Iassist 2012 dms public version


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  • Joint effort between us and scientistNot perfectly linear- can archive at any point, but this is our ideal processInterview-hardly anyone thinks their data is useful to others
  • Iassist 2012 dms public version

    1. 1. Johns Hopkins University Data Management Services: Reviewing Our First Year David Fearon Betsy Gunia IASSIST June 7, 2012 1
    2. 2. Our service development: a social science analogy Developing new services for data management support required understanding social factors, not just technical.• Services emerging from data curation “social movement”• Investigating – University culture for outreach – Data practices for consulting & curation support – Trends in public funding, data sharing & curation 2
    3. 3. Data curation “social movement” Emergence Recognizing the need for curation & access • eScience: digital data production outpaces sharing & preservation Coalescence Policy & requirements • Jan 2011: NSF Data Management Plan requirementInstitutionalization Building Services & Infrastructure • 2009: NSF DataNet funds Data Conservancy at JHU 3
    4. 4. Data Management Services at Academic Libraries• Academic libraries in early stages of expanding services to support data curation & management Data Management Planning Support Assist in data Provide tools Consult with archiving & for planning researchers sharing JHU Data Management Services 4
    5. 5. JHU Data Management Services Preparing Data Archiving Research Data Management Plans Assist in implementing plan, Assistance with data Services management plans preserve & share research through JHU Data Archive Funded by JHU schools Cost using our service 2% of grant’s total direct cost JHU Data Archive features (in development): Data Conservancy architecture Accepts data from all disciplines Feature-level discovery Interoperable data access Persistent identifiers Supports long-term preservation .org 5
    6. 6. Investigating JHU Cultures to introduce Data Management Services Outreach Goals Approach Building awareness Finding appropriate of services communication channels Research Projects Dept. Deans Admin Admins Library Targeted Colleagues Researchers workshops 6
    7. 7. Investigating JHU Cultures to introduce Data Management Services Outreach Goals Approach Building awareness Finding appropriate of services communication channels Demonstrating Consulting and Relevance of customized support services Do DMPs Investigating data practices archive matter to Can’t I copy Why NSF? a template? my data? 7
    8. 8. Understanding Data Practices Data Management Plans Data Practices Data Archiving 8
    9. 9. Consulting on data management plans Contact from Final Plans Principal Info on PI Investigator (PI) Standards JHU DMS Background Comments on Plan Research Data Repositories PI Drafts Data In-Person Questionnaire Management Consultation Plan 9
    10. 10. In-Person Consultation Tool: Questionnaire (sample questions)Section I: Data Products and StandardsWhat naming conventions/schema will be used for yourdata, if any?Section II: Data Storing and Long-Term PreservationDuring the project, how (i.e. media) and where (i.e.location(s)) will data be stored and who is responsiblefor it?Section III: Data SharingAre there any data with privacy concerns to sharing(e.g., human subjects)? If so, what policies need to beadhered to and how will policies be enforced? 10
    11. 11. Social vs. Physical Science: Observations from data plans • Mixture of digital and physical material:Data Type/ • digital (documents, audio recordings, photos, database) Qty • non digital (newspaper, interview notes, artifacts) • Datasets on the scale of MBs and GBs, not TBs • Use of human subjects does not exempt one from sharing Personal dataIdentifiers oGraduate student received grant but was asked to modify data management plan and find something to share • More familiar with term “codebook” than “metadata”Metadata • Metadata is more often created manually by the PI 11
    12. 12. Archiving of Data: An Evolving ProcessMap how data flows through researchproject Evaluate existing data and identify missing information Decide what and when to archive 12
    13. 13. Investigating trends in data curation Funders new requirements & policy •Other funders adopting data management plan requirementsData curation archiving, repositories, standards• Expanding our expertise and knowledgebaseData sharing Collaboration, data-intensive science• E.g., academic credit for sharing data collections? 13
    14. 14. Thank you David Fearon Betsy Gunia datamangement@jhu.eduJHU Data Management Services The Sheridan Libraries http://dmp.data.jhu.edu/ (410) 516-0713 14