Imagine if you could gather data from thousands of mobile data points reacting to the environment around them? That's what our Research Software Engineers have been helping to do and in more than one language thanks to an international collaboration!

As part of the Data Science Research Partnership between BBC R&D and the University of Manchester, one of our research software engineers (RSE), Josh Woodcock, spent 3 months working with BBC R&D to develop a way to visualise click data from an internal trial of the Cook-Along Kitchen Experience (CAKE). Involved in the project were Jonathan Carlton (PhD student with BBC R&D and University of Manchester), Andy Brown (BBC R&D), John Keane and Caroline Jay (University of Manchester).

Research IT has recently been involved in an exciting new use case which aimed to help people with a chronic lung disease self-report the impact of their symptoms on their wellbeing and to view their data.

Traditionally the first step in interpreting video is to code it into a form that can be analysed systematically. The coding process is currently performed manually, and it can be slow and difficult, and biased by subjectivity. David Mawdsley (Research IT) recently presented a poster at the first “Advances in Data Science” conference explaining how we are helping Dr Caroline Jay’s group develop a way to quickly code human behaviours allowing the rapid analysis of hours of video.

Two members of Research IT are co-authors on a recently published paper in BMC Ecology. The paper describes the development and implementation of "BioVeL" - a virtual laboratory for data analysis and modelling in biodiversity science and ecology.