BackgroundGenomic and biosocial research data about individuals is rapidly proliferating, bringing the potential for novel opportunities for data integration and use. The scale, pace and novelty of these applications raise a number of urgent sociotechnical, ethical and legal questions, including optimal methods of data storage, management and access. Although the open science movement advocates unfettered access to research data, many of the UK’s longitudinal cohort studies operate systems of managed data access, in which access is governed by legal and ethical agreements between stewards of research datasets and researchers wishing to make use of them. Amongst other things, these agreements aim to respect the reasonable expectations of the research participants who provided data and samples, as expressed in the consent process. Arguably, responsible data management and governance of data and sample use are foundational to the consent process in longitudinal studies and are an important source of trustworthiness in the eyes of those who contribute data to genomic and biosocial research.MethodsThis paper presents an ethnographic case study exploring the foundational principles of a governance infrastructure for Managing Ethico-social, Technical and Administrative issues in Data ACcess (METADAC), which are operationalised through a committee known as the METADAC Access Committee. METADAC governs access to phenotype, genotype and ‘omic’ data and samples from five UK longitudinal studies.FindingsUsing the example of METADAC, we argue that three key structural features are foundational for practising responsible data sharing: independence and transparency; interdisciplinarity; and participant-centric decision-making. We observe that the international research community is proactively working towards optimising the use of research data, integrating/linking these data with routine data generated by health and social care services and other administrative data services to improve the analysis, interpretation and utility of these data. The governance of these new complex data assemblages will require a range of expertise from across a number of domains and disciplines, including that of study participants. Human-mediated decision-making bodies will be central to ensuring achievable, reasoned and responsible decisions about the use of these data; the METADAC model described in this paper provides an example of how this could be realised.

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SummaryBackgroundIncreases in portion size are thought by many to promote obesity in children. However, this relationship remains unclear. Here, we explore the extent to which a child's BMI is predicted both by parental beliefs about their child's ideal and maximum portion size and/or by the child's own beliefs.MethodsParent–child (5–11 years) dyads (N = 217) were recruited from a randomized controlled trial (n = 69) and an interactive science centre (n = 148). For a range of main meals, parents estimated their child's ‘ideal’ and ‘maximum tolerated’ portions. Children completed the same tasks.ResultsAn association was found between parents' beliefs about their child's ideal (β = .34, p < .001) and maximum tolerated (β = .30, p < .001) portions, and their child's BMI. By contrast, children's self‐reported ideal (β = .02, p = .718) and maximum tolerated (β = −.09, p = .214) portions did not predict their BMI. With increasing child BMI, parents' estimations aligned more closely with their child's own selected portions.ConclusionsOur findings suggest that when a parent selects a smaller portion for their child than their child self‐selects, then the child is less likely to be obese. Therefore, public health measures to prevent obesity might include instructions to parents on appropriate portions for young children.

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