Data management at MSU Library: an overview
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Data management at MSU Library: an overview



Overview of data management at Montana State University

Overview of data management at Montana State University



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  • Data management should happen throughout the data lifecycle, from the moment you conceive of a research project until the data are archived and preserved for future access and reuse. (Lifecycle from UK Data Archive) <br /> <br /> Creating data <br /> design research <br /> plan data management (formats, storage etc) <br /> plan consent for sharing <br /> locate existing data <br /> collect data (experiment, observe, measure, simulate) <br /> capture and create metadata <br /> <br /> Processing data <br /> enter data, digitise, transcribe, translate <br /> check, validate, clean data <br /> anonymise data where necessary <br /> describe data <br /> manage and store data <br /> <br /> Analyzing data <br /> interpret data <br /> derive data <br /> produce research outputs <br /> author publications <br /> prepare data for preservation <br /> <br /> Preserving data <br /> migrate data to best format <br /> migrate data to suitable medium <br /> back-up and store data <br /> create metadata and documentation <br /> archive data <br /> <br /> Giving access to data <br /> distribute data <br /> share data <br /> control access <br /> establish copyright <br /> promote data <br /> <br /> Re-using data <br /> follow-up research <br /> new research <br /> undertake research reviews <br /> scrutinise findings <br /> teach and learn <br /> <br /> <br />
  • Funding agency requirements <br /> NSF, NIH <br /> Whitehouse memo that says “unclassified research funded by the Federal Govt must be stored for long-term preservation and publicly available in order to maximize the impact of the Federal research investment” <br /> A recent article in “Nature” mentioned that NIH and Wellcome Trust are withholding grant money from researchers who do not make publications openly available – this trend could someday apply to data. Funding agencies are taking open access seriously <br /> <br /> Advance science <br /> Facilitate data reuse and repurposing <br /> Expedite the scientific process, saving time and resources in the long run <br /> Ensure research integrity – data can be used to replicate results and verify research <br /> <br /> Support open access – MSU’s institutional repository is optimized for search engines, so your data will rise to the top of a Google search. This leads to <br /> Increased research impact <br /> Increased citations <br /> Share data and knowledge <br /> Public: scientific community <br /> Increases research efficiency – and prevents duplication of effort by enabling others to use your data <br /> Private: data management tools allow sharing within a research team <br /> Preserve your data <br /> Protect your data for future research <br /> For example, Climate researchers use data from the past hundred years to analyze climate trends. You want your data to be available to support agriculture development on Mars in the 22nd Century! <br /> <br /> <br />
  • You (the researcher): <br /> Create <br /> Informative file names <br /> Logical directory and folder structures <br /> Preservation-friendly formats <br /> Document <br /> Versions <br /> Metadata <br /> ReadMes <br /> Protect <br /> Sensitive data <br /> Backup: master, local, external <br /> <br /> <br />
  • Bulk data storage <br /> Data analysis and visualization <br /> Software development
  • Data Management Librarian: <br /> Data management consulting <br /> DMPTool <br /> Help write and revise data management plans <br /> Metadata consulting <br /> Scholarly communication <br /> Encourage data sharing and reuse <br /> Advise on copyright and sensitive data <br /> Data repository guidance <br /> Including data publishing in ScholarWorks, our institutional repository
  • And of course facilitates the long-term preservation and accessibility of your work. <br /> <br /> ScholarWorks: Your scholarly output, all freely available in one place <br /> Open access to your scholarly output (articles, book chapters, presentations, blogs, data, etc.) <br /> Link to your data, even if it’s archived elsewhere (e.g. in a discipline-specific repository) <br /> Link your data to the associated articles <br /> Receive a permanent identifier for clear citations <br /> Store embargoed data for future publication <br /> Preserve your scholarly output for the long term <br />

Data management at MSU Library: an overview Presentation Transcript

  • 2. OUTLINE  What is data management?  Why data management?  Data management roles at MSU  What does the library offer?
  • 3. WHAT IS DATA MANAGEMENT? create process analyze preserve give access re-use from UK Data Archive:
  • 4. WHY DATA MANAGEMENT? Direct Verification of published research Preservation of access to data Allows reuse/repurposing of data Data discoverability Indirect (costs avoided) Redundant data collection Inefficient legacy data curation Burden of sharing-upon-request Near term Protects against personnel turnover Facilitates review and validation Long term Secure long-term stewardship Increased impact per publication Private Increased citations New collaborations Public More efficient use of research dollarsAdapted from Dryad 101, and Beagrie N, Lavoie BF, Woollard M (2010) Keeping Research Data Safe 2. Bristol:
  • 5. DATA MANAGEMENT ROLES You (the researcher) •Informative file names •Logical directory and folder structures •Preservation-friendly formats Create •Versions •Metadata •Readmes Document •Sensitive data •Backup: master, local, externalProtect
  • 6. DATA MANAGEMENT ROLES Research Computing Group  Bulk data storage  Data analysis consulting  Software development
  • 7. DATA MANAGEMENT ROLES Data Management Librarian Data management consulting Data repository guidance Scholarly communication Connections to other resources
  • 9. WHAT DOES THE LIBRARY OFFER? Learning opportunities  Workshops for faculty  Education modules for the classroom