Responsible Governance for a Food and Nutrition E-Infrastructure: Case Study of the Determinants and Intake Data Platform - Timotijevic, Lada; Carr, Indira; De La Cueva, Javier; Eftimov, Tome; Hodgkins, Charo E.; Koroušić Seljak, Barbara; Mikkelsen, Bent E.; Selnes, Trond; Van't Veer, Pieter; Zimmermann, Karin (Frontiers in Nutrition, 2022)
Distributed computing infrastructures – commonly known as e-infrastructures - provide researchers shared access to large data collections enabled through advanced Information Communication Technology (ICT) tools for data analysis, large-scale computing resources, and high-performance visualisation. Although the consumer food choices and dietary behaviour are of direct relevance to public health, prevention, health promotion, environmental sustainability and socioeconomic impacts of the food system, the scientific domain of food consumption and its relation to health and sustainability is not yet facilitated by a well-supported e-infrastructure. Recently, a network of scientists has been established to develop an international Food Nutrition Health Research Infrastructure, which will exist as an e-infrastructure that enables innovative science in the domain of food and health. As part of this e-infrastructure, a dedicated Determinants and Intake (DI) Data Platform will utilise the cutting-edge ICT and new technology such as smart phones, APPs, sensors, internet of things and big data to facilitate innovation and developments in food consumer science. One of the key challenges for implementation of the DI Data Platform is how to develop responsible governance that observes the ethical and legal frameworks of big data research and innovation, whilst simultaneously capitalising on huge opportunities offered by open science and the use of big data in food consumer science research. The focus of the current paper is to examine how to develop responsible governance of food consumer science e-infrastructure using the case study DI Data Platform. We address this challenge with a specific focus on four key governance considerations: data type and technology; data ownership and intellectual property; data privacy and security; and institutional arrangements for ethical governance. The paper concludes with a set of responsible research governance principles that can inform the implementation of DI Data Platform, and in particular: consider both individual and group privacy; monitor the power and control (e.g. between the scientist and the research participant) in the process of research; question the veracity of new knowledge based on big data analytics; understand the diverse interpretations of scientists’ responsibility across different jurisdictions.