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Title: Data-driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities

Abstract

Data-driven science and technology have helped achieve meaningful results in areas such as materials/drug discovery and health care, but efforts to apply high-end data science algorithms to the areas of glass and ceramics are still limited. Many glass and ceramic researchers are interested in enhancing their work by using more data and data analytics to efficiently develop better functional materials. Simultaneously, the data science community is looking for a way to access materials data resources to test and validate their advanced computational learning algorithms. To bring together the glass/ceramic and data science communities to address this issue, The American Ceramic Society (ACerS) convened a Glass/Ceramics Data Science Workshop on February 6, 2018, at Nexight Group offices in Silver Spring, Maryland. The workshop, sponsored by the National Institute for Standards and Technology (NIST) Advanced Manufacturing Technologies (AMTech) program, brought together a select group of 20 key leaders in the data science, informatics, and glass/ceramics communities to identify the greatest opportunities and mechanisms for facilitating increased collaboration and coordination between these communities. This article summarizes workshop discussions about the current challenges that limit interactions and collaboration between the glass/ceramic and data science communities, opportunities for a coordinated approach that leverages existing knowledgemore » in both communities, and a clear path toward the enhanced use of data science technologies for functional glass and ceramic research and development.« less

Authors:
 [1];  [2];  [3]; ORCiD logo [4];  [5];  [6];  [7];  [8];  [9];  [10];  [3];  [6];  [11];  [1];  [12];  [13];  [9];  [11];  [1];  [3] more »;  [14];  [15];  [16] « less
  1. The American Ceramic Society
  2. Kent State University
  3. Nexight Group
  4. BATTELLE (PACIFIC NW LAB)
  5. North Carolina State University
  6. IBM
  7. DuPont Central Research
  8. Schott
  9. Lehigh University
  10. Oak Ridge National Laboratory
  11. Pennsylvania State University
  12. Citrine IO
  13. Iowa State University
  14. Corning
  15. University of Chicago
  16. Materials Development, Inc.
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1572500
Report Number(s):
PNNL-SA-136773
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Journal of the American Ceramic Society
Additional Journal Information:
Journal Volume: 102; Journal Issue: 11
Country of Publication:
United States
Language:
English
Subject:
data science, ceramics, informatics

Citation Formats

Deguire, Eileen, Bartolo, Laura, Brindle, Ross, Devanathan, Ram, Dickey, Elizabeth, Fessler, Justin, French, Roger H., Fotheringham, Ulrich, Harmer, Martin P., Lara-Curzio, Edgar, Lichtner, Sara, Maillet, Emmanuel, Mauro, John, Mecklenborg, Mark, Meredig, Bryce, Rajan, Krishna, Rickman, Jeffrey M., Sinnott, Susan B., Spahr, Charlie, Suh, Changwon, Tandia, Adama, Ward, Logan, and Weber, Richard. Data-driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities. United States: N. p., 2019. Web. doi:10.1111/jace.16677.
Deguire, Eileen, Bartolo, Laura, Brindle, Ross, Devanathan, Ram, Dickey, Elizabeth, Fessler, Justin, French, Roger H., Fotheringham, Ulrich, Harmer, Martin P., Lara-Curzio, Edgar, Lichtner, Sara, Maillet, Emmanuel, Mauro, John, Mecklenborg, Mark, Meredig, Bryce, Rajan, Krishna, Rickman, Jeffrey M., Sinnott, Susan B., Spahr, Charlie, Suh, Changwon, Tandia, Adama, Ward, Logan, & Weber, Richard. Data-driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities. United States. https://doi.org/10.1111/jace.16677
Deguire, Eileen, Bartolo, Laura, Brindle, Ross, Devanathan, Ram, Dickey, Elizabeth, Fessler, Justin, French, Roger H., Fotheringham, Ulrich, Harmer, Martin P., Lara-Curzio, Edgar, Lichtner, Sara, Maillet, Emmanuel, Mauro, John, Mecklenborg, Mark, Meredig, Bryce, Rajan, Krishna, Rickman, Jeffrey M., Sinnott, Susan B., Spahr, Charlie, Suh, Changwon, Tandia, Adama, Ward, Logan, and Weber, Richard. 2019. "Data-driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities". United States. https://doi.org/10.1111/jace.16677.
@article{osti_1572500,
title = {Data-driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities},
author = {Deguire, Eileen and Bartolo, Laura and Brindle, Ross and Devanathan, Ram and Dickey, Elizabeth and Fessler, Justin and French, Roger H. and Fotheringham, Ulrich and Harmer, Martin P. and Lara-Curzio, Edgar and Lichtner, Sara and Maillet, Emmanuel and Mauro, John and Mecklenborg, Mark and Meredig, Bryce and Rajan, Krishna and Rickman, Jeffrey M. and Sinnott, Susan B. and Spahr, Charlie and Suh, Changwon and Tandia, Adama and Ward, Logan and Weber, Richard},
abstractNote = {Data-driven science and technology have helped achieve meaningful results in areas such as materials/drug discovery and health care, but efforts to apply high-end data science algorithms to the areas of glass and ceramics are still limited. Many glass and ceramic researchers are interested in enhancing their work by using more data and data analytics to efficiently develop better functional materials. Simultaneously, the data science community is looking for a way to access materials data resources to test and validate their advanced computational learning algorithms. To bring together the glass/ceramic and data science communities to address this issue, The American Ceramic Society (ACerS) convened a Glass/Ceramics Data Science Workshop on February 6, 2018, at Nexight Group offices in Silver Spring, Maryland. The workshop, sponsored by the National Institute for Standards and Technology (NIST) Advanced Manufacturing Technologies (AMTech) program, brought together a select group of 20 key leaders in the data science, informatics, and glass/ceramics communities to identify the greatest opportunities and mechanisms for facilitating increased collaboration and coordination between these communities. This article summarizes workshop discussions about the current challenges that limit interactions and collaboration between the glass/ceramic and data science communities, opportunities for a coordinated approach that leverages existing knowledge in both communities, and a clear path toward the enhanced use of data science technologies for functional glass and ceramic research and development.},
doi = {10.1111/jace.16677},
url = {https://www.osti.gov/biblio/1572500}, journal = {Journal of the American Ceramic Society},
number = 11,
volume = 102,
place = {United States},
year = {2019},
month = {11}
}

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