Unique Property Reference Numbers - Great Britain: Open UPRN
收藏Snowflake2025-02-17 更新2025-04-09 收录
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## Introduction
OS Open UPRN are the authoritative identifier used to uniquely identify addressable locations in Great Britain; they are essential for bringing property and address information together.
Coverage: Great Britain
Format: Vector
Scale: 1:1 250 to 1:10 000
Update Cycle: Weekly. Open UPRN is updated every six weeks, in-line with the AddressBase Epoch dates published on ['Product Refresh Dates'](https://docs.os.uk/os-downloads/resources/product-refresh-dates#addressbase-products).
Last Updated: December 2024
Release Note: [https://docs.os.uk/os-downloads/identifiers/os-open-uprn/release-notes/december-2024](https://docs.os.uk/os-downloads/identifiers/os-open-uprn/release-notes/december-2024)
## What's in this product?
Open UPRN: Contains the position of each record held within AddressBase Premium along with the unique identifier – the Unique Property Reference Number (UPRN).
## What is its value?
Open UPRN creates value for customers in a variety of ways including:
1. Share and link data related to UPRNs, to aid detailed spatial analysis and visualisation of your use cases.
2. The UPRN is a persistent identifier to an addressable location that is never re-used, allowing you to confidently manage associated information to an address and track changes in addressing over time.
3. The UPRNs are primarily allocated by Local Authorities, under their legal duty to maintain this information. This means you can have confidence you're accessing an authoritative source of these identifiers that is current and accurate for your use cases.
## Case Studies
Climate Risk Scenario Modelling for SimAnalytica: [https://www.ordnancesurvey.co.uk/customers/case-studies/simanalytica-climate-risk-scenario-modelling](https://www.ordnancesurvey.co.uk/customers/case-studies/simanalytica-climate-risk-scenario-modelling)
Using de-identified patient addresses to support better location-base care for Researchers at the Clinical Effectiveness Group, at Queen Mary University of London: [https://www.ordnancesurvey.co.uk/customers/case-studies/identifying-the-wider-determinants-of-health](https://www.ordnancesurvey.co.uk/customers/case-studies/identifying-the-wider-determinants-of-health)
Helping customers find their home using Zoopla:
[https://www.ordnancesurvey.co.uk/customers/case-studies/zoopla-the-uprn](https://www.ordnancesurvey.co.uk/customers/case-studies/zoopla-the-uprn)
Improving home delivery outcomes for Riverford Organic Farmers: [https://www.ordnancesurvey.co.uk/customers/case-studies/kerbside-location-data-accuracy](https://www.ordnancesurvey.co.uk/customers/case-studies/kerbside-location-data-accuracy)
提供机构:
Ordnance Survey
创建时间:
2025-02-14



