LAUSR

The ESRC Strategic Network for Obesity (here after referred to as the Network) was established in November 2015, with funding from the Economic and Social Research Council in the UK. The primary aim of the Network is to exploit new and emerging forms of data to catalyse an approach to obesity research using big data, which is transdisciplinary, cross-institutional, multi-sector and international. Obesity has been characterised as a wicked problem [1], which intersects multiple domains including lifestyle and behaviour, local environments, economic circumstances, socio-demographic characteristics and family circumstances. In the past, it has been difficult or impossible for researchers to access suitable intelligence about many of these drivers. The Network has been explicitly focused on identification of the measures necessary to harness new datasets from multiple sources, for example, consumer behaviour, lifestyle and activity, and health outcomes. Initial steps have been taken to frame these sources with data science methods to embrace the notion of complex systems approaches in obesity— producing new proposals to generate evidence for research and policy evaluation. The embedded value within these data and the co-production with public and third sector participants makes this an exceptional opportunity to ensure output is of outstanding policy relevance. Over the past 3 years, a series of events have been hosted in diverse locations, each combining open research seminars with developmental activities in a workshop format, which have synthesised the interests of individual Network members. The Network engages a variety of academics, policy makers, and industry partners, and fosters an inclusive environment with capacity building at its heart by explicit sharing of organisational tasks and contributions from a range of career stages. This is critically important in an area developing as quickly as the field of big data and obesity research where experience of the application area is crucial in equal measures with a fresh approach and new methods development.