e-Science at the                  University of Minnesota                                e-Science Symposium              ...
History, Evolution & Current State • Present my experiences as a researcher and show   how changes in research call for th...
First, Let’s Agree… • E-Science (or eScience) is computationally   intensive scientific research, typically   performed ov...
E-Science • …has often been called cyberinfrastructure in   the U.S. • Nowadays, cyberinfrastructure is used less (at   le...
Technology is the Major Impact on Science                                                                     • High-throu...
Layne, the Bacteriologist©2012 Regents of the University of Minnesota. All rights reserved.
Screening for New Medicines                                                                           384 colonies        ...
Technology Increased Speed & Data Generation©2012 Regents of the University of Minnesota. All rights reserved.
Manual Colony Selection Became Automated                                                                     mRNA Microarr...
More Data Requires (More) Computers        # of data points generated                                                     ...
Researchers & Computers Network to   Manage Data – Share, Store, Analyze©2012 Regents of the University of Minnesota. All ...
Reviewing our definition…  …computationally intensive scientific research,  typically performed over distributed networks ...
Which Leads to the Next Part of the Story©2012 Regents of the University of Minnesota. All rights reserved.
Layne, the University of Minnesota          Person / Gopher / Frozen Guy         aka informationist, informaticist,       ...
Research at University of Minnesota • Twin Cities Campus        – >52,000 students, 3400 faculty, 150 graduate and        ...
Academic Health Center (AHC)©2012 Regents of the University of Minnesota. All rights reserved.
E-Science Landscape – 2006 - Present • Libraries developed a model for assessing   research support – 2005-2006 – humaniti...
E-Science Landscape – 2006 - Present • 2007+ - virtual community development –   EthicShare, AgEcon • 2007-2009 – Cyberinf...
Things We’ve Learned from Researchers • Participants want        – help with Data Management Plans (80%)        – to share...
Researchers also indicate they’d like: • to gain a better understanding of new data   management and collaboration tools (...
We used Charles Humphrey’s model of the      Research Life Cycle to help inform or  strategic direction for supporting e-s...
The Research Life Cycle©2012 Regents of the University of Minnesota. All rights reserved.
We Identified Library Roles • Content/Collection Development & Managing   Datasets • Teaching and Learning • Outreach • Li...
Research Networking • We first implemented open source Harvard   Profiles (UMN Profiles) - ~4,000 researchers • Collaborat...
Data Management Plans (DMP) • Brief description of how primary   investigator will comply with funder’s data   sharing pol...
Several DMP Tools Are Available • A variety of data management resources have   been developed at by the University Librar...
DataOne (NSF) DMPs • Several examples are provided at:   http://www.dataone.org/plans • DMPTool provides guidance and reso...
Where Our Work is Leading Us • We realize that there are gaps in   understanding privacy and security issues   around data...
Research Support and Services Collaboratives • Data Access Working Group • Research Communities and Networks • Digital Hum...
AHC Information Exchange • Governance structure consisting of the SVP   AHC, SVP of Research, CTSA PI • Working groups inc...
©2012 Regents of the University of Minnesota. All rights reserved.
Future of e-science • A positive development for libraries – it is   important for us to take the lead        – This is sh...
Acknowledgements • University of Minnesota Health Sciences   Colleagues, particularly Andre Nault, Jonathan   Koffel, Lind...
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Layne Johnson "e-Science at the Univeristy of Minnesota"

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Dr. Layne Johnson gave this presentation during the "Understanding E-Science: A Symposium for Medical Librarians" on February 13, 2012 in Houston, TX.

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Layne Johnson "e-Science at the Univeristy of Minnesota"

  1. 1. e-Science at the University of Minnesota e-Science Symposium National Network of Libraries of Medicine South Central Region Texas Medical Center Library Layne M. Johnson, Ph.D. February 13, 2012©2012 Regents of the University of Minnesota. All rights reserved.
  2. 2. History, Evolution & Current State • Present my experiences as a researcher and show how changes in research call for the expertise of librarians and information specialists • Review the experiences at Minnesota and the roles that the University Library colleagues have played • Take a fresh look at the developing requirements and advances in e-science to best prepare ourselves and researchers to meet future needs©2012 Regents of the University of Minnesota. All rights reserved.
  3. 3. First, Let’s Agree… • E-Science (or eScience) is computationally intensive scientific research, typically performed over distributed networks and involving large amounts of data. Also, e- science often involves collaboration. • E-Science can be referred to as E-Research to accommodate disciplines outside of the sciences, e.g. the Digital Humanities.©2012 Regents of the University of Minnesota. All rights reserved.
  4. 4. E-Science • …has often been called cyberinfrastructure in the U.S. • Nowadays, cyberinfrastructure is used less (at least by me), and e-Science is used more frequently.©2012 Regents of the University of Minnesota. All rights reserved.
  5. 5. Technology is the Major Impact on Science • High-throughput screening, sequencing • Equipment generating data 24/7 • Information increasing logarithmically • Communications, networking • Regulations, standards©2012 Regents of the University of Minnesota. All rights reserved.
  6. 6. Layne, the Bacteriologist©2012 Regents of the University of Minnesota. All rights reserved.
  7. 7. Screening for New Medicines 384 colonies 24 96 384 What next? Single colony©2012 Regents of the University of Minnesota. All rights reserved.
  8. 8. Technology Increased Speed & Data Generation©2012 Regents of the University of Minnesota. All rights reserved.
  9. 9. Manual Colony Selection Became Automated mRNA Microarrays [increased Aseptic Robotic Automation #samples, increased sensitivity]©2012 Regents of the University of Minnesota. All rights reserved.
  10. 10. More Data Requires (More) Computers # of data points generated 460800 500000 450000 400000 350000 300000 250000 200000 115200 150000 100000 28800 50000 240 0 1 Colony 24 Colonies 96 Colonies 384 Colonies Bacterial Colonies Tested©2012 Regents of the University of Minnesota. All rights reserved.
  11. 11. Researchers & Computers Network to Manage Data – Share, Store, Analyze©2012 Regents of the University of Minnesota. All rights reserved.
  12. 12. Reviewing our definition… …computationally intensive scientific research, typically performed over distributed networks and involving large amounts of data, with a dash of collaboration thrown in©2012 Regents of the University of Minnesota. All rights reserved.
  13. 13. Which Leads to the Next Part of the Story©2012 Regents of the University of Minnesota. All rights reserved.
  14. 14. Layne, the University of Minnesota Person / Gopher / Frozen Guy aka informationist, informaticist, librarian, etc.©2012 Regents of the University of Minnesota. All rights reserved.
  15. 15. Research at University of Minnesota • Twin Cities Campus – >52,000 students, 3400 faculty, 150 graduate and professional degrees – Medicine to business, law to liberal arts, science and engineering to architecture and agriculture – ~$770M in sponsored research in 2011, $305M from NIH – 2010 NSF research ranking – 8th among top 20 public research universities in the US©2012 Regents of the University of Minnesota. All rights reserved.
  16. 16. Academic Health Center (AHC)©2012 Regents of the University of Minnesota. All rights reserved.
  17. 17. E-Science Landscape – 2006 - Present • Libraries developed a model for assessing research support – 2005-2006 – humanities, social sciences • 2006-2007 – analysis of science faculty and graduate students re: discovery, use, & management of data and information • 2007 – ARL report – “Agenda for Developing E- Science in Research Libraries” – W. Lougee coauthor©2012 Regents of the University of Minnesota. All rights reserved.
  18. 18. E-Science Landscape – 2006 - Present • 2007+ - virtual community development – EthicShare, AgEcon • 2007-2009 – Cyberinfrastructure Alliance – University Libraries, IT, Office VP Research • 2010 – data audits, Research Networking implemented • 2010+ - Data Management workshops - >300 faculty©2012 Regents of the University of Minnesota. All rights reserved.
  19. 19. Things We’ve Learned from Researchers • Participants want – help with Data Management Plans (80%) – to share data with collaborators (84%) – to use metadata services (70%) – auto-backup data services (77%) – long term access to data (76%) – repositories for data on campus (e.g. GIS, 70%)©2012 Regents of the University of Minnesota. All rights reserved.
  20. 20. Researchers also indicate they’d like: • to gain a better understanding of new data management and collaboration tools (76%) • to be able to not only identify experts, but also core resources, like biorepository samples, core centers of technology and methods & equipment support • to compete more aggressively for funding opportunities©2012 Regents of the University of Minnesota. All rights reserved.
  21. 21. We used Charles Humphrey’s model of the Research Life Cycle to help inform or strategic direction for supporting e-science at the University of Minnesota (in the spirit of full disclosure, we modified the model – and so should you)©2012 Regents of the University of Minnesota. All rights reserved.
  22. 22. The Research Life Cycle©2012 Regents of the University of Minnesota. All rights reserved.
  23. 23. We Identified Library Roles • Content/Collection Development & Managing Datasets • Teaching and Learning • Outreach • Liaison Services • Translational Science and Informatics Support • Research Networking • Leadership©2012 Regents of the University of Minnesota. All rights reserved.
  24. 24. Research Networking • We first implemented open source Harvard Profiles (UMN Profiles) - ~4,000 researchers • Collaboration with Office VP Research, Libraries, Colleges – we are implementing SciVal Experts, Funding, Spotlight – Got us at the table – Is pushing us into ontology work, linked open data, and the semantic web©2012 Regents of the University of Minnesota. All rights reserved.
  25. 25. Data Management Plans (DMP) • Brief description of how primary investigator will comply with funder’s data sharing policy • Largest funding agencies include NIH and NSF©2012 Regents of the University of Minnesota. All rights reserved.
  26. 26. Several DMP Tools Are Available • A variety of data management resources have been developed at by the University Libraries the University of Minnesota. Check into them at http://www.lib.umn.edu/datamanagement • For DMPs, see specifically: http://www.lib.umn.edu/datamanagement/D MP (take a look at the DMP checklist)©2012 Regents of the University of Minnesota. All rights reserved.
  27. 27. DataOne (NSF) DMPs • Several examples are provided at: http://www.dataone.org/plans • DMPTool provides guidance and resources for your data management plan – Create plans – Meet funder requirements – Step by step instructions – Get data management advice©2012 Regents of the University of Minnesota. All rights reserved.
  28. 28. Where Our Work is Leading Us • We realize that there are gaps in understanding privacy and security issues around data – especially in the health sciences • We also have identified gaps in our understanding of bench scientist (discovery, T1, pre-human) needs • We recognize an opportunity to transform several roles to support research and data needs©2012 Regents of the University of Minnesota. All rights reserved.
  29. 29. Research Support and Services Collaboratives • Data Access Working Group • Research Communities and Networks • Digital Humanities • We see the boundaries between the Academic Health Center dissolving and a focus on enterprise solutions expanding • One example is the AHC Information Exchange©2012 Regents of the University of Minnesota. All rights reserved.
  30. 30. AHC Information Exchange • Governance structure consisting of the SVP AHC, SVP of Research, CTSA PI • Working groups include informatics, research studies, architecture – Many groups request support from the libraries – Identity (like ORCID, etc.) – Metadata – Classification©2012 Regents of the University of Minnesota. All rights reserved.
  31. 31. ©2012 Regents of the University of Minnesota. All rights reserved.
  32. 32. Future of e-science • A positive development for libraries – it is important for us to take the lead – This is shown to be true from e-Science Institute activities with ARL • Need for open dialogue at all levels – local, regional, national, global • Opportunities abound – and can be leveraged with existing resources and sound strategies©2012 Regents of the University of Minnesota. All rights reserved.
  33. 33. Acknowledgements • University of Minnesota Health Sciences Colleagues, particularly Andre Nault, Jonathan Koffel, Linda Watson • University Library colleagues, especially Lisa Johnston, John Butler, Meghan Lafferty, Wendy Lougee • Health Informatics Colleagues and Clinical and Translational Science Institute Colleagues • Cooper Mark Edward Johnson©2012 Regents of the University of Minnesota. All rights reserved.

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