The next London Borough Data Partnership meeting will be held on 29 March at City Hall, the headquaters of the Greater London Authority.

A full agenda has been pulled together and will include :

Theo Blackwell, Chief Digital Officer, GLA

The search for HMOs : Can machine learning help? : data processes and techniques explored to identify “Houses in Multiple Occupation” within Barking and Dagenham. Including their experience of participation in the NESTA/GLA HMO machine learning pilot and further work they have since undertaken. Pye Nyunt and Phil Canham, LB of Barking and Dagenham

Clean Air London : London’s air quality, although improving, still has areas which exceed EU safe NO2 limits. Ollie and Theo are working to bring together a wide range of heterogeneous sensor networks to build machine learning algorithms that can accurately predict air pollution at a high spatial-temporal resolution. This will be used to establish the most effective locations for new sensors and to inform policy such that key areas and times can be targeted. Ollie Hamelijnck and Theo Damoulas, Alan Turing Institute

London Office of Data Analytics : hear the latest from the GLA's City Data team on the City Datastore, Data Sharing Agreements, Data Academy and other pan-London data project initiatives

Places are limited to employees of London Government organisations. Due to the popularity of these events, please coordinate attendance with colleagues from your organisation to help us ensure full London-wide representation.