Projects

Business man commuter with smartphone on the way to work outdoors in city, coronavirus concept.

Case study: responding to the coronavirus pandemic using aggregated BT mobility data

To support the national fight against coronavirus (COVID-19) in March 2020, BT made aggregate, anonymised mobility data available to the UK Government. We quickly turned this into daily updates, with only one day’s delay between activity and the reporting of it.

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A concept image of the novel coronavirus.

Use of hybrid data to understand the community-level influences on coronavirus (COVID-19) incidence

Understanding and monitoring the major influences on COVID-19 infection numbers in communities is essential to inform policy making and evaluate the impact of non-pharmaceutical interventions. We have developed a community-level analysis by assembling a large set of static and dynamic data for England.

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Worker shortages: A window on labour demand during the coronavirus (COVID-19) pandemic

The UK’s exit from the European Union created uncertainty about workers across a range of sectors, exacerbated by concerns over workers leaving the country and the impact on labour supply. The coronavirus (COVID-19) pandemic created additional and sudden changes, with sectors being affected heterogeneously and demand switching from services to goods.

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Technical report: Predicting cattle camp locations in South Sudan from Sentinel 2 satellite imagery

Cattle are central to many people’s livelihoods in South Sudan, but there are very few recent data on the number of animals and their geographic distribution. Building on previous work, this blog explores new methods, based on convolutional neural networks, that can better distinguish cattle camps from similar landscape features.

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The Data Science Campus – five years of data science for public good

On 27 March 2017, with an audience of UK and international data science leaders from across the public, private and academic sectors, a team of 8, some brilliant presentations, and a lot of excitement, the Data Science Campus was launched. 5 years later, Louisa Nolan shares what have we learned along the way.

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Employing data science to analyse the use of preferential tariffs in free trade agreements

Preference utilisation rates (PURs) measure the extent to which UK businesses make use of the zero or reduced tariffs available via free trade agreements (FTAs). In this work, we study the take-up of preferential tariffs by UK businesses between 2009 and 2019 and examine their trends and patterns.

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Technical Report: Project Mertz—novel use of historical RAF flight safety records

Part of our mission at the Data Science Campus (DSC) is to build data science capability across the public sector. In this project, which grew out of our Data Science Accelerator programme, we worked with the Royal Air Force (RAF) to help upskill their staff in the Python programming language and natural language processing (NLP) methods.

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