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Systematic observation is a promising unobtrusive method of assessing human behavior in urban environments without many issues typically associated with self-report measures (e.g., recall bias, low response rates). Improvements in video camera technologies make it more feasible for researchers to conduct systematic observation, which could reduce the time, labor, and cost to facilitate high-quality observational research in urban environments at scale. However, there are important ethical and information governance challenges driven by data protection laws, which discourage many researchers from using camera-based observation methods. The European Union General Data Protection Regulation is a leading global standard for data protection. Drawing on our experiences of conducting three studies using video cameras in public spaces, we discuss how to conduct this kind of research in line with General Data Protection Regulation requirements. The paper outlines issues concerning data protection, privacy, informed consent, and confidentiality, and how we addressed them. In doing this, the paper provides support for responsible use of camera-based observation methods, which will be of value to researchers, ethics committees, and funders. Outlining how to use video cameras responsibly will enable more research to be conducted that, in turn, will build the case for its benefits to researchers and society. [ABSTRACT FROM AUTHOR]

Biomedical innovation is often rewarded by exclusive proprietary rights such as patents. In the case of gene editing, induced pluripotent stem cells, and three‐dimensional (3D) bioprinting (here described as biomodifying technologies), the limitations of the patent system come into stark relief, generating both technical and political doubts. Generally, political and technological limitations are supposed to be solved with so‐called good governance, based on some principles. We focus on three of such governance principles (participation, accountability, and transparency) to show how they have been weakened, instead of strengthened, by the current patent system. We demonstrate that although patent applications are submitted by both public and private players, the latter have imposed a growing dominance in gene editing, induced pluripotent stem cells, and 3D bioprinting, disseminating their aggressive and exclusive strategies. As a consequence, a logic of experimentality tends to prevail where the three fundamental governance principles fail to be enacted. [ABSTRACT FROM AUTHOR]

Biomodifying technologies—such as gene editing, induced pluripotent stem cells, and bioprinting—are being developed for a wide range of applications, from pest control to lab-grown meat. In medicine, regulators have responded to the challenge of evaluating modified 'natural' material as a therapeutic 'product' by introducing more flexible assessment schemes. Attempts have also been made to engage stakeholders across the globe on the acceptable parameters for these technologies, particularly in the case of gene editing. Regulatory flexibility and stakeholder engagement are important, but a broader perspective is also needed to respond to the potential disruption of biomodification. Our case-study technologies problematize basic ideas—such as 'nature', 'product', and 'donation'—that underpin the legal categories used to regulate biotechnology. Where such foundational concepts are rendered uncertain, a socially responsive and sustainable solution would involve exploring evolutions in these concepts across different societies. We suggest that the global observatory model is a good starting point for this 'Adaptive Societal Governance' approach, in which a self-organizing network of scholars and interested parties could carry out the multi-modal (meta)analyses needed to understand societal constructions of ideas inherent to our understanding of 'life'. [ABSTRACT FROM AUTHOR]

Data platforms represent a new paradigm for carrying out health research. In the platform model, datasets are pooled for remote access and analysis, so novel insights for developing better stratified and/or personalised medicine approaches can be derived from their integration. If the integration of diverse datasets enables development of more accurate risk indicators, prognostic factors, or better treatments and interventions, this obviates the need for the sharing and reuse of data; and a platform-based approach is an appropriate model for facilitating this. Platform-based approaches thus require new thinking about consent. Here we defend an approach to meeting this challenge within the data platform model, grounded in: the notion of ‘reasonable expectations’ for the reuse of data; Waldron’s account of ‘integrity’ as a heuristic for managing disagreement about the ethical permissibility of the approach; and the element of the social contract that emphasises the importance of public engagement in embedding new norms of research consistent with changing technological realities. While a social contract approach may sound appealing, however, it is incoherent in the context at hand. We defend a way forward guided by that part of the social contract which requires public approval for the proposal and argue that we have moral reasons to endorse a wider presumption of data reuse. However, we show that the relationship in question is not recognisably contractual and that the social contract approach is therefore misleading in this context. We conclude stating four requirements on which the legitimacy of our proposal rests. [ABSTRACT FROM AUTHOR]

Responsible Research and Innovation ('RRI') is a cross-cutting priority for scientific research in the European Union and beyond. This paper considers whether the way such research is organised and delivered lends itself to the aims of RRI. We focus particularly on international consortia, which have emerged as a common model to organise large-scale, multi-disciplinary research in contemporary biomedical science. Typically, these consortia operate through fixed-term contracts, and employ governance frameworks consisting of reasonably standard, modular components such as management committees, advisory boards, and data access committees, to co-ordinate the activities of partner institutions and align them with funding agency priorities. These have advantages for organisation and management of the research, but can actively inhibit researchers seeking to implement RRI activities. Conventional consortia governance structures pose specific problems for meaningful public and participant involvement, data sharing, transparency, and 'legacy' planning to deal with societal commitments that persist beyond the duration of the original project. In particular, the 'upstream' negotiation of contractual terms between funders and the institutions employing researchers can undermine the ability for those researchers to subsequently make decisions about data, or participant remuneration, or indeed what happens to consortia outputs after the project is finished, and can inhibit attempts to make project activities and goals responsive to input from ongoing dialogue with various stakeholders. Having explored these challenges, we make some recommendations for alternative consortia governance structures to better support RRI in future. [ABSTRACT FROM AUTHOR]

Over the last decade dramatic advances have been made in both the technology and data available to better understand the multifactorial influences on child and adolescent health and development. This paper seeks to clarify methods that can be used to link information from health, education, social care and research datasets. Linking these different types of data can facilitate epidemiological research that investigates mental health from the population to the patient; enabling advanced analytics to better identify, conceptualise and address child and adolescent needs. The majority of adolescent mental health research is not able to maximise the full potential of data linkage, primarily due to four key challenges: confidentiality, sampling, matching and scalability. By presenting five existing and proposed models for linking adolescent data in relation to these challenges, this paper aims to facilitate the clinical benefits that will be derived from effective integration of available data in understanding, preventing and treating mental disorders. [ABSTRACT FROM AUTHOR]

The EU General Data Protection Regulation (‘GDPR’) seeks to balance the public interest in research with privacy rights of individuals, in particular, through research exemptions and safeguards set out in Article 89. While this affords Member States limited opportunities to modify the application of the GDPR at a national level, including for data processing that is necessary for the performance of a task carried out in the public interest, it is necessary for national approaches to conform with Article 89 safeguards where appropriate. One development of interest to the research community in the UK is a statutory power for public authorities to disclose administrative data for research under the Digital Economy Act 2017 (DEA). This article uses the DEA as a case study for analysis of the GDPR provisions governing processing of data for research purposes—including de-identification—and draws on human rights norms and jurisprudence to interpret the broad requirement for ‘appropriate safeguards’ for the ‘rights and freedoms of the data subject’ under Article 89. This analysis is important for data controllers seeking to meet their obligations under the UK framework and for those in other EU Member States considering the development of similar national provisions for data processing for research purposes. [ABSTRACT FROM AUTHOR]