There is an expanding and intensive focus on the accessibility, reproducibility, and rigor of basic, clinical, and translational research. This focus complements the need to identify sustainable ways to generate actionable research results that improve human health. The principles and practices of open science offer a promising path to address both issues by facilitating: 1) increased transparency of data and methods which promotes research reproducibility and rigor; and 2) cumulative efficiencies wherein research tools and the output of research are combined to accelerate the delivery of new knowledge. While great strides have been in made in terms of enabling the open science paradigm in the biological sciences, progress in sharing of patient-derived health data has been more moderate. This lack of widespread access to common and well characterized health data is a substantial impediment to the timely, efficient, and multi-disciplinary conduct of translational research, particularly in those instances where hypotheses spanning multiple scales (from molecules to patients to populations) are being developed and tested. To address such challenges, we review current best practices and lessons learned, and explore the need for policy changes and technical innovation that can enhance the sharing of health data for translational research.

Original languageEnglish
Pages (from-to)240-246
Number of pages7
JournalPacific Symposium on Biocomputing
Issue number212669
StatePublished - 2018
Event23rd Pacific Symposium on Biocomputing, PSB 2018 - Kohala Coast, United States
Duration: Jan 3 2018Jan 7 2018


  • Data science
  • Open data
  • Open science
  • Translational research


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