Data Collection surrounds our modern lives. From sensors in smartphones to connected cars linking with roadside monitors to read air pollution, data is everywhere. There are over 20 billion devices currently connected to the internet. Cisco predicts this will be 500 billion by 2030. We recognise the challenge this poses for modern Statistical methods. They are poor and outdated. They cannot analyse the data effectively and most of this streamed data which could be used for societal and economical good, is simply being lost.
The ‘StatScale: Statistical Scalability for Streaming Data’ programme is working to develop new ways to interpret this data. A collaboration between both Lancaster University and University of Cambridge, involves research with industrialpartners including AstraZeneca, BT and Shell UK, and includes £2.8m funding from EPSRC. StatScale benefits from its significant partnerships with industry and these collaborations help inform StatScale’s research agenda and support the research to make a direct economic and societal benefit.
StatScale’s theoretical and methodological work will form the basis of the next generation of scalable statistical algorithms. This is essential to ensure the UK’s competitive edge in science and technological industries. From smart watches to instrumented oil fields, ScatScale will have individual, national and global effects. The programme is led by Professors Idris Eckley and Paul Fearnhead from Lancaster University, and Professor Richard Samworth and Dr Rajen Shah at the University of Cambridge.