Data Lab is an in-Hub AI powered application created for exploring and understandning spatial data directly in the browser. It helps visualise the search results on an interactive map. Data Lab removes the need for GIS expertise while still supporting advanced spatial analysis across planning, transport, environment, demographics, and urban infrastructure.

Using Data Lab

Data Lab is designed for exploring and understanding London through location-based data. It supports analysis across planning, transport, environment, demographics, and urban infrastructure.

Typical use cases include identifying services within areas, analysing accessibility around transport hubs, comparing neighbourhood characteristics, and examining how different spatial datasets overlap.

More complex requests can combine multiple spatial operations, such as geocoding a location, creating a buffer, and intersecting it with another dataset. All results are returned as GeoJSON and rendered automatically as layers on the map.

Data sources

Data Lab uses a combination of curated datasets, OpenStreetMap, geocoding services, and user-uploaded data to answer queries and perform spatial analysis.

Curated application datasets
Datasets covering London topics such as planning, transport, heritage, environment, demographics, crime, and public services. Sources include TfL, the GLA, Ordnance Survey, Historic England, London boroughs, and UK government bodies.

OpenStreetMap
A community-maintained global mapping database used when relevant data is not available in the curated library. Typically used for amenities and points of interest such as restaurants, pubs, pharmacies, parks, and other local features.

Geocoding services (Nominatim)
Used to convert place names, addresses, landmarks, and postcodes into map locations.

Private datasets
User-uploaded datasets stored within Data Lab. These can be queried alongside public datasets and used for custom analysis. Data quality depends on the source provided by the user.

Available data

Data Lab provides a curated library of London-focused datasets covering:

• Heritage and conservation (listed buildings, conservation areas, monuments)
• Planning and development (brownfield sites, allocations, opportunity areas)
• Transport and accessibility (TfL network, PTAL, cycle infrastructure)
• Green spaces (OS greenspace, open space access)
• Demographics and economy (house prices, population density, deprivation, income)
• Environment (noise, emissions, flood risk, ULEZ, broadband speed)
• Amenities and services (schools, hospitals, GP practices, supermarkets)
• Crime and safety (theft, burglary, robbery, drugs)
• Energy and utilities (EPCs, heat networks, energy demand, solar potential)

Private datasets can also be uploaded and queried alongside the public library.

Key capabilities

Data Lab supports:

• Displaying data layers (e.g. GP practices in a borough)
• Spatial queries (e.g. features within a distance of transport nodes)
• Filtering and comparison (e.g. building grades within an area)
• Buffer analysis (e.g. 1km zones around key locations)
• Intersection analysis (e.g. overlap between planning and opportunity areas)
• Statistical summaries (e.g. crime counts by category)
• Geocoding (e.g. converting place names into map locations)

Where curated data is not available, OpenStreetMap is used as a fallback for general points of interest.

Scope and limitations

Data Lab is currently limited to London-based datasets. It does not support queries outside London.

Map layers are automatically rendered but cannot currently be restyled or toggled within the interface. Refinement and filtering must be done through the chat assistant.