Grants

University of California, Office of the President

To scale up adoption of standardized data usage and data citation metrics across the scholarly communications landscape

  • Amount $368,298
  • City Oakland, CA
  • Investigator Daniella Lowenberg
  • Year 2020
  • Program Technology
  • Sub-program Data & Computational Research

The Make Data Count (MDC) initiative has worked with global research stakeholders and through the Research Data Alliance (RDA) to develop the building blocks for responsible research assessment metrics for research data, to better understand the impact and reach of data. Not only has the initiative developed a community-vetted standard for the reporting of data usage metrics, is has also created a set of server-side tools that allow easy implementation of the standard by existing data repositories.  Initial partners already implementing the standard include Dataverse, Zenodo, Figshare, Dryad, institutional and governmental repositories. Funds from this grant provide support for the continued expansion and increased adoption of the MDC data metrics standards and framework. Led by Daniella Lowenberg at the California Digital Library, the MDC team will focus on three key groups of activities over the two-year grant period. First, they will make it dramatically easier for less-resourced repositories to implement and benefit from data metrics by developing a log analysis server and expanding an existing event data aggregator to include dataset metrics. Second, they will work through the publisher consortium network, CrossRef, to encourage journal publishers to implement best practices for data citation. Third, they will work in collaboration with the bibliometric research community to begin studying data usage across research disciplines, through the development of an open corpus of data for the study of data citation and usage trends. This work will continue to elevate research data in international discussions about research assessment and value, with goals of developing accessible and understood open data metrics.  

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