skip to content


a network for developers and users of imaging and analysis tools

Cambridge Big Data is a Strategic Research Initiative of the University of Cambridge.

  • University of Cambridge Strategic Research Initiatives and Networks build on areas of existing research strength by bringing together a critical mass of expertise from across the Schools, with four key aims: to address large-scale multi-disciplinary research challenges; to increase the University's capacity to influence national and international research, policy and funding agendas; to strengthen internal cross-disciplinary research collaborations; and to provide a platform for large-scale funding applications, recruitments and international research partnerships.

    The term Big Data has come to describe a wide variety of datasets and techniques for dealing with them. The underlying datasets may be structured with pre-determined schemas, or unstructured like social media data; they are often large and growing rapidly due to high data flow rates, for example streaming data from sensors or machines in real-time, they may be in a variety of formats from plain text to compressed video and have variable useful lifetimes. The data is often complex, especially when composed of large merged datasets that reduce the need for pre-sampling and provide increased scope for correlations to be found. The unique characteristics (often captured as Volume, Velocity, Variety) of Big Data datasets introduce new challenges in areas such as data transfer, storage, processing, analysis and visualization, and render traditional approaches in these areas inadequate especially due to the need to be agile and efficient at keeping datasets correct, accurate and relevant.

    There are wider challenges than just the technical, and Big Data is increasingly used as an umbrella term to also include the connected societal, ethical and data science issues that arise. When personal data is collected, stored and processed it can, especially when used in combination with other datasets, lead not just to improved products and business processes, but also to (unexpected) losses of privacy. Issues of compliance and accountability, already made harder by the growing reliance on distributed (cloud) resources and services, become even more difficult to track with these new datasets. Furthermore, getting the most out of them relies on the problems to be solved being clearly defined, the results being interpreted correctly and then clearly communicated; each step can become a challenge to effectiveness.

    To make contact with Cambridge Big Data researchers please email Clare Dyer-Smith, Cambridge Big Data Co-ordinator (email: or one of our Theme Champions for the area you are interested in here.

    University colleagues are invited to join CBD here.

    External enquirers are welcome to join our mailing list here.