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Standards

Frameworks

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Displaying 26 - 50 of 53

Using Simulation and Digital Twins to Innovate: Are We Getting Smarter?

December 15, 2021
Author(s)
Simon Taylor, Bjorn Johansson, Sumin Jeon, Loo Hay Lee, Peter Lendermann, Guodong Shao
Digital Twins have recently emerged as a major new area of innovation. Digital Twins are often found at the core of "smart" solutions that have also emerged as major areas of innovation. Modeling and Simulation (M&S) approaches create a model of a real

Ultraviolet Radiation Technologies and Healthcare Associated Infections: Standards and Metrology Needs

August 20, 2021
Author(s)
Dianne L. Poster, C Cameron Miller, Richard Martinello, Norman Horn, Michael T. Postek, Troy Cowan, Yaw S. Obeng, John J. Kasianowicz
The National Institute of Standards and Technology (NIST) hosted an international workshop on ultraviolet-C (UV-C) disinfection technologies on January 14 – 15, 2020 in Gaithersburg, Maryland in collaboration with the International Ultraviolet Association

A Novel Data Standards Platform using ISO Core Components Technical Specification

August 1, 2021
Author(s)
Nenad Ivezic, Boonserm Kulvatunyou, Elena Jelisic, Hakju Oh, Simon P. Frechette, Vijay Srinivasan
It is generally observed in inter-organizational communication that present-day data exchange standards are too costly and too complex to develop and use. These problems in data exchange are felt keenly by manufacturing industry with its vast supply chains

The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

November 12, 2020
Author(s)
Kamal Choudhary, Kevin Garrity, Andrew C. Reid, Brian DeCost, Adam Biacchi, Angela R. Hight Walker, Zachary Trautt, Jason Hattrick-Simpers, Aaron Kusne, Andrea Centrone, Albert Davydov, Francesca Tavazza, Jie Jiang, Ruth Pachter, Gowoon Cheon, Evan Reed, Ankit Agrawal, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei Kalinin, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, David Vanderbilt, Karin Rabe
The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques

FRAMEWORK FOR A DIGITAL TWIN IN MANUFACTURING

April 11, 2020
Author(s)
Guodong Shao, Moneer M. Helu
Digital twin has the potential to be an important technology for achieving smart manufacturing. However, there remains a lot of confusion about the concept and how it can be implemented in real manufacturing systems, especially among small-to-medium

EcoFAB: Advancing microbiome science through standardized fabricated ecosystems

June 21, 2019
Author(s)
Karsten Zengler, Kirsten Hofmockel, Scott Behie, Hans Bernstein, James Brown, Jos? Dinneny, Sheri Floge, Samuel Forry, Matthias Hess, Scott Jackson, Stephen Lindemann, Jennifer Pett-Ridge, Elizabeth Shank, Ophelia Venturelli, Matthew Wallenstein, Nitin Baliga, Christer Jansson, Trent Northen
Microbiome science is arguably the fastest-advancing research field in biology today. However, current efforts are largely focused on disparate and often irreproducible experimental systems. Here we present the results of a one-and-a-half-day workshop that

NIST Big Data Interoperability Framework: Volume 1, Big Data Definitions [Version 2]

June 26, 2018
Author(s)
Wo L. Chang, Nancy Grady, NBD-PWG NIST Big Data Public Working Group
Big Data is a term used to describe the large amount of data in the networked, digitized, sensor- laden, information-driven world. The growth of data is outpacing scientific and technological advances in data analytics. Opportunities exist with Big Data to

NIST Big Data Interoperability Framework: Volume 2, Big Data Taxonomies [Version 2]

June 26, 2018
Author(s)
Wo L. Chang, Nancy Grady, NBD-PWG NIST Big Data Public Working Group
Big Data is a term used to describe the large amount of data in the networked, digitized, sensor- laden, information-driven world. While opportunities exist with Big Data, the data can overwhelm traditional technical approaches and the growth of data is

NIST Big Data Interoperability Framework: Volume 9, Adoption and Modernization

June 26, 2018
Author(s)
Wo L. Chang, Russell Reinsch, NBD-PWG NIST Big Data Public Working Group
The potential for organizations to capture value from Big Data improves every day as the pace of the Big Data revolution continues to increase, but the level of value captured by companies deploying Big Data initiatives has not been equivalent across all

NIST Big Data Interoperability Framework: Volume 1, Big Data Definitions

October 22, 2015
Author(s)
Wo L. Chang, Nancy Grady, NBD-PWG NIST Big Data Public Working Group
Big Data is a term used to describe the large amount of data in the networked, digitized, sensor- laden, information-driven world. While opportunities exist with Big Data, the data can overwhelm traditional technical approaches and the growth of data is

NIST Big Data Interoperability Framework: Volume 2, Big Data Taxonomies

October 22, 2015
Author(s)
Wo L. Chang, Nancy Grady, Community Resilience Program NIST
Big Data is a term used to describe the large amount of data in the networked, digitized, sensor- laden, information-driven world. While opportunities exist with Big Data, the data can overwhelm traditional technical approaches and the growth of data is

NIST Big Data Interoperability Framework: Volume 3, Use Cases and General Requirements

October 22, 2015
Author(s)
Wo L. Chang, Geoffrey Fox, NBD-PWG NIST Big Data Public Working Group
Big Data is a term used to describe the large amount of data in the networked, digitized, sensor-laden, information-driven world. While opportunities exist with Big Data, the data can overwhelm traditional technical approaches and the growth of data is

NIST Big Data Interoperability Framework: Volume 4, Security and Privacy

October 22, 2015
Author(s)
Wo L. Chang, Arnab Roy, Mark Underwood, NBD-PWG NIST Big Data Public Working Group
Big Data is a term used to describe the large amount of data in the networked, digitized, sensor-laden, information-driven world. While opportunities exist with Big Data, the data can overwhelm traditional technical approaches and the growth of data is
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