Smoky mountain data challenge 2020: An open call to solve data problems in the areas of neutron science, material science, urban modeling and dynamics, geophysics, and biomedical informatics

Suzanne Parete-Koon; Peter F. Peterson; Garrett E. Granroth; Wenduo Zhou; Pravallika Devineni; Nouamane Laanait; Junqi Yin; Albina Borisevich; Ketan Maheshwari; Melissa Allen-Dumas; Srinath Ravulaparthy; Kuldeep Kurte; Jibo Sanyal; Anne Berres; Olivera Kotevska; Folami Alamudun; Keith Gray; Max Grossman; Anar Yusifov; Ioana Danciu; Gil Alterovitz; Dasha Herrmannova

doi:10.1007/978-3-030-63393-6_28

Smoky mountain data challenge 2020: An open call to solve data problems in the areas of neutron science, material science, urban modeling and dynamics, geophysics, and biomedical informatics

Suzanne Parete-Koon, Peter F. Peterson, Garrett E. Granroth, Wenduo Zhou, Pravallika Devineni, Nouamane Laanait, Junqi Yin, Albina Borisevich, Ketan Maheshwari, Melissa Allen-Dumas, Srinath Ravulaparthy, Kuldeep Kurte, Jibo Sanyal, Anne Berres, Olivera Kotevska, Folami Alamudun, Keith Gray, Max Grossman, Anar Yusifov, Ioana DanciuGil Alterovitz, Dasha Herrmannova

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The 2020 Smoky Mountains Computational Sciences and Engineering Conference enlists research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. This work describes the significance of each of the seven data sets and their associated challenge questions. The challenge questions for each data set were required to cover multiple difficulty levels. An international call for participation was sent to students, and researchers asking them to form teams of up to four people to apply novel data analytics techniques to these data sets.

Original language	English
Title of host publication	Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI - 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Revised Selected Papers
Editors	Jeffrey Nichols, Arthur ‘Barney’ Maccabe, Suzanne Parete-Koon, Becky Verastegui, Oscar Hernandez, Theresa Ahearn
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	425-442
Number of pages	18
ISBN (Print)	9783030633929
DOIs	https://doi.org/10.1007/978-3-030-63393-6_28
State	Published - 2021
Event	17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020 - Virtual, Online Duration: Aug 26 2020 → Aug 28 2020

Publication series

Name	Communications in Computer and Information Science
Volume	1315 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020
City	Virtual, Online
Period	08/26/20 → 08/28/20

Funding

Acknowledgments. This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725” This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. S. Parete-Koon et al.—Contributed Equally. This manuscript has been co-authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy. gov/downloads/doe-public-access-plan).

Keywords

Artificial intelligence
Data analytics
Machine learning

Access to Document

10.1007/978-3-030-63393-6_28

Cite this

Parete-Koon, S., Peterson, P. F., Granroth, G. E., Zhou, W., Devineni, P., Laanait, N., Yin, J., Borisevich, A., Maheshwari, K., Allen-Dumas, M., Ravulaparthy, S., Kurte, K., Sanyal, J., Berres, A., Kotevska, O., Alamudun, F., Gray, K., Grossman, M., Yusifov, A., ... Herrmannova, D. (2021). Smoky mountain data challenge 2020: An open call to solve data problems in the areas of neutron science, material science, urban modeling and dynamics, geophysics, and biomedical informatics. In J. Nichols, A. B. Maccabe, S. Parete-Koon, B. Verastegui, O. Hernandez, & T. Ahearn (Eds.), Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI - 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Revised Selected Papers (pp. 425-442). (Communications in Computer and Information Science; Vol. 1315 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-63393-6_28

Parete-Koon, Suzanne ; Peterson, Peter F. ; Granroth, Garrett E. et al. / Smoky mountain data challenge 2020 : An open call to solve data problems in the areas of neutron science, material science, urban modeling and dynamics, geophysics, and biomedical informatics. Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI - 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Revised Selected Papers. editor / Jeffrey Nichols ; Arthur ‘Barney’ Maccabe ; Suzanne Parete-Koon ; Becky Verastegui ; Oscar Hernandez ; Theresa Ahearn. Springer Science and Business Media Deutschland GmbH, 2021. pp. 425-442 (Communications in Computer and Information Science).

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abstract = "The 2020 Smoky Mountains Computational Sciences and Engineering Conference enlists research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. This work describes the significance of each of the seven data sets and their associated challenge questions. The challenge questions for each data set were required to cover multiple difficulty levels. An international call for participation was sent to students, and researchers asking them to form teams of up to four people to apply novel data analytics techniques to these data sets.",

keywords = "Artificial intelligence, Data analytics, Machine learning",

author = "Suzanne Parete-Koon and Peterson, {Peter F.} and Granroth, {Garrett E.} and Wenduo Zhou and Pravallika Devineni and Nouamane Laanait and Junqi Yin and Albina Borisevich and Ketan Maheshwari and Melissa Allen-Dumas and Srinath Ravulaparthy and Kuldeep Kurte and Jibo Sanyal and Anne Berres and Olivera Kotevska and Folami Alamudun and Keith Gray and Max Grossman and Anar Yusifov and Ioana Danciu and Gil Alterovitz and Dasha Herrmannova",

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year = "2021",

doi = "10.1007/978-3-030-63393-6_28",

language = "English",

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series = "Communications in Computer and Information Science",

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booktitle = "Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI - 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Revised Selected Papers",

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Parete-Koon, S , Peterson, PF , Granroth, GE, Zhou, W, Devineni, P, Laanait, N, Yin, J , Borisevich, A , Maheshwari, K , Allen-Dumas, M, Ravulaparthy, S, Kurte, K, Sanyal, J, Berres, A, Kotevska, O, Alamudun, F, Gray, K, Grossman, M, Yusifov, A, Danciu, I, Alterovitz, G & Herrmannova, D 2021, Smoky mountain data challenge 2020: An open call to solve data problems in the areas of neutron science, material science, urban modeling and dynamics, geophysics, and biomedical informatics. in J Nichols, AB Maccabe, S Parete-Koon, B Verastegui, O Hernandez & T Ahearn (eds), Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI - 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Revised Selected Papers. Communications in Computer and Information Science, vol. 1315 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 425-442, 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Virtual, Online, 08/26/20. https://doi.org/10.1007/978-3-030-63393-6_28

Smoky mountain data challenge 2020: An open call to solve data problems in the areas of neutron science, material science, urban modeling and dynamics, geophysics, and biomedical informatics. / Parete-Koon, Suzanne ; Peterson, Peter F.; Granroth, Garrett E. et al.
Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI - 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Revised Selected Papers. ed. / Jeffrey Nichols; Arthur ‘Barney’ Maccabe; Suzanne Parete-Koon; Becky Verastegui; Oscar Hernandez; Theresa Ahearn. Springer Science and Business Media Deutschland GmbH, 2021. p. 425-442 (Communications in Computer and Information Science; Vol. 1315 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Borisevich, Albina

AU - Maheshwari, Ketan

AU - Allen-Dumas, Melissa

AU - Ravulaparthy, Srinath

AU - Kurte, Kuldeep

AU - Sanyal, Jibo

AU - Berres, Anne

AU - Kotevska, Olivera

AU - Alamudun, Folami

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AB - The 2020 Smoky Mountains Computational Sciences and Engineering Conference enlists research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. This work describes the significance of each of the seven data sets and their associated challenge questions. The challenge questions for each data set were required to cover multiple difficulty levels. An international call for participation was sent to students, and researchers asking them to form teams of up to four people to apply novel data analytics techniques to these data sets.

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SN - 9783030633929

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Parete-Koon S , Peterson PF , Granroth GE, Zhou W, Devineni P, Laanait N et al. Smoky mountain data challenge 2020: An open call to solve data problems in the areas of neutron science, material science, urban modeling and dynamics, geophysics, and biomedical informatics. In Nichols J, Maccabe AB, Parete-Koon S, Verastegui B, Hernandez O, Ahearn T, editors, Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI - 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2021. p. 425-442. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-63393-6_28

Smoky mountain data challenge 2020: An open call to solve data problems in the areas of neutron science, material science, urban modeling and dynamics, geophysics, and biomedical informatics

Abstract

Publication series

Conference

Funding

Keywords

Access to Document

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