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Advancing Data Citations: Best Practices and Challenges for Dynamic Datasets

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marli
11 diapositives · 255 Views · Jul 24, 2014

This report discusses the complexities of data citation, focusing on Digital Object Identifiers (DOIs) and their role in academia and research. Key topics include authorship issues, the definition of "new" datasets, and the significance of metadata in citations. It explores the maintenance and policy challenges surrounding DOIs, orphaned citations, and the necessary infrastructure for verifying dataset provenance. Emphasizing reproducibility and real-time data management, the report advocates for a consensus in the community to enhance data stewardship and improve recognition of research contributions through data citations.

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  1. Data Citation Breakout Report Pine Group http://twc.titanpad.com/82 March 3, 2011

  2. Folks • Chris Mattmann (NASA JPL, University of Southern California) • Bob Arko (LDEO) • Joanne Luciano (RPI) • Anna Milan (NGDC) • Bob Simons (NOAA) • Brian Wee (NEON, Inc.) • Leslie Hsu (LDEO) • Roland Viger (USGS, reporting) • James Wilson (James Madison University) • Tom Narock (NASA/GSFC) • Cathy Constable (SIO, UCSD) • Yoori Choi (CUAHSI)

  3. Good Article on DOI Formation • http://www.dlib.org/dlib/january11/starr/01starr.html

  4. Feedback • Guidance/examples to clarify • Many types of data (collect use-cases) • Scope of Identifier vs. Metadata • Daisy Chaining of DOIs • Roles (author, editor, others?) • authorship problematic (person who wrote the text report, idea person, technician/data cruncher/point of content) • Publisher also possibly unclear • Synthetic collections (what’s a “new” dataset?).

  5. Maintenance & Policy • Orphaned DOIs • Infrastructure/tools to detect • Policy consensus on what to do • Funding to implement • Ties in to data stewardship • Require DOI issuer to verify qualified hosting?

  6. Usage/Context of Citation • Subsetting? • Part of author’s methods? Transformations? • Not just “lat/long box”, selection by attribute, feature • Date of download vs. date of online availability • Promote linkage to traditional pubs • Minimum completeness of DOI spec vetted • Not science content or even metadata

  7. Possible Special Cases • Again, metadata vs. identifier/locator clarity • Multi-step derivatives • Year • Publication vs. acquisition • Temporal range • Provisional vs. Final data • Dynamic (e.g. real-time) “living” data sets and DOIs

  8. Research Needs • Consensus thresholds for creating a "new" product? • Reproducibility • Domain-specific? • New version vs. new data product • Handle "living"/streaming/real-time (i.e. constantly updated with new obs) data sets • Handle provisional/QA/QC changes to a data set (i.e. fixing previous obs)

  9. Ideas for Functionality • UnidataIDV used to allow publication of XML for specifying all the data used in a 4-D visualization. A consumer could load that XML into a new IDV session and pull all the exact same data.--> interesting application of a data citation. • Compilation tools from data provider to help create citable datasets. • Ruth’s point re: users not realizing what tools are doing wrt data marshalling

  10. Education/Outreach/Marketing • Consensus in community, traditional publishers critical uptake • Could inform NSF data mgmtreqs • Promote as important (potentially) as trad. Pubs for researcher evaluation