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Related Experiment Video

Updated: Apr 30, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Workflow for detecting biomedical articles with underlying open and restricted-access datasets.

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Summary
This summary is machine-generated.

We developed a validated, semi-automated workflow to monitor research data sharing in biomedical articles. This method reliably identifies openly and restricted-access data, aiding institutional and funder monitoring efforts.

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Area of Science:

  • Biomedical Research
  • Meta-research
  • Data Science

Background:

  • Monitoring research data sharing is crucial for institutions and funders.
  • Existing automated tools for data sharing detection have limitations in definition and scope.
  • Previous manual validation studies were based on small sample sizes.

Purpose of the Study:

  • To develop and validate a comprehensive, semi-automated workflow for detecting shared research data in biomedical publications.
  • To establish detailed criteria and a workflow combining automated and manual steps for screening both open and restricted-access data.
  • To provide reliable data for internal incentivization schemes and institutional monitoring dashboards.

Main Methods:

  • Developed detailed screening criteria for research data sharing.
  • Implemented a workflow combining automated screening with manual validation.
  • Validated the screening procedure using two independent samples, achieving high inter-rater reliability (Krippendorff's alpha ≥0.8).
  • Screened 11,035 biomedical research articles, with 1,381 articles undergoing manual review for potential data sharing.

Main Results:

  • The developed workflow demonstrated high reliability in detecting shared research data.
  • In the 2021 institutional sample, 7.8% of articles had openly shared underlying data.
  • An additional 1.0% of articles shared restricted-access data, totaling 8.3% with open and/or restricted-access data.
  • Screening results were reported for the institution and an independent meta-research sample.

Conclusions:

  • The presented workflow is a comprehensive and validated method for identifying shared research data in biomedical publications.
  • The workflow effectively combines automated and manual processes to consider both open and restricted-access data.
  • The methodology is adaptable for various contexts, with potential for future development and application.