# Creating a Colouring London database from scratch ## Data downloading The scripts in this directory are used to extract, transform and load (ETL) the core datasets for Colouring London: 1. Building geometries, sourced from Ordnance Survey MasterMap (Topography Layer) 1. Unique Property Reference Numbers (UPRNs), sourced from Ordnance Survey AddressBase To get the required datasets, you'll need to complete the following steps: 1. Sign up for the Ordnance Survey [Data Exploration License](https://www.ordnancesurvey.co.uk/business-government/licensing-agreements/data-exploration-sign-up). You should receive an e-mail with a link to log in to the platform (this could take up to a week). 2. Navigate to https://orders.ordnancesurvey.co.uk/orders and click the button for: ✏️ Order. From here you should be able to click another button to add a product. 3. Drop a rectangle or Polygon over London and make the following selections, clicking the "Add to basket" button for each: ![](screenshot/MasterMap.png)

![](screenshot/AddressBase.png) 4. You should be then able to check out your basket and download the files ## Prerequisites You should already have set up PostgreSQL and created a database. Make sure to create environment variables to use `psql` if you haven't already: ```bash export PGPASSWORD= export PGUSER= export PGHOST=localhost export PGDATABASE= ``` Create the core database tables: ```bash cd ~/colouring-london psql < migrations/001.core.up.sql ``` There is some performance benefit to creating indexes after bulk loading data. Otherwise, it's fine to run all the migrations at this point and skip the index creation steps below. Install GNU parallel, this is used to speed up loading bulk data. ## Process and load Ordance Survey data Before running any of these scripts, you will need the OS data for your area of interest. AddressBase and MasterMap are available directly from [Ordnance Survey](https://www.ordnancesurvey.co.uk/). The alternative setup below uses OpenStreetMap. The scripts should be run in the following order: ```bash # extract both datasets extract_addressbase.sh ./addressbase_dir extract_mastermap.sh ./mastermap_dir # filter mastermap ('building' polygons and any others referenced by addressbase) filter_transform_mastermap_for_loading.sh ./addressbase_dir ./mastermap_dir # load all building outlines load_geometries.sh ./mastermap_dir # index geometries (should be faster after loading) psql < ../migrations/002.index-geometries.sql # create a building record per outline create_building_records.sh # add UPRNs where they match load_uprns.py ./addressbase_dir # index building records psql < ../migrations/003.index-buildings.sql ``` ## Alternative, using OpenStreetMap This uses the [osmnx](https://github.com/gboeing/osmnx) python package to get OpenStreetMap data. You will need python and osmnx to run `get_test_polygons.py`. To help test the Colouring London application, `get_test_polygons.py` will attempt to save a small (1.5km²) extract from OpenStreetMap to a format suitable for loading to the database. In this case, run: ```bash # download test data python get_test_polygons.py # load all building outlines ./load_geometries.sh ./ # index geometries (should be faster after loading) psql < ../migrations/002.index-geometries.up.sql # create a building record per outline ./create_building_records.sh # index building records psql < ../migrations/003.index-buildings.up.sql ``` ## Finally Run the remaining migrations in `../migrations` to create the rest of the database structure. # Updating the Colouring London database with new OS data