This dataset contains the Camden, Barnet, Brent, City of London, City of Westminster, Haringey and Islington extract of the OS Open Names dataset.

This dataset contains locations of Council owned trees on highways and in parks and open spaces in the borough. The data is collected during cyclical tree inspections by Camden tree officers. Each point contains tree species, height, spread, diameter at breast height (DBH), and maturity. Tree sequence number attached to each tree is site specific.

The data shows property and bid information for homes advertised by the London Borough of Camden on the Home Connections website.

This dataset contains planning applications in the London Borough of Camden dating back to 01/01/2010. Planning application extents are captured against the OS MasterMap product, due to licensing restrictions with this product, this dataset is represented as point geometry, located to the nearest postcode (derived from the OS Code-Point Open product). Attribution includes application number, development address, development description, registered date, decision date and case officer.

This dataset contains road collisions in Camden dating back to 2005. Data is provided by TfL (Transport for London) on an annual basis in three parts – this is the casualties part; some information has been added from the attendants part. Attendants and vehicles are available on the open data platform as separate datasets and they can all be joined together using the Reference column. If joined, where multiple attendants/casualties/vehicles exists for one Accident Reference there will be multiple records for the same accident. To avoid anomalies it is suggested any data analysis undertaken should use three years of data.

This dataset gives locations for all Camden Housing Estates with 20 or more units (tenanted, leasehold or non-residential) in the national grid (easting/northing) format and latitude and longitude. It is derived from the housing stock data at https://opendata.camden.gov.uk/Housing/Camden-Housing-Stock/pkzy-2qkt.

This dataset contains a list of Camden's housing stock; attributes include the property type, number of bedrooms and approximate location. Location is based on the centre point of the housing estate the property resides in; estates which contain less than twenty properties do not have a location to provide anonymity to the tenant.

The neighbourhood profiles are 22 data profiles that, collectively, cover the whole borough of Camden. The profiles contain comprehensive, verifiable and up-to-date statistics from a variety of sources about the community characteristics, assets and strengths, challenges and needs in each neighbourhood. They are designed to help the Council, other statutory partners and the VCS understand what is being delivered in small areas and the resources that already exist in each area, and identify any gaps.

The neighbourhoods are composites of lower super output areas (LSOAs), which are smaller than wards. The neighbourhoods do not conform to administrative boundaries or electoral wards. Their borders are instead based on the actual way that residents identify with particular areas and how they really move about within certain localities.

Not all car parks are Public. A map showing the location of assets containing the term "Car Park".

This dataset contains the parking bays location in the London Borough of Camden. A parking bay consists of a number of parking spaces, therefore individual parking spaces cannot be identified in this dataset, however the attribution includes the approximate length of the parking bay in metres, and the approximate number of spaces in the parking bay. Other attribution includes restriction type, times of operation, maximum stay, tariff, road name and CPZ (Controlled Parking Zone). The Easting and Northing (and Longitude and Latitude) attributes are automatically calculated based on an arbitrary node along the polyline geometry of the parking bay; the WKT (Well Known Text) attributes can be used to redraw the full extent of each parking bay using a GIS (Geographic Information System).