Article

Share and share alike: deciding how to distribute the scientific and social benefits of genomic data.

Department of Anthropology, University of Oklahoma, Norman, Oklahoma 73019, USA.
Nature Reviews Genetics (Impact Factor: 39.79). 09/2007; 8(8):633-9. DOI: 10.1038/nrg2124
Source: PubMed

ABSTRACT Emerging technologies make genomic analyses more efficient and less expensive, enabling genome-wide association and gene-environment interaction studies. In anticipation of their results, funding agencies such as the US National Institutes of Health and the Wellcome Trust are formulating guidelines for sharing the large amounts of genomic data that are generated by the projects that they sponsor. Data-sharing policies can have varying implications for how disease susceptibility and drug-response research will be pursued by the scientific community, and for who will benefit from the resulting medical discoveries. We suggest that the complex interplay of stakeholders and their interests, rather than single-issue and single-stakeholder perspectives, should be considered when deciding genomic data-sharing policies.

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    • "In light of the increasing availability of genomic data, data sharing and open access policies were promoted by large international consortia in order to maximize the use of generated datasets and enhance the statistical power of studies. Funding organizations also drafted policies to expand accessibility and use of datasets by requiring researchers to incorporate data sharing plans in their fund-seeking proposals (Foster and Sharp 2007; NIH 2014). As a consequence, central on-line databases such as the database of Genotypes and Phenotypes (dbGaP) a and the European Genome-phenome Archive b have been designated to host vast volumes of data either in a publicly accessible or controlled fashion. "
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    ABSTRACT: In order to study the relationship between genes and diseases, the increasing availability and sharing of phenotypic and genotypic data have been promoted as an imperative within the scientific community. In parallel with data sharing practices by clinicians and researchers, recent initiatives have been observed in which individuals are sharing personal genomic data. The involvement of individuals in such initiatives is facilitated by the increased accessibility of personal genomic data, offered by private test providers along with availability of online networks. Personal webpages and on-line data sharing platforms such as Consent to Research (Portable Legal Consent), Free the Data, and Genomes Unzipped are being utilized to host and share genotypes, electronic health records and family history uploaded by individuals. Although personal genomic data sharing initiatives vary in nature, the emphasis on the individuals' control on their data in order to benefit research and ultimately health care has seen as a key theme across these initiatives. In line with the growing practice of personal genomic data sharing, this paper aims to shed light on the potential challenges surrounding these initiatives. As in the course of these initiatives individuals are solicited to individually balance the risks and benefits of sharing their genomic data, their awareness of the implications of personal genomic data sharing for themselves and their family members is a necessity. Furthermore, given the sensitivity of genomic data and the controversies around their complete de-identifiability, potential privacy risks and harms originating from unintended uses of data have to be taken into consideration.
    03/2015; 11(3). DOI:10.1186/s40504-014-0022-7
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    ABSTRACT: Dissemination, reuse and sharing of digital resources is technically and culturally challenging in neu- roscience - particularly in the area of Multi-Electrode Array (MEA) recording. Large, complex datasets are typical, with a heterogeneous range of data and code formats. The CARMEN project (http://www.carmen.org.uk/) aims to enable broad sharing or resources, through provision of a secure, online environment for data analysis, and curation of data, analysis code and experimental protocols.
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