Investigating Data Reusability in Density Functional Theory Studies

Rob Fleur; Addy Ireland; Xintong Zhao; Scott McClellan; Eric Paltoo; Tianyu Su; Channyung Lee; Yuan An; Xiaohua Hu; Elif Ertekin; Jane Greenberg

doi:10.1109/BigData59044.2023.10386967

2023 IEEE International Conference on Big Data (BigData)

Investigating Data Reusability in Density Functional Theory Studies

Year: 2023, Pages: 6143-6144

DOI Bookmark: 10.1109/BigData59044.2023.10386967

Authors

Rob Fleur, Drexel University,Metadata Research Center,Philadelphia,USA
Addy Ireland, Drexel University,Metadata Research Center,Philadelphia,USA
Xintong Zhao, Drexel University,Metadata Research Center,Philadelphia,USA
Scott McClellan, Drexel University,Metadata Research Center,Philadelphia,USA
Eric Paltoo, Drexel University,Metadata Research Center,Philadelphia,USA
Tianyu Su, University of Illinois at Urbana-Champaign,Mechanical Science and Engineering,Urbana,USA
Channyung Lee, University of Illinois at Urbana-Champaign,Mechanical Science and Engineering,Urbana,USA
Yuan An, Drexel University,Metadata Research Center,Philadelphia,USA
Xiaohua Hu, Drexel University,Metadata Research Center,Philadelphia,USA
Elif Ertekin, University of Illinois at Urbana-Champaign,Mechanical Science and Engineering,Urbana,USA
Jane Greenberg, Drexel University,Metadata Research Center,Philadelphia,USA

Abstract

Over the last decade, there has been a significant increase in supporting reproducible computational research (RCR) [1]. The global adoption of the FAIR principles [2] stands as a key indicator of this trend. Specifically, federal and global research funding agencies have increasingly mandated scientific data and related products, such as code and algorithms, be made Findable, Accessible, Interoperable, and Reusable (FAIR) [2].

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Investigating Data Reusability in Density Functional Theory Studies

Authors

Abstract

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