文献类型： 会议论文

第一作者： Nigam H. Shah

作者： Nigam H. Shah ¹ ; Jessica D. Tenenbaum ² ; Lara Mangravite ³ ; Philip R.O Payne ⁴ ;

作者机构： 1.Center for Biomedical Informatics Research, Stanford University School of Medicine Stanford, CA, USA

2.Department ofBiostatistics and Bioinformatics, Duke University School of Medicine Durham, NC, USA

3.Sage Bionetworks Seattle, WA, USA

4.Institute for Informatics, Washington University School of Medicine St. Louis, MO, USA

关键词： Open Science;Open Data;Translational Research;Data Science

会议名称： Pacific Symposium on Biocomputing

主办单位：

页码： 240-246

摘要： 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.

分类号： q811