Projects
Explore further details on our ongoing projects for a deeper understanding of our current initiatives.
SPRITE+ brings together people involved in research, practice, and policy with a focus on digital contexts. We are a 'one stop shop' for engagement between academic and non-academic communities - a way for these communities to connect and a platform for building collaborations across the spectrum of issues relating to security, privacy, identity and trust.
We are funded until 31 August 2027 under the Engineering and Physical Science Research Council (EPSRC) Digital Security and Resilience Theme (grant reference EP/W020408/1).
SPRITE+ is led by a consortium of five universities: University of Manchester (lead institution), Imperial College London, Lancaster University, Queen’s University Belfast, and University of Southampton. Our Management Team is supported by a multi-disciplinary group of more than 190 Expert Fellows and 24 Project Partners from different sectors, including industry, government, law enforcement, and civil society.
More info can be found on the SPRITE+ website.
DIGISURVOR is an innovative project that provides vital knowledge that enables a transformational shift in how Digital Footprint Data can be anonymised and linked to survey responses, thereby opening it up for ethically compliant secondary analysis.
The project is inter-disciplinary and brings together expertise from political science, social statistics and computer science. It will proceed in three main phases.
DIGISURVOR will make a significant substantive, methodological and ethical contribution to the use of linked survey and digital footprint data within academia and the wider survey research practitioner and user community. More generally, the project will contribute directly to furthering the ESRC Digital Footprints research agenda in terms of building the foundations for rigorous, ethical and societally relevant future research using DFD, and widening access to this new resource across the research community.
The UK Data Service is the principal repository for economic, population, and social research data in the UK. As hosts of the largest trusted digital archive of its kind, our expertise in the collection, preservation, and dissemination of quality data is the culmination of nearly sixty years of sustained investment by the Economic and Social Research Council (ESRC) in the UK’s research data infrastructure.
Meticulously curated over this period from trusted data providers including governments, the Office for National Statistics, the ESRC, and diverse other funders and data owners, our digital collection comprises nationally and internationally significant datasets such as the Census, Understanding Society, the UK Cohort Studies, the Labour Force Surveys, the Family Resources Surveys and many others.
Pioneers in data curation, data literacy and actively managing long-term access to high quality data, our expertise continues to transform social science research, teaching and learning.
More information can be found on the UKDS website.
The Survey Data Collection Methods Collaboration (SDCMC) is a response to post pandemic challenges and aims to deliver a step change in approaches to collecting population survey data in the UK to ensure that it will remain possible to carry out high quality social surveys of the kinds required by the public and academic sectors to monitor and understand society, and to provide an evidence base for policy. It does this primarily through a rigorous programme of research focused on ensuring large-scale social surveys in the UK can innovate and adapt in a changing environment and continue to deliver high quality and inclusive data.
The primary aim of the programme of work is to assess the quality implications of the most important survey design choices relevant to future UK surveys and provide good practice guidance and practical training materials, while a secondary aim is to identify promising ways to improve the capacity and skillset of both interviewers and research professionals and take steps towards making those improvements.
The SDCMC will generate a range of research and training outputs and will engage in a programme of dissemination and promotion activities. Outputs will have a strong practical orientation, consisting of good practice guidance for survey design, survey implementation, survey commissioners and survey data users, all backed up by rigorous and well-documented research and with a range of associated activities to ensure that the lessons are disseminated to all relevant stakeholders and, where appropriate, embedded in institutional practice in a timely manner. The project will also seek to enable a whole community dialogue and collaborative response to wider strategic challenges and issues, as well as incorporating a strong training and capacity building component.
This project aims to build capacity within the international data services community, by providing upskilling opportunities for UKDS staff and developing foundational level data skills modules in computational social science for the wider global community.
It establishes a community of practice to provide enhanced support to users through the lifetime of the project and beyond. Through upskilling mechanisms, this project will enhance data services capacity both in the UK and globally, enhance the careers of data service professionals, and through the establishment of a Community of Practice will contribute to a culture of lifelong learning.
This project explores the capacities of recently advanced network modelling methods in testing core social
theories: symbolic interactionism and social constructivism. and will provide the first comprehensive
quantitative test of such theories.
These new methods enable the disentangling of the complex structures that relate persons, words, and material objects in small groups of collocated individuals. This, in turn, enables cross-validation of the fundamental assumptions the two theories have regarding how cultural meanings are formed across different types of interaction, structural levels, and time spans.
The project utilised a globally unique multi-dimensional dataset that captures socio-cultural dynamics in five groups over two years. Development of statistical models for the analysis of how cultural meaning is created in society will constitute a major contribution to social science. Results of the testing of core social theories have the potential to trigger fundamental changes in social sciences and beyond.
The British Election Study (BES) is one of the longest-running election studies worldwide and the longest-running social science survey in the UK.
It has made a major contribution to the understanding of political attitudes and behaviour over nearly sixty years.
Surveys have taken place immediately after every general election since 1964.
The first study conducted by David Butler and Donald Stokes in 1964, transformed the study of electoral behaviour in the UK.
Since then the BES has provided data to help researchers understand changing patterns of party support and election outcomes.
Immigration is a major political issue, with increasing media coverage, rising anti-immigration sentiment, and the rise of anti-immigration political parties.
The issue of migration sits centrally within the wider debate about ethnic and religious diversity and its effects on social cohesion.
We are still, though, a long way from understanding these issues and their potential consequences.
They seem to rest on beliefs about national identity and ethnicity, but cannot be divorced from the effects of social class, education, economic competition, and inequality, as well as the influences of geographical and social segregation, social structures, and institutions.
This project will integrate two very different disciplines, social science, and complexity science, to gain a new understanding of these complex, social issues.
It will do this by building a series of computer simulation models of these social processes.
One could think of these as serious versions of the Sims computer games, programmes that track the social interactions between many individuals.
Such simulations allow ‘what if’ experiments to be performed so that a deeper understanding of the possible outcomes for society as a whole can be established based on the interactions of many individuals.