Place
Places frame how people live their lives – they are settings where we work, shop, socialise, and move; they influence our decisions, lifestyles, and health.
The Challenge
Places are recognised as central to the future of UK policymaking, the current government’s plan to “Power Up Britain” acknowledges that different areas have different challenges, and high levels of geographic inequality which require local solutions to tackle.
Livability, wellbeing, and health outcomes are determined by a broad set of interlinking factors. However, there is a lack of joined up evidence in different domains as it relates to places, leading to conclusions that are siloed within disparate thematic areas.
Good quality data that provide a joined-up view of the complexity of places are essential for delivering positive change and reducing place-based inequalities.
HASP’s Approach
HASP will work with data owners to curate a collection of datasets which represent the composition of places as it relates to how people behave, and the services, infrastructure and environment which people have access to. We will serve these data to the research community in research ready formats.
HASP will support place-based research, with a focus on health and sustainability, which goes beyond the current state-of-the-art.
This will be achieved by providing access to data that would otherwise be difficult or impossible for researchers to obtain; and by supporting and encouraging research that is cross-cutting, to eliminate the silos that currently exist to provide a deeper understanding of place based challenges and inequalities.
Economic inclusion across Great Britain
SIPHER
A multifaceted dataset for researchers and policy actors to explore the extent and nature of economic inclusion across Great Britain.
Projects
Generating synthetic mobility trajectories for privacy-preserving data sharing
Despite major safeguards in place around the storage and use of fine-grained mobility data, there remain concerns about the risk to individual privacy, and questions about the continued willingness of the public to permit data for use in research.
This project develops methods that better capture spatial, temporal, and contextual heterogeneity in synthetic data, essential for local level intelligence, derived from smart data.
Uncovering e-food deserts
The e-food deserts index (EFDI) is a multi-dimensional composite index for Great Britain which measures the extent to which neighbourhoods exhibit characteristics associated with food deserts across four key drivers of groceries accessibility.
Developed by Dr Andy Newing, input data are drawn from a range of sources including the Census and existing indicators of deprivation and accessibility at the neighbourhood level. It also incorporates a number of custom-derived indicators of food store accessibility, consumer behaviours and availability of groceries e-commerce drawn from our own modelling.
