1. 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 centers nationwide to help small manufacturers
Baldrige National Quality Award

2. 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

3. 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

4. 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

5. Information & Knowledge Management
Knowledge Development
Information
Information Synthesis
Data Collection

6. “...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

7. 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

8. 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, …

9. 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