About Streetary
Methodology, data sources and how we score every street
What is Streetary?
Streetary is a free, independent resource that provides street-level data for England and Wales. We combine 8 open data sources to generate a composite score for each street across nine dimensions of neighbourhood quality.
Our goal is to make neighbourhood-level data accessible to everyone — whether you are buying your first home, relocating for work, or simply curious about your own street.
Scoring Methodology
Each street receives an overall score from 0 to 100, calculated as a weighted average of nine dimensions:
| Dimension | Weight | What It Measures |
|---|---|---|
| Safety | 20% | Street-level crime rates and types from police.uk |
| Daily Access | 15% | Proximity to supermarkets, GP surgeries, pharmacies, post offices |
| Transport | 15% | Distance to bus stops, rail stations, tube and tram stops |
| Environment | 10% | Green spaces, parks and natural areas nearby |
| Market Value | 10% | Median price, trends, transactions from HM Land Registry |
| Family | 10% | Nearby schools, Ofsted ratings, primary and secondary phases |
| Energy Efficiency | 8% | EPC ratings for properties on the street |
| Flood Risk | 7% | Environment Agency flood zones (1, 2 and 3) |
| Walkability | 5% | Overall proximity to amenities and services on foot |
Scores are relative benchmarks — a lower score means the street scored lower on our measured metrics, not that it is a bad place to live. Many factors that matter (community spirit, noise, views, character) are not captured by open data.
Data Sources
All data comes from publicly available, government or community open data sources:
| Source | What It Provides | Licence |
|---|---|---|
| Ordnance Survey Open Names | Street inventory and coordinates (733K streets) | OGL v3.0 |
| ONS Census 2021 | Demographics, tenure, household composition by LSOA | OGL v3.0 |
| HM Land Registry | Property transactions, prices and trends (2014+) | OGL v3.0 |
| police.uk | Street-level crime data by category | OGL v3.0 |
| Ofsted | School inspection ratings (Outstanding to Inadequate) | OGL v3.0 |
| NaPTAN (DfT) | Public transport stops — bus, rail, tube, tram | OGL v3.0 |
| Environment Agency | Flood risk zones from Flood Map for Planning | OGL v3.0 |
| OpenStreetMap | Points of interest — shops, parks, amenities | ODbL |
Quality Controls
Every street passes through five quality gates before a page is published:
- Identity — at least one postcode is linked to the street
- Sufficient data — at least 3 independent data sources contribute
- Uniqueness — the data profile differs meaningfully from neighbouring streets (anti-thin-content check)
- Differentiation — at least 6 populated data fields and 1 street-level data point
- Narrative quality — the auto-generated description meets minimum length and specificity
Streets that fail any gate are excluded. Currently 99.3% of streets pass all five gates.
Limitations
Streetary is a data tool, not professional advice. Important limitations include:
- Scores reflect available open data only — many quality-of-life factors are not captured
- Crime data is mapped to approximate street locations by police.uk, not exact addresses
- Census data is at LSOA level (typically 1,000-3,000 people), not individual streets
- Property prices may be sparse for streets with few transactions
- School proximity does not guarantee admission to that school
- Flood zones are modelled, not observed — localised flooding may not appear
Always consult qualified professionals before making property or relocation decisions.
Who Runs Streetary
Streetary is built and maintained by Yoel Castaño, an independent software developer specialising in open-data products. He designed and runs the entire pipeline behind this site: ingesting 8+ UK government datasets, the 9-dimension scoring methodology described above, and the publishing system that keeps 732,287 street pages up to date.
Streetary is independently funded, hosts no property listings and earns no commissions from portals — rankings cannot be bought or influenced. Corrections and methodology questions are personally reviewed.
- Contact: [email protected]
- LinkedIn: linkedin.com/in/yoelcastanopeon
Contact
Questions, corrections or data enquiries: [email protected] — or write directly to the author at [email protected].
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