Connecting shared biomedical data, code, and researchers to speed discovery
SoS:B10:ldentifying and Encouraging Connections among Data Reuse, Scientific Innovation, and Scientific Careers
['FUNDING_R01'] · UNIVERSITY OF MICHIGAN AT ANN ARBOR · NIH-11193514
This project looks at how sharing and reusing biomedical datasets, analysis code, and researcher collaborations can lead to more diverse and novel scientific discoveries that could help patients.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF MICHIGAN AT ANN ARBOR (nih funded) |
| Locations | 1 site (ANN ARBOR, UNITED STATES) |
| Trial ID | NIH-11193514 on ClinicalTrials.gov |
What this research studies
You can expect the team to build 'knowledge graphs' that link publications, datasets, analysis code, variables, and author information from public archives like ICPSR and PhysioNet. They will combine metadata from sources such as Dimensions and OpenAlex to trace how data and code move through the research system. The project will measure whether reused data leads to more diverse or novel findings and whether certain researchers or datasets are overlooked. Finally, the team will refine their metrics with stakeholder input and make recommendations to encourage fairer, more impactful data reuse in biomedical research.
Who could benefit from this research
Good fit: This project does not enroll patients directly; it uses existing biomedical datasets and researcher metadata, so people whose health data are already archived in public repositories (like PhysioNet) are the ones indirectly involved.
Not a fit: Patients whose conditions are not represented in public or archived biomedical datasets are unlikely to see direct benefits from this project.
Why it matters
Potential benefit: If successful, this work could speed up useful discoveries, make research more equitable, and help ensure important datasets and code reach more researchers who can translate findings into better care.
How similar studies have performed: Prior bibliometric and data-sharing studies have shown that sharing can increase citations and collaboration, but linking datasets, code, and researchers with knowledge graphs to promote diversity and novelty is a newer and less-tested approach.
Where this research is happening
ANN ARBOR, UNITED STATES
- UNIVERSITY OF MICHIGAN AT ANN ARBOR — ANN ARBOR, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: HEMPHILL, LIBBY — UNIVERSITY OF MICHIGAN AT ANN ARBOR
- Study coordinator: HEMPHILL, LIBBY
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.