This dataset contains the National Statistics Postcode Lookup (NSPL) for the United Kingdom. The NSPL relates current postcodes to a range of current statutory administrative, electoral, health and other statistical geographies via ‘best-fit’ allocation from the 2011 Census output areas. It supports the production of area based statistics from postcoded data. The NSPL is produced by ONS Geography, which provides geographic support to the Office for National Statistics (ONS) and geographic services used by other organisations.

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.

On 3 July 2017, the Leader of the Council, Georgia Gould made a public commitment to publish Fire Risk Assessments for all blocks above 10 storeys in the interests of resident safety and transparency.

FRAs are inevitably technical documents so we have produced a set of Frequently Asked Questions to help the reader to interpret them. Each individual FRA is prefaced with a summary and any subsequent actions the Council has taken in response.

Cycling in Camden is becoming ever more popular with the introduction of safe, convenient and protected routes. There are several cycle counters in Camden which provide counts of cyclists a long these routes.

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 attendant part, casualties 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 contains transactional penalty charge notice data held in the London Borough of Camden's parking management system; inclusive of penalty charge notices issued by Civil Enforcement Officers on street and those issued by Civil Enforcement Officers via CCTV. Attribution includes contravention code, ticket type, street, parking restriction, vehicle category and status of case.

Where possible, the approximate location of the PCN has been captured. The 'Spatial Accuracy' column can be used to determine what level of location has been captured:

Civil Enforcement Officer GPS Location = the GPS location reported by the CEO's handheld device
Fixed CCTV Camera = the location of the CCTV camera, this could be many metres from the vehicle in contravention
Unknown = No location has been captured

The PNA looks at the current provision of pharmacies in Camden and how well they meet residents’ needs. It includes information on each of the pharmacies in the borough, including their opening hours, the types of services offered, and how frequently the services are used.

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.

This dataset contains data captured by sensors operated by London Air. This is downloaded via their API (Application Programming Interface) and filtered to only include sensors within the London Borough of Camden.