Libraries & Librarians

First-of-Its-Kind: Largest Collection of Data Reuse Indicators Now Openly Available

October 15, 2026

Make Data Count and Digital Science have released a first-of-its-kind open, contextualized collection of linkages between research articles and the datasets they cite or reuse. This effort builds on Make Data Count’s decade-long endeavors to make all connections between data and papers publicly accessible, with Digital Science contributing their expertise and infrastructure to greatly expand the resource.

The collection, now available to access from Make Data Count, brings together a comprehensive set of datasets mentioned in research articles across disciplines, identified by DOI or accession number. Where the evidence supports it, these links are classified as primary (data generated for the article) or secondary (existing data reused in the study). Built by Digital Science in collaboration with Make Data Count and open source algorithms, the resource is available under a CC0 public-domain dedication. This resource will be updated monthly, with dated releases available so users can cite the specific version they use.

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Responsible data metrics depend on evidence that the community can examine, question, and improve. This regularly updated collection is intended for use across all disciplines, research and evaluation stakeholders. The linkages also give infrastructure providers and research information services a shared foundation for developing and scrutinizing tools and indicators. Open, auditable, and trusted infrastructure are core values of the Make Data Count initiative, and the broad dissemination of this corpus allows for any use and integration of this information.

“While the goals of MDC have not changed since its inception, our methods for developing the necessary open infrastructure for data metrics have evolved. The key piece to all of our work, and what’s been missing, is having a trusted and comprehensive base of information covering the many ways data are mentioned in scientific articles. This new approach to building a data citation corpus is a major milestone in advancing our understanding of how open data are reused”
— Daniella Lowenberg, Chair, Make Data Count Steering Committee

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Explore this first release by downloading a CSV snapshot from the Make Data Count website or through BigQuery and consult the accompanying technical documentation for more information. We look forward to supporting all of the future integrations and use of this novel information!