Rights, interests and expectations: Indigenous perspectives on unrestricted access to genomic data

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Abstract

<p class="first" id="d2585455e631">Addressing Indigenous rights and interests in genetic resources has become increasingly challenging in an open science environment that promotes unrestricted access to genomic data. Although Indigenous experiences with genetic research have been shaped by a series of negative interactions, there is increasing recognition that equitable benefits can only be realized through greater participation of Indigenous communities. Issues of trust, accountability and equity underpin Indigenous critiques of genetic research and the sharing of genomic data. This Perspectives article highlights identified issues for Indigenous communities around the sharing of genomic data and suggests principles and actions that genomic researchers can adopt to recognize community rights and interests in data. </p>

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Integrated knowledge translation (IKT) in health care: a scoping review

Anna R Gagliardi, Whitney Berta, Anita Kothari … (2016)

Background Integrated knowledge translation (IKT) refers to collaboration between researchers and decision-makers. While advocated as an approach for enhancing the relevance and use of research, IKT is challenging and inconsistently applied. This study sought to inform future IKT practice and research by synthesizing studies that empirically evaluated IKT and identifying knowledge gaps. Methods We performed a scoping review. We searched MEDLINE, EMBASE, and the Cochrane Library from 2005 to 2014 for English language studies that evaluated IKT interventions involving researchers and organizational or policy-level decision-makers. Data were extracted on study characteristics, IKT intervention (theory, content, mode, duration, frequency, personnel, participants, timing from initiation, initiator, source of funding, decision-maker involvement), and enablers, barriers, and outcomes reported by studies. We performed content analysis and reported summary statistics. Results Thirteen studies were eligible after screening 14,754 titles and reviewing 106 full-text studies. Details about IKT activities were poorly reported, and none were formally based on theory. Studies varied in the number and type of interactions between researchers and decision-makers; meetings were the most common format. All studies reported barriers and facilitators. Studies reported a range of positive and sub-optimal outcomes. Outcomes did not appear to be associated with initiator of the partnership, dedicated funding, partnership maturity, nature of decision-maker involvement, presence or absence of enablers or barriers, or the number of different IKT activities. Conclusions The IKT strategies that achieve beneficial outcomes remain unknown. We generated a summary of IKT approaches, enablers, barriers, conditions, and outcomes that can serve as the basis for a future review or for planning ongoing primary research. Future research can contribute to three identified knowledge gaps by examining (1) how different IKT strategies influence outcomes, (2) the relationship between the logic or theory underlying IKT interventions and beneficial outcomes, and (3) when and how decision-makers should be involved in the research process. Future IKT initiatives should more systematically plan and document their design and implementation, and evaluations should report the findings with sufficient detail to reveal how IKT was associated with outcomes. Electronic supplementary material The online version of this article (doi:10.1186/s13012-016-0399-1) contains supplementary material, which is available to authorized users.

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IMG/M: integrated genome and metagenome comparative data analysis system

I-Min Chen, Victor Markowitz, Ken Chu … (2016)

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support for examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review (ER) companion system (IMG/M ER: https://img.jgi.doe.gov/mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.