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CityX: ideas into action

Data Science Fellowships

See how we tackle city challenges like poor air quality and housing conditions by involving data science experts through our Data Science Fellowship programme.

Helping city councils unlock and make better use of their data is key to solving city challenges, to create a better urban environment for all.

Our Data Science Fellowship programme connects UK data scientists with city authorities to do just that.

Local authorities often don’t have access to the budget or skills to fund data-driven innovations. We wanted to help them develop greater confidence in working with data innovators and create new market opportunities for innovative UK companies.

Our first data science fellows have shown that bringing specialist data science skills into councils to address real life city challenges can deliver great results.

If you are a local authority or city council with a unique challenge or one that is common to other councils, we can help you access the expertise of a data scientist. To find out more about this programme get in touch.

If you’re a company with an innovation that could help councils unlock their data or use it more effectively, get in touch.

Plus – check out our Data Science Fellowship programme FAQs and our stories about how Data Science Fellows helped to improve air quality in Newcastle upon Tyne and housing conditions in Nottingham.

 

What our first two Data Science Fellows achieved

Improving air quality in Newcastle Upon Tyne

Annual averages for nitrogen dioxide have exceeded EU limits in Newcastle upon Tyne, along with many UK city regions, for the last four years.

In Newcastle, our Fellow, Dr. Raquel Vaz, worked on a data challenge about air quality. Working in collaboration with the City Council and Newcastle University’s Urban Observatory, the aim was to determine the impact of restricting vehicle access on a key city centre link, Blackett Street.

The outcomes:

  • Using time series analysis and geospatial statistics, Dr Vaz demonstrated that temporary road closures significantly improve air quality in the centre of Newcastle during selected weekends.

  • She created a roadmap for potential future analysis and future data sharing, which could lead to systematic improvements in air quality in the long term

Dr Vaz’s research also highlighted that to assess the full economic impact of such a policy, data scientists would need access to further sources of data held by the council and others, such as people movement data, vehicle counts and vehicle journey times.

The council saw a huge value in the transparency of data analysis and the idea of an independent view of the city system through data.

Improving housing conditions in Nottingham

Ensuring private rental housing is in good condition for tenants In Nottingham. Fellow, Dr. David Hopkinson worked with the City Council to look at the council’s landlord licensing scheme.

Using a machine learning approach known as ‘Active Learning’, Dr Hopkinson and the Geographical Information Systems team in Nottingham were able to combine data science and expert domain knowledge to identify private rental properties that were unlikely to be registered with the licencing scheme but needed to be.

Check out David’s presentation.

The outcomes:

  • The information generated helped to more efficiently identify homes that may not have signed up to the landlord licensing scheme and were considered most vulnerable.
  • Early estimates suggest that by taking this approach, the council’s Safer Housing team could identify up to six times more unregistered rental properties over a two year period.
  • Through this Dr Hopkinson has helped Nottingham City Council to enforce a new licensing scheme that ensures privately rented properties are in a good condition for tenants.

If you are a local authority or city council with a unique challenge or one that is common to other councils, we can help you access the expertise of a data scientist. To find out more about this programme get in touch.

If you’re a company with an innovation that could help councils to unlock their data or use it more effectively, get in touch.

Collaborating on this programme has shown us that data techniques such as machine learning can add a further dimension to projects and that we can apply similar techniques to other areas of licensing. This fits with our smart city ambitions, and may increase our work with universities and other organisations in this sector.

– Laura Pullen, Business Development Manager, Geographical Information Services (GIS), Nottingham City Council

There is now an opportunity to roll out this technology to other towns and cities to improve housing conditions for tenants.

Our first Fellows have shown that bringing the knowledge and expertise of data scientists into solving a real life city challenge can deliver great benefits.

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