UK Food Hygiene Rating System
The UK Food Hygiene Rating System data contains information for thousands of business across the United Kingdom.
In licensing terms it seems this is a dataset we can make use of, and they have already been listed as credited Contributors (although the license is not the only consideration. Due to #Location Inaccuracy problems described below, this is not a candidate dataset for direct import into OpenStreetMap)
<EstablishmentDetail> <FHRSID>207603</FHRSID> <LocalAuthorityBusinessID>2006/00077/COMM</LocalAuthorityBusinessID> <BusinessName>Starbucks Coffee Company</BusinessName> <BusinessType>Restaurant/Cafe/Canteen</BusinessType> <BusinessTypeID>1</BusinessTypeID> <AddressLine1>Unit 6</AddressLine1> <AddressLine2>Block 4</AddressLine2> <AddressLine3>Jubilee Street</AddressLine3> <AddressLine4>Brighton</AddressLine4> <PostCode>BN1 1GE</PostCode> <RatingValue>5</RatingValue> <RatingKey>fhrs_5_en-GB</RatingKey> <RatingDate>2011-08-11</RatingDate> <LocalAuthorityCode>875</LocalAuthorityCode> <LocalAuthorityName>Brighton and Hove</LocalAuthorityName> <LocalAuthorityWebSite>http://www.brighton-hove.gov.uk/foodsafety</LocalAuthorityWebSite> <LocalAuthorityEmailAddress>firstname.lastname@example.org</LocalAuthorityEmailAddress> <Scores/> <SchemeType>FHRS</SchemeType> <Geocode> <Longitude>50.82486600000000</Longitude> <Latitude>-0.13894300000000</Latitude> </Geocode> </EstablishmentDetail>
This is equivalent to node:1236329881.
From this data, the following can be merged into OpenStreetMap:
- BusinessName → name
- BusinessType can be used to infer amenity or shopping or tourism or a number of other values.
- AddressLine1 → addr:housenumber, addr:street
- AddressLine2 → addr:city
- PostCode → postal_code
- LocalAuthorityBusinessID → id
For the FHRS specific data, I propose a number of new keys:
- RatingValue → fhrs:rating
- LocalAuthorityName → fhrs:authority
- FHRSID → fhrs:id
- RatingDate → fhrs:inspectiondate
The Geocode property can be used as a way to distinguish between similarly named businesses (chains with a lot of locations like McDonalds, Starbucks etc.) and to add points of interest that do not exist.
It looks like the Latitude and Longitude coordinates of each place are the approximate location of the place based on postcode. As an example, all these places have the same coordinates (-0.12234400000000 51.58105100000000) and postcode (N8 8PT), but in fact they are scattered around the street:
Belash Restaurant/Cafe/Canteen 5 N8 8PT -0.12234400000000 51.58105100000000 Bistro Aix Restaurant/Cafe/Canteen 4 N8 8PT -0.12234400000000 51.58105100000000 Broadway Fish Bar Restaurant/Cafe/Canteen 2 N8 8PT -0.12234400000000 51.58105100000000 Dixy Chicken Restaurant/Cafe/Canteen 4 N8 8PT -0.12234400000000 51.58105100000000 Honeycomb Cafe Retailers - other 3 N8 8PT -0.12234400000000 51.58105100000000 Meghna Restaurant Restaurant/Cafe/Canteen 1 N8 8PT -0.12234400000000 51.58105100000000 Melange Restaurants Ltd Restaurant/Cafe/Canteen 3 N8 8PT -0.12234400000000 51.58105100000000 Nakama Restaurant/Cafe/Canteen 1 N8 8PT -0.12234400000000 51.58105100000000 Papaya Restaurant/Cafe/Canteen 4 N8 8PT -0.12234400000000 51.58105100000000 Pizza Hut Delivery Takeaway/sandwich shop 5 N8 8PT -0.12234400000000 51.58105100000000 Royal News Retailers - other 4 N8 8PT -0.12234400000000 51.58105100000000 The Henry Reader Pub/bar/nightclub 3 N8 8PT -0.12234400000000 51.58105100000000 Virgin Active Restaurant/Cafe/Canteen 4 N8 8PT -0.12234400000000 51.58105100000000
For local authorities in Wales, the data is provided in two XML files, containing both English and Welsh place text strings. For simplicity, it might be best to import data for England first and then import Welsh data afterwards once we know what the issues with the data are.