A comprehensive campus-based approach to address the opportunities and challenges posed by data intensive research

James C. Wilgenbusch, Carla Bates, Lisa Johnston, Joshua A. Baller, Evan Bollig, Claudia Neuhauser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Faced with escalating expenses related to data storage needs and a capable set of on campus storage service providers, the University of Minnesota (UMN) developed a comprehensive framework to better address current and emerging challenges and opportunities brought by data intensive research. Elements of this framework and the process used to develop it could be applied at other research institutions to advance their efforts to address the challenges they face supporting data intensive science. While approaches may differ slightly, addressing these challenges within our respective universities is critical, and perhaps a prerequisite to building and sustaining partnerships among providers of advanced research computing and fully realizing the value of our data.

Original languageEnglish (US)
Title of host publicationProceedings of the Practice and Experience in Advanced Research Computing
Subtitle of host publicationRise of the Machines (Learning), PEARC 2019
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450372275
DOIs
StatePublished - Jul 28 2019
Event2019 Conference on Practice and Experience in Advanced Research Computing: Rise of the Machines (Learning), PEARC 2019 - Chicago, United States
Duration: Jul 28 2019Aug 1 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2019 Conference on Practice and Experience in Advanced Research Computing: Rise of the Machines (Learning), PEARC 2019
CountryUnited States
CityChicago
Period7/28/198/1/19

Bibliographical note

Funding Information:
Faced with escalating expenses related to data storage needs and a capable set of on campus storage service providers, the University of Minnesota (UMN) developed a comprehensive framework to better address current and emerging challenges and opportunities brought by data intensive research. Elements of this framework and the process used to develop it could be applied at other research institutions to advance their efforts to address the challenges they face supporting data intensive science. While approaches may differ slightly, addressing these challenges within our respective universities is critical, and perhaps a prerequisite to building and sustaining partnerships among providers of advanced research computing and fully realizing the value of our data. ACM proceedings Campus Planning Data Intensive Research Lessons Learned Storage Systems University Budgeting 1 James C. Wilgenbusch Author 2 Carla Bates Author 3 Lisa Johnston Author 4 Joshua A. Baller Author 5 Evan Bollig Author 6 Claudia Neuhauser Author 1 Gray, J. and Szalay, A. 2007. A Transformed Scientific Method. Presentation to the Computer Science and Technology Board of the National Research Council (Mountain View, CA, 2007). 2 Design Thinking: A Method for Creative Problem Solving: 2019. https://www.ideou.com/pages/design-thinking. Accessed: 2019-02-19. 3 New UMN council aims to better manage research data | The Minnesota Daily: https://www.mndaily.com/article/2018/05/h99atuieooqdqhg. Accessed: 2019-05-17. 4 A New Design for Managing the Deluge of Research Data: https://research.umn.edu/inquiry/post/new-design-managing-deluge-research-data. Accessed: 2019-05-17. 5 University Storage Council | IT@UMN: https://it.umn.edu/experts-communities/university-storage-council. Accessed: 2019-05-17. 6 Bottom, J., D. Atkins, A. Blatecky, R. McMullen, T. Tannenbaum, J. Cheetham, J. Wlgenbusch, K. Bhatia, E. Deumens, B. van Oehsen, G. Fox, M. Aiolkowski, A. Bedrossian, D. Fay. 2017. The Future of Cloud for Academic Research Computing. Results of an NSF-Supported Workshop, entitled "Cloud Forward" Supported by NSF ACI/CSE Award 1632037. 1 a89-Wilgenbusch.pdf ACM 2019 [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-] [-]

Keywords

  • ACM proceedings
  • Campus Planning
  • Data Intensive Research
  • Lessons Learned
  • Storage Systems
  • University Budgeting

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