Working Group 5: Dataset Citation Metrics


Susanna-Assunta Sansone, PhD

Jeffrey Grethe, PhD

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Define a set of qualitative and quantitative metrics that support intended capability of the NIH BD2K Data Discovery Index (DDI) prototype - being designed by the bioCADDIE Core Development Team. Please, refer to the White Paper for details on what the bioCADDIE is set to accomplish and how this consortium operates.

The DDI has fairly loose requirements for indexing biomedical data (stored in existing data sources), and various quality metrics should be used to determine how and which data is filtered and presented to the users.

Such metrics such as the date when the data were produced, provenance (from which researchers, groups, database, project, funders etc), the number of times a data set has been cited in the literature, downloaded from a repository or richly curated according to community standards could serve as the means to rank data results or provide the user with a set of criteria to restrict their search


Members and synergies

This WG does not plan to initiate a separate discussion, but aims to link with and contributes to existing and synergistics community activities to determine metrics to be used for the DDI prototype, namely:

  1. Making Data Count project; co-led by Jennifer Lin and Martin Fenner (PLOS), Trisha Cruse (CDL), and DataONE.
  2. NISO Altmetrics initiative on output types and identifiers; co-chaired by Mike Taylor (Elsevier) and Kristi Holmes (Northwestern)
  3. CASRAI Data Level Metrics group led by Rebecca Lawrence (F1000Research) and Sunje Dallmeier-Thiessen (CERN).
  4. THOR; consortium of 10 partners.



This WG will summarize lessons learned by the activities above, identifying what can be used by and implemented in the DDI and what is still needed.

Group Members