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Practical Applications of e-Science
 

Practical Applications of e-Science

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A. Sallans. "Practical Applications of e-Science." Presented at the 2011 eScience Bootcamp at the University of Virginia's Claude Moore Health Sciences Library. 4 March 2011

A. Sallans. "Practical Applications of e-Science." Presented at the 2011 eScience Bootcamp at the University of Virginia's Claude Moore Health Sciences Library. 4 March 2011

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    Practical Applications of e-Science Practical Applications of e-Science Presentation Transcript

    • PRACTICAL APPLICATIONSOF E-SCIENCEAndrew SallansHead of Strategic Data InitiativesUniversity of Virginia LibraryE-Science BootcampClaude Moore Health Sciences Library, University of Virginia4 March 2011
    • ROUND 2:SCIENTIFIC DATA CONSULTING GROUP December/January 2010: rethinking the model  Budgetary pressures  Changes in organizational priorities  Emerging demand in research community Spring 2010: decision to focus on data May 2010: close of RCL, start of SciDaC 2
    • WHAT’S HOT IN 2010? Open data: growing governmental interest in making publicly-funded research more transparent and more available (NIH, NSF) Broader critical review: greater interest evaluating original research data (Nature) Technological advances: sharing of research results easier and faster (Repositories, Web 2.0) Reuse/preservation of research data: increased consideration of the cost and value of research data and need to ensure its longevity 3
    • “SCIENTISTS SEEKING NSF FUNDING WILL SOON BEREQUIRED TO SUBMIT DATA MANAGEMENT PLANS”Press Release 10-077, May 5, 2010 Current Policy: o “To advance science by encouraging data sharing among researchers” o Data obtained with federal funds be accessible to the general public o Grantees must develop and submit specific plans to share materials collected with NSF support, except where this is inappropriate or impossible On or around October 2010: o All new NSF proposals will be required to include a data management plan in the form of a 2 pg supplementary document (peer reviewed) o New policy is meant to be a 1st step toward a more comprehensive approach to data management o Exact requirements vague 4
    • THE CHALLENGE FOR INSTITUTIONSData is expensive Time, instrumentation, inability to reproduceIncreasing regulation Granting agencies and journals require submissionInadequate training No formal data management curriculumPreservation is not a priority For most researchers, preservation takes time away from the work that is rewarded (publication, teaching) 5
    • SO…WHO’S GOING TO TAKE THIS ON? Researchers? VPR? CIO? OSP? UL? 6
    • WHY THE LIBRARY? Neutral: works across the entire institution Strong in relationship building: has experience fostering discussion and relationships, and cultivates an existing support network Intellectual Property experts: has dealt with copyright, can translate to data Service-oriented: uniquely positioned as an intellectual service unit within the institution 7
    • GETTING STARTED… Take what we learned in the RCL experience and apply it to the focused demands around dataSteps: Conduct a stakeholder analysis Make a short term plan (12 months) Develop clear priorities Refine and standardize consulting methods Communicate heavily 8
    • STAKEHOLDER ANALYSIS (ABBREVIATED)Internal External Researchers  Funding agencies Graduate Students  Broader research Grant Administrators community Deans  “The Public” VP/CIO VPR OSP UL 9
    • SHORT TERM PLAN Survey OSP to match grant holders with regulations Educate/engage subject librarians Build political awareness/support Build partnerships with local/national/international groupsResource requests: Staffing commitment Travel/partnership support 10 Promotion of initiative to institution
    • CLEAR PRIORITIES1. Data interviews/assessments2. Response to NSF Data Management Plan (DMP) Mandate3. Leadership on data for the Institutional Repository (IR) 11
    • CONSULTING METHODS Interviews/assessments DMP templates LOTS of documentation Constant and continuous refinement of process Adherence to core principle of helping the researcher improve process (not approaching it theoretically) 12
    • COMMUNICATE HEAVILY Internal  Inform staff of processes, priorities, and progress  Keep stakeholders engaged  Reach the consumers from many angles External  Discuss and share experiences with colleagues at other institutions  Create partnerships to share, build upon resources and experiences, collaborate on tools  Networking (Twitter, LinkedIn, listserves, conference calls, conference presentations) Bottom line: this is a big culture shift, and you do have to 13 say the same thing many times in different ways
    • HOW TO MAKE THIS WORK… Librarians as partners o Consult with and advise researchers o Provide leadership to the institution o Work with existing data organizations In order to succeed, librarians need to: • Build and develop specific expertise • Facilitate communication 14
    • TIME OUT: NSF DMP UPDATE Now effective January 18, 2011 Some earlier proposals also require DMPs (even some in early December) Broad guidelines, but directorates may have specific guidelines for their community Uploaded as 2-page supplemental document in FastLane (with specific format requirements) Formally peer-reviewed, and will require status updates in all progress reports 15
    • UVA SCIDAC NSF DMP RESPONSEUVa Library’s Original Request Develop boilerplate for researchers to use in proposalsSciDaC Group’s Response No boilerplate, successful proposals need customized plans Our approach involves:  Knowledge across many communities (“translational” opportunities)  Leadership on policy/infrastructure development  Development of a template that simplifies writing the planPrinciples Must be easy for researcher Must be supportable by available UVA resources/infrastructure Must be able to be followed-through on if grant is awarded 16
    • ONGOING ISSUES Training: how do you train librarians to meet these new needs? Buy-in: how do you get effective buy-in from people around the institution? Scalability: how do you scale this to support all of the researchers who need support? 17
    • TRAINING LIBRARIANSUVa Library Staff Model Scientific Data Consultants Subject LibrariansCurrent Training Model Brown Bag Data Curation Discussions Data InterviewsGoals and Objectives Build Data Literacy Create Collaborative Opportunities Establish the Library for Data Preservation 18
    • BUY-IN BY THE INSTITUTION Regulations are helpful Partnerships between key stakeholders:  University libraries (UL)  Central IT (CIO)  Research Office (VP for Research)  Sponsored Programs/Research Strategic investment: take ownership, allocate resources, and demonstrate capability 19
    • SCALING UP TO MEET DEMAND Time: NSF research support alone is going to be very time consuming (UVA had about 140 proposals over the past year, 44 in November alone) Funding: work with leaders to find money  Redirection/reallocation of grant overhead dollars  Write-in of library staff on grants Strategy: decide how to invest  How might units be reorganized?  How could staff resources and expertise be refocused? 20  What external partnerships would add value?
    • WRAP-UP Libraries are well-positioned to play a vital role in research data support Open Data initiatives are a call to action 21
    • QUESTIONS? Please feel free to contact me with questions at als9q@virginia.edu or 434-243-2180. 22