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Characterizing the Biomedical Data-Sharing Landscape.

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  • 1Angela G. Villanueva, M.P.H., is a Research Associate at the Center for Medical Ethics and Health Policy at Baylor College of Medicine. Robert Cook-Deegan, M.D., is a Professor in the School for the Future of Innovation in Society at Arizona State University. Barbara A. Koenig, Ph.D., is Professor of Bioethics and Medical Anthropology, based at the Institute for Health & Aging, University of California, San Francisco. Patricia A. Deverka, M.D., M.S., M.B.E., is Director, Value Evidence and Outcomes at Geisinger National Precision Health, where she focuses on demonstrating the value of genomic sequencing for health systems and policy-makers.Erika Versalovic is a Ph.D. student in the philosophy department at the University of Washington and a neuroethics fellow with the Center for Neurotechnology in Seattle, WA. Amy L. McGuire, J.D., Ph.D., is the Leon Jaworski Professor of Biomedical Ethics and Director of the Center for Medical Ethics and Health Policy at Baylor College of Medicine. Mary A. Majumder, J.D., Ph.D., is an Associate Professor of Medicine at the Center for Medical Ethics and Health Policy, Baylor College of Medicine.

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Summary
This summary is machine-generated.

New technologies enable extensive biomedical data sharing, particularly genomic data. A new typology reveals diverse data-sharing practices and stakeholders, challenging traditional norms about individual data ownership.

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Area of Science:

  • Biomedical Informatics
  • Genomic Data Science
  • Health Data Governance

Background:

  • Technological advancements and biomedical informatics have significantly increased the capacity for generating and sharing biomedical data.
  • Genomic data presents unique challenges and opportunities within the broader biomedical data landscape.
  • Existing frameworks for data sharing may not fully encompass the complexities of modern biomedical research.

Purpose of the Study:

  • To develop a typology that characterizes the landscape of genomic data sharing in biomedical research.
  • To identify key stakeholders involved in genomic data sharing.
  • To understand current data-sharing practices and their implications for research norms.

Main Methods:

  • Analysis of existing literature and case studies on genomic data sharing.
  • Development of a classification system (typology) for data-sharing initiatives.
  • Stakeholder analysis within the biomedical research ecosystem.

Main Results:

  • The study reveals a diverse range of data-sharing efforts and facilitators in genomic research.
  • The typology highlights various stakeholders, including researchers, institutions, and patient advocacy groups.
  • Novel data-sharing models are emerging that challenge established norms regarding data control and individual privacy.

Conclusions:

  • A nuanced understanding of the genomic data-sharing landscape is crucial for effective research collaboration.
  • Existing data-sharing norms are being redefined by innovative practices, particularly concerning the role of data subjects.
  • Further research is needed to develop adaptive governance frameworks that support responsible and equitable data sharing.