Standard Reference Data Act

Trustworthy information “on-demand”: data collection autonomous input at publication federation of data archives world-wide data management metadata, uncertainty, provenance data mining data evaluation – best value, “self-improving” archives expert systems comprehensive archives non-linear, multi-variate, constrained, statistical optimization self-consistent, reflexive annotation of uncertainty “virtual measurements” first principles computations

PrIMe – Process Informatics in a Community Collaboration for the Development of Combustion Models Needs reliable hardware modern data-management tools sustained experimental data collection and evaluation scientific tools for mechanism generation, model reduction, dataset analysis, …

Challenges 100’s gigabytes - federated world-wide semantics & syntax – legacy mirror archives or only query federation? real-time access to comprehensive archive non-standard, legacy database schema non-standard or non-existent provenance quality measures and annotation metadata update upon evaluation enable dynamic self-consistency computation in a distributed environment architectures for “on-demand” first principles computational estimation