Session Organizers: Philip Payne (Washington University), Nigam Shah (Stanford University), Jessie Tenenbaum (Duke University), Lara Mangravite (Sage Bionetworks) 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 in proximal domains resulting in greater productivity and a reduction in redundant research investments. While great strides have been in made in terms of enabling the open science paradigm in the biological science domain, progress in sharing of patient-derived health data has not been as notable. 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 molecular to patient to populations) are being developed and tested. To address these challenges, this session will focus on current best practices, lessons learned and the need of policy as well technical innovation for the sharing of health data for translational research, including the following topic areas: What are the major successes and lessons learned to-date in terms of creating the policy, technical, and socio-cultural frameworks necessary to deliver patient-derived “reference” data sets “at scale” to the translational research community? Where such data has been made available “at scale”, what types of innovative translational research, spanning scales from molecules to patients to populations, has been made possible, and has that research been proven to be reproducible or cumulative in nature (in accordance with the principles of open science)? What are the current gaps in knowledge and practice that prevent or preclude the further development and widespread use of such frameworks, and ultimately data sets, such that the sharing of patient-derived “reference” data sets achieved parity with the sharing of biological data? We are currently inviting paper submissions for this session that address the following areas: The creation, verification and validation of tools and methods that can assist in the sharing, discovery, and analysis of open health data in a primary or secondary manner, including the development of databases, algorithms, and modeling techniques The conduct of discovery science in data-intensive experimental contexts that leverage such open health data resources across scales from molecules to patient to populations The interaction of multidisciplinary computational, biology, clinical, and population health science teams to conduct research that serves to identify policy, technical, and socio-cultural needs associated with the implementation of open science paradigms that include not only biological but also patient- derived health data, with all of the complexities that such diverse data sets and their sharing involves

Submission deadline: August 1, 2017 Meeting date and location: January 3-7, 2018 - The Big Island of Hawaii   For more details on submission guidelines, please visit the PSB web site at: PSB Paper Format Instructions Need more information? Email the session organizers: prpayne@gmail.com