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Metadata for Research Data

Metadata for Research Data

Presentation given to the LIS853: Metadata course, UW-Madison iSchool. October 2015

Brianna Marshall

October 26, 2015
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  1. about me Brianna Marshall Digital Curation Coordinator, UW Libraries Lead,

    Research Data Services MLS/MIS, May 2014 Indiana University School of Informatics + Computing    
  2. what is research data? “the recorded factual information commonly accepted

    in the scientific community as necessary to validate research findings.” INCLUDES: code, figures, statistics, interviews, transcripts EXCLUDES: preliminary analyses, drafts of papers, plans for further research, communication + peer reviews, physical samples -  OMB Circular, White House
  3. federal funding requirements around research data Data Management Plans (DMPs)

    required by most federal funders since 2011 Office of Science and Technology Policy (OSTP) memorandum •  Released by the White House •  Published spring 2013; took effect fall 2015 •  Requires open sharing of published articles and data •  Publication repository is provided; data repository is not •  Most require that researchers provide access to “all materials needed to reproduce published findings” •  Applies to agencies with $100M + in R&D
  4. the who, what, why, where, when Important information to capture

    about data may include: •  Principal investigator •  Funding sources •  Data collector/producer •  Project description •  Sample and sampling procedures •  Weighting •  Substantive, temporal, and geographic coverage of the data collection •  Data source(s) •  Unit(s) of analysis/observation •  Variables •  Technical information on files •  Data collection instruments Adapted from ICPSR
  5. what’s in a good readme file? •  Names + contact

    info for people associated with the project" •  List of files, including a description of their relationship to one another" •  Copyright + licensing information" •  Limitations of the data" •  Funding sources / institutional support" " tl;dr !! Any information necessary for someone with no knowledge of the research to understand and / or replicate the work."
  6. what do I tell researchers? •  Describe project/folder level vs.

    item-level description •  Advise them to start conversation + remain aware of community standards •  I have to make tough choices as repository manager –  If a dataset doesn’t have metadata, I won’t preserve it –  Sometimes data (even with detailed metadata!) is too big for our repository platform •  Data without the contextual information needed to interpret it (and ultimately reproduce the research results) is useless"
  7. final thoughts •  In research, sharing data isn’t yet commonplace

    - much less capturing metadata" •  Federal funding requirements necessitate data sharing but don’t provide guidance on metadata to support it" •  Metadata standards are disciplinary; can be hard to give generalizable advice" •  We need new information professionals willing to wade into the mess and help us solve this!"