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NSF Data Management Plan Case
    Study: UVa’s Response

                        Andrew Sallans
 Head of Strategic Data Initiatives / Scientific Data Consulting
                       Group (SciDaC)
                 University of Virginia Library

        Research Data Access and Preservation Summit
                       31 March 2011
Outline
    1. DMP templates
    2. Advising/consulting with researchers
    3. Expansion of DMP Online tool




2
Our organization
     Mostly a virtual organization, coordination is priority
     University Libraries
         Scientific Data Consulting Group (2 FTE, 2 PTE)
         Professional School Data Librarians
         Subject Librarians
         Attorney
         IR Team
     VP/Chief Information Officer
       Info Security, Policy, and Records Office
       Other infrastructure managers (ie. storage, networks, etc.)
     Office VP for Research
     Office of Sponsored Programs

3
NSF Data Management Plans
     New NSF Directorates/Divisions continue to release
     and specify guidelines
       Education and Human Resources (EHR)
       Engineering (ENG)
       Geological Sciences (GEO)
       Mathematical and Physical Sciences (MPS)
       Social, Behavioral, and Economic Sciences (SBE)




4
DMP Templates
     Coordination of entire effort with VPR, CIO, and OSP
     Inform researcher of the requirements for their respective
        directorate/program, try to help them make good decisions
       Provide instructions for how to develop a DMP for that
        directorate/program (not just giving them a DMP)
       Formatted template in the structure that is specified by the
        directorate/program (if not specified, use the general)
       Encourage review/feedback on DMP draft from SciDaC
        before submission
       We use a disclaimer to try and avoid liability for misunderstood
        advice or other points gone wrong
       Available at: http://www.lib.virginia.edu/brown/data

5
Advising/Consulting to Researchers
     Aiming to get in the front of the research process, to reduce the
      amount of extra work necessary for project wrap-up
     Conducting data interviews/assessments (combination of many
      methods including UIUC/Purdue’s, DCC’s, and others) to establish a
      baseline with a given researcher
     Involving subject librarians for collective learning and
      development of skills
     Delivering a final assessment report and recommendations on
      data management process improvement to the researcher, with an open
      offer for consultation on how to implement the recommendations




6
Expansion of DMP Online Tool
     Recognition of need for
      US version of DCC’s
      DMP Online Tool
     Partnership developed
      between a number of
      institutions (CDL, UIUC,
      Smithsonian, UVa,
      DataONE, and DCC)
     Seeking additional
      participation from many
      other institutions (already
      ICPSR)


7
DMP Online Tool (continued)
     5 user types for system (Researcher, Editor, Funder Admin,
        Institution Admin, Super Admin)
       Multiple authentication options (using institutional options like
        Shibboleth as well as local system)
       Starting with NSF DMP requirements, will expand to other
        funders quickly
       Will provide institution-specific guidance, tied to
        authentication, and ideally make referral to local expertise
       Open to everyone
       Aiming to have a first version by around June (will be doing a
        big testing run first week of May with researchers and NSF officials at
        DataONE workshop)
       Details available:
        http://www.cdlib.org/uc3/datamanagement/dmpo.html


8
Challenges ahead… (a selection)
     Tighter coordination of services and support across the
        institution
       Data ownership issues
       Balance of priority (benefit to the institution or the
        researcher/community?)
       Alignment of these efforts with community, national,
        international efforts for data management
       Funding of the support services (part of overhead costs?)



9
Thank you!
     Andrew Sallans
     Head of Strategic Data Initiatives / Scientific Data Consulting Group
     University of Virginia Library
     Email: als9q@virginia.edu
     Twitter: asallans
     http://www.lib.virginia.edu/brown/data




10

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NSF Data Management Plan Case Study: UVa’s Response.

  • 1. NSF Data Management Plan Case Study: UVa’s Response Andrew Sallans Head of Strategic Data Initiatives / Scientific Data Consulting Group (SciDaC) University of Virginia Library Research Data Access and Preservation Summit 31 March 2011
  • 2. Outline 1. DMP templates 2. Advising/consulting with researchers 3. Expansion of DMP Online tool 2
  • 3. Our organization  Mostly a virtual organization, coordination is priority  University Libraries  Scientific Data Consulting Group (2 FTE, 2 PTE)  Professional School Data Librarians  Subject Librarians  Attorney  IR Team  VP/Chief Information Officer  Info Security, Policy, and Records Office  Other infrastructure managers (ie. storage, networks, etc.)  Office VP for Research  Office of Sponsored Programs 3
  • 4. NSF Data Management Plans  New NSF Directorates/Divisions continue to release and specify guidelines  Education and Human Resources (EHR)  Engineering (ENG)  Geological Sciences (GEO)  Mathematical and Physical Sciences (MPS)  Social, Behavioral, and Economic Sciences (SBE) 4
  • 5. DMP Templates  Coordination of entire effort with VPR, CIO, and OSP  Inform researcher of the requirements for their respective directorate/program, try to help them make good decisions  Provide instructions for how to develop a DMP for that directorate/program (not just giving them a DMP)  Formatted template in the structure that is specified by the directorate/program (if not specified, use the general)  Encourage review/feedback on DMP draft from SciDaC before submission  We use a disclaimer to try and avoid liability for misunderstood advice or other points gone wrong  Available at: http://www.lib.virginia.edu/brown/data 5
  • 6. Advising/Consulting to Researchers  Aiming to get in the front of the research process, to reduce the amount of extra work necessary for project wrap-up  Conducting data interviews/assessments (combination of many methods including UIUC/Purdue’s, DCC’s, and others) to establish a baseline with a given researcher  Involving subject librarians for collective learning and development of skills  Delivering a final assessment report and recommendations on data management process improvement to the researcher, with an open offer for consultation on how to implement the recommendations 6
  • 7. Expansion of DMP Online Tool  Recognition of need for US version of DCC’s DMP Online Tool  Partnership developed between a number of institutions (CDL, UIUC, Smithsonian, UVa, DataONE, and DCC)  Seeking additional participation from many other institutions (already ICPSR) 7
  • 8. DMP Online Tool (continued)  5 user types for system (Researcher, Editor, Funder Admin, Institution Admin, Super Admin)  Multiple authentication options (using institutional options like Shibboleth as well as local system)  Starting with NSF DMP requirements, will expand to other funders quickly  Will provide institution-specific guidance, tied to authentication, and ideally make referral to local expertise  Open to everyone  Aiming to have a first version by around June (will be doing a big testing run first week of May with researchers and NSF officials at DataONE workshop)  Details available: http://www.cdlib.org/uc3/datamanagement/dmpo.html 8
  • 9. Challenges ahead… (a selection)  Tighter coordination of services and support across the institution  Data ownership issues  Balance of priority (benefit to the institution or the researcher/community?)  Alignment of these efforts with community, national, international efforts for data management  Funding of the support services (part of overhead costs?) 9
  • 10. Thank you! Andrew Sallans Head of Strategic Data Initiatives / Scientific Data Consulting Group University of Virginia Library Email: als9q@virginia.edu Twitter: asallans http://www.lib.virginia.edu/brown/data 10