Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/132328
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Type: Journal article
Title: Sharing data to build a medical information commons: from Bermuda to the Global Alliance
Author: Cook-Deegan, R.
Ankeny, R.A.
Jones, K.M.
Citation: Annual Review of Genomics and Human Genetics, 2017; 18(1):389-415
Publisher: Annual Reviews
Issue Date: 2017
ISSN: 1545-293X
1545-293X
Editor: Chakravarti, A.
Green, E.D.
Statement of
Responsibility: 
Robert Cook-Deegan, Rachel A. Ankeny, and Kathryn Maxson Jones
Abstract: The Human Genome Project modeled its open science ethos on nematode biology, most famously through daily release of DNA sequence data based on the 1996 Bermuda Principles. That open science philosophy persists, but daily, unfettered release of data has had to adapt to constraints occasioned by the use of data from individual people, broader use of data not only by scientists but also by clinicians and individuals, the global reach of genomic applications and diverse national privacy and research ethics laws, and the rising prominence of a diverse commercial genomics sector. The Global Alliance for Genomics and Health was established to enable the data sharing that is essential for making meaning of genomic variation. Data-sharing policies and practices will continue to evolve as researchers, health professionals, and individuals strive to construct a global medical and scientific information commons.
Keywords: Patents; data sharing; sociology of science; model organisms; knowledge commons; science policy
Rights: Copyright © 2017 Robert Cook-Deegan et al. This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See credit lines of images or other third party material in this article for license information.
DOI: 10.1146/annurev-genom-083115-022515
Published version: http://dx.doi.org/10.1146/annurev-genom-083115-022515
Appears in Collections:Genetics publications

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