The Partners

Leeds Institute for Data Analytics


Growing through support from a network of local and national collaborators, LIDA is becoming a major powerhouse for research, civic engagement and business growth in the North of England and beyond.

Established in 2014, with major investments from the UK Research Councils and the University of Leeds, LIDA has developed state of the art physical and IT infrastructures to raise the bar in standards of data quality, access, protection and exploitation.
There is a growing movement around the world to ensure the effective use of vast data collections to drive research, policy development and public good initiatives. The Leeds Institute for Data Analytics brings together applied research groups and data scientists from all disciplines, opening up new opportunities to understand health and human behaviour and casting light on the action required to tackle a wide range of social and environmental problems.

Connecting academic research with external partners in business, government and the third sector; LIDA is matching the world class capabilities of University research with the needs and opportunities of local organisations.

Sheffield Methods Institute


The University of Sheffield is a member of the Russell Group of leading UK research universities. It has an outstanding reputation for the development and application of research methods in Social Science. This activity is now being focused through the Sheffield Methods Institute (SMI) of which Prof Gwilym Pryce is the Director. The SMI has established itself an as interdisciplinary methods hub for the development and application of innovative methods in social research encompassing a broad spectrum of substantive and methods-based disciplines at Sheffield. The SMI aims to develop an interdisciplinary community of methods-orientated researchers with links to a wide range of departments including the iSchool (Information School), the Centre for Criminological Research, the Advanced Computing Research Centre, Department of Computer Science, the Centre for Signal Processing and Complex Systems among others. The SMI is based in the Faculty of Social Sciences at Sheffield which is currently ranked in the top ten for citations in the UK. In the Research Excellence Framework 2014, 80% of the Faculty’s research assessed was graded as world leading or internationally excellent, with the majority of the Faculty’s submissions ranked in the top ten, of which 5 were in the top five.

Liverpool Geographic Data Science Lab


The Geographic Data Science Lab at the University of Liverpool are an interdisciplinary research centre interested in the development and application of new methods at the intersection of Geographic Information Science, Spatial Analysis and Applied Geocomputation. As a group we hold various substantive interests related to the form, function or dynamics of human activities and their contexts.

Manchester Data Science Institute


Manchester’s Data Science Institute acts as an access point to the University’s expertise in data science, facilitates interactions between data science researchers and problem holders, owns the University’s data science strategy, and will deliver sustainable support for the community.

Manchester has an engaged data science community of almost 250 investigators, with methodologists embedded in Schools across the University addressing problems in extracting meaning from data, managing data volume, the variety of data used in analyses, the velocity with which it is produced and the veracity of those data.

Data science has a home in all three of the University’s faculties (Science & Engineering; Humanities; Biology, Medicine & Health Sciences) supported across the whole data life cycle by work in the schools of Computer Science and Mathematics. From information management, through analytics, to practical applications. This creates a virtuous circle, where challenging real-world problems drive the methodology research agenda, whilst providing a natural driver for building new algorithms and methods.