Murtagh Madeleine J, Turner Andrew, Minion Joel T, Fay Michaela, Burton Paul R
Data to Knowledge Research Group, School of Social and Community Medicine, University of Bristol , Bristol, United Kingdom .
Biopreserv Biobank. 2016 Jun;14(3):231-40. doi: 10.1089/bio.2016.0002. Epub 2016 May 20.
The social structures that govern data/sample release aim to safeguard the confidentiality and privacy of cohort research participants (without whom there would be no data or samples) and enable the realization of societal benefit through optimizing the scientific use of those cohorts. Within collaborations involving multiple cohorts and biobanks, however, the local, national, and supranational institutional and legal guidelines for research (which produce a multiplicity of data access governance structures and guidelines) risk impeding the very science that is the raison d'etre of these consortia. We present an ethnographic study, which examined the epistemic and nonepistemic values driving decisions about data access and their consequences in the context of the pilot of an integrated approach to co-analysis of data. We demonstrate how the potential analytic flexibility offered by this approach was lost under contemporary data access governance. We identify three dominant values: protecting the research participant, protecting the study, and protecting the researcher. These values were both supported by and juxtaposed against a "public good" argument, and each was used as a rationale to both promote and inhibit sharing of data. While protection of the research participants was central to access permissions, decisions were also attentive to the desire of researchers to see their efforts in building population biobanks and cohorts realized in the form of scientific outputs. We conclude that systems for governing and enabling data access in large consortia need to (1) protect disclosure of research participant information or identity, (2) ensure the specific expectations of research participants are met, (3) embody systems of review that are transparent and not compromised by the specific interests of one particular group of stakeholders, and (4) facilitate data access procedures that are timely and efficient. Practical solutions are urgently needed. New approaches to data access governance should be trialed (and formally evaluated) with input from and discussion with stakeholders.
管理数据/样本发布的社会结构旨在保护队列研究参与者（没有他们就没有数据或样本）的保密性和隐私，并通过优化这些队列的科学利用来实现社会效益。然而，在涉及多个队列和生物样本库的合作中，地方、国家和超国家层面的研究机构及法律指南（这些指南产生了多种数据访问治理结构和准则）有可能阻碍这些联盟存在的根本——科学本身。我们开展了一项人种志研究，该研究考察了在数据联合分析综合方法试点背景下，驱动数据访问决策的认知和非认知价值及其后果。我们展示了这种方法所提供的潜在分析灵活性是如何在当代数据访问治理下丧失的。我们识别出三种主导价值：保护研究参与者、保护研究以及保护研究者。这些价值既得到了“公共利益”论点的支持，又与之并列相对，并且每种价值都被用作促进和抑制数据共享的理由。虽然保护研究参与者对于访问权限至关重要，但决策也关注研究者希望看到他们在建立人群生物样本库和队列方面的努力以科学产出的形式得以实现。我们得出结论，大型联盟中管理和实现数据访问的系统需要：（1）保护研究参与者信息或身份的披露；（2）确保满足研究参与者的特定期望；（3）体现透明且不受某一特定利益相关者群体特殊利益影响的审查制度；（4）促进及时高效的数据访问程序。迫切需要切实可行的解决方案。应在利益相关者的参与和讨论下，试验（并进行正式评估）新的数据访问治理方法。
