Zobrazeno 1 - 10
of 81
pro vyhledávání: '"Robert J. Hanisch"'
Autor:
Angela Y. Lee, Cedric J. Powell, Justin M. Gorham, Adam Morey, John Henry J. Scott, Robert J. Hanisch
Publikováno v:
Data Science Journal, Vol 23, Pp 45-45 (2024)
It has been over 20 years since the National Institute of Standards and Technology (NIST) launched the first web version of its X-ray Photoelectron Spectroscopy (XPS) database (Lee et al., 2002; Wagner, 1991) which has approximately 1000 active users
Externí odkaz:
https://doaj.org/article/8995b62d67bf4d73bb032b6a764b8799
Now Is the Time to Build a National Data Ecosystem for Materials Science and Chemistry Research Data
Publikováno v:
ACS Omega, Vol 7, Iss 16, Pp 13398-13402 (2022)
Externí odkaz:
https://doaj.org/article/70c45c919ebb4386b7ee5bd44a141d66
Autor:
Raymond L. Plante, Chandler A. Becker, Andrea Medina-Smith, Kevin Brady, Alden Dima, Benjamin Long, Laura M. Bartolo, James A. Warren, Robert J. Hanisch
Publikováno v:
Data Science Journal, Vol 20, Iss 1 (2021)
As a result of a number of national initiatives, we are seeing rapid growth in the data important to materials science that are available over the web. Consequently, it is becoming increasingly difficult for researchers to learn what data are availab
Externí odkaz:
https://doaj.org/article/26777726d60d42688294268e19962359
Autor:
Andrea Medina-Smith, Chandler A. Becker, Raymond L. Plante, Laura M. Bartolo, Alden Dima, James A. Warren, Robert J. Hanisch
Publikováno v:
Data Science Journal, Vol 20, Iss 1 (2021)
The International Materials Resource Registries (IMRR) working group of the Research Data Alliance (RDA) was created to spur initial development of a federated registry system to allow for easier discovery and access to materials data. As part of thi
Externí odkaz:
https://doaj.org/article/e173a6aa658a49f3a5492a5c95b7646c
Autor:
Nicholas Petrick, Marisa Cruz, Krishna Kandarpa, Ronald M. Summers, Tarik K. Alkasab, Steven E. Seltzer, Bibb Allen, Danica Marinac-Dabic, Judy Burleson, Robert J. Hanisch, Curtis P. Langlotz, Kevin Lyman, Keith P. Dreyer, Wendy Nilsen
Publikováno v:
Journal of the American College of Radiology. 16:1179-1189
Advances in machine learning in medical imaging are occurring at a rapid pace in research laboratories both at academic institutions and in industry. Important artificial intelligence (AI) tools for diagnostic imaging include algorithms for disease d
Autor:
Raymond Plante, Andrea M. Medina-Smith, Robert J. Hanisch, Alden Dima, James A. Warren, Laura M. Bartolo, Chandler A. Becker
Publikováno v:
Data Science Journal, Vol 20, Iss 1 (2021)
Data Science Journal; Vol 20 (2021); 18
Data Science Journal; Vol 20 (2021); 18
The International Materials Resource Registries (IMRR) working group of the Research Data Alliance (RDA) was created to spur initial development of a federated registry system to allow for easier discovery and access to materials data. As part of thi
In the past decade, numerous public and private sector documents have highlighted the need for materials data to facilitate advanced technologies in myriad industrial and economic sectors. These documents have been analyzed to identify prevalent gaps
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a3354dda2d783a511467a62a405ab19f
https://doi.org/10.6028/nist.ir.8364
https://doi.org/10.6028/nist.ir.8364
NIST is leading the development of the Research Data Framework (RDaF) with involvement and input from national and international leaders in the broad research data stakeholder community. Research data is defined here as the recorded factual material
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6cf7e6f342b5232ccd1adb10f1f45694
https://doi.org/10.6028/nist.sp.1500-18
https://doi.org/10.6028/nist.sp.1500-18
Autor:
Chandler A. Becker, Alden Dima, James A. Warren, Kevin G. Brady, Laura M. Bartolo, Raymond Plante, Robert J. Hanisch, Andrea M. Medina-Smith, Benjamin Long
Publikováno v:
Data science journal
Data Science Journal; Vol 20 (2021); 15
Data Science Journal, Vol 20, Iss 1 (2021)
Data Science Journal; Vol 20 (2021); 15
Data Science Journal, Vol 20, Iss 1 (2021)
As a result of a number of national initiatives, we are seeing rapid growth in the data important to materials science that are available over the web. Consequently, it is becoming increasingly difficult for researchers to learn what data are availab
Autor:
Anne L. Plant, Robert J. Hanisch
Publikováno v:
Issue 2.4, Fall 2020. 2
Scientific progress requires the ability of scientists to build on the results produced by those who preceded them. Because of this, there is concern that irreproducible scientific results are being reported. We suggest that while reproducibility can