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Querying Urban/Rural Classification for Scottish Data Zones

Overview

This guide explains how to query the urban/rural classification for Scottish data zones using the statistics.gov.scot SPARQL endpoint.

Important Context

There are two related datasets on statistics.gov.scot:

  1. Data Zone Lookup 2022 (http://statistics.gov.scot/data/data-zone-lookup-2022)
  2. This is a FileDataset containing CSV data only
  3. Not queryable via SPARQL - only available as a CSV download
  4. Contains comprehensive geography lookup information including UR2, UR3, UR6, UR8 classifications

  5. Urban Rural Classification (6-Fold) (http://statistics.gov.scot/data/urban-rural-classification)

  6. This is a LinkedDataset (RDF Data Cube)
  7. Fully queryable via SPARQL
  8. Contains the 6-fold urban/rural classification linked to data zones
  9. This is the dataset to use for SPARQL queries

Dataset Structure

The Urban Rural Classification dataset is structured as an RDF Data Cube with the following components:

  • Dataset URI: http://statistics.gov.scot/data/urban-rural-classification
  • Dimensions:
  • Reference Area (sdmx:refArea): The data zone (e.g., http://statistics.gov.scot/id/statistical-geography/S01014811)
  • Reference Period (sdmx:refPeriod): The year (e.g., http://reference.data.gov.uk/id/year/2022)
  • Measure:
  • Rank (http://statistics.gov.scot/def/measure-properties/rank): Integer value 1-6 representing the classification
  • Attributes:
  • Unit Measure (sdmx:unitMeasure): Reference to the classification concept scheme

Classification Values

The 6-fold urban/rural classification uses the following numeric codes:

Code Classification Description
1 Large Urban Areas Settlements of over 125,000 people
2 Other Urban Areas Settlements of 10,000 to 125,000 people
3 Accessible Small Towns Settlements of 3,000-10,000 people, within 30 minutes drive of a settlement of 10,000+
4 Remote Small Towns Settlements of 3,000-10,000 people, with drive time over 30 minutes to a settlement of 10,000+
5 Accessible Rural Settlements of less than 3,000 people, within 30 minutes drive of a settlement of 10,000+
6 Remote Rural Settlements of less than 3,000 people, with drive time over 30 minutes to a settlement of 10,000+

SPARQL Queries

Basic Query: Get Classification for a Specific Data Zone

PREFIX qb: <http://purl.org/linked-data/cube#>
PREFIX sdmx: <http://purl.org/linked-data/sdmx/2009/dimension#>

SELECT ?classification
WHERE {
  ?obs qb:dataSet <http://statistics.gov.scot/data/urban-rural-classification> .
  ?obs sdmx:refArea <http://statistics.gov.scot/id/statistical-geography/S01014811> .
  ?obs <http://statistics.gov.scot/def/measure-properties/rank> ?classification .
}

Example Result: 1 (Large Urban Areas)

Detailed Query: Get Classification with Year and Label

PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX qb: <http://purl.org/linked-data/cube#>
PREFIX sdmx: <http://purl.org/linked-data/sdmx/2009/dimension#>

SELECT ?dataZone ?year ?classification ?classificationLabel
WHERE {
  ?obs qb:dataSet <http://statistics.gov.scot/data/urban-rural-classification> .
  ?obs sdmx:refArea ?dataZone .
  ?obs sdmx:refPeriod ?yearUri .
  ?obs <http://statistics.gov.scot/def/measure-properties/rank> ?classification .
  ?yearUri rdfs:label ?year .

  FILTER(?dataZone = <http://statistics.gov.scot/id/statistical-geography/S01014811>)

  OPTIONAL {
    ?obs sdmx:unitMeasure ?classUnit .
    ?classUnit rdfs:label ?classificationLabel .
  }
}

Query Multiple Data Zones

PREFIX qb: <http://purl.org/linked-data/cube#>
PREFIX sdmx: <http://purl.org/linked-data/sdmx/2009/dimension#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT ?dataZoneCode ?classification
WHERE {
  ?obs qb:dataSet <http://statistics.gov.scot/data/urban-rural-classification> .
  ?obs sdmx:refArea ?dataZone .
  ?obs <http://statistics.gov.scot/def/measure-properties/rank> ?classification .

  # Extract just the code from the URI
  BIND(STRAFTER(STR(?dataZone), "http://statistics.gov.scot/id/statistical-geography/") AS ?dataZoneCode)

  # Filter for specific data zones
  FILTER(?dataZoneCode IN ("S01014811", "S01013481"))
}

Data Zone URI Format

Data zones are referenced using URIs in the format:

http://statistics.gov.scot/id/statistical-geography/[DATA_ZONE_CODE]

For example: - Data zone S01014811: http://statistics.gov.scot/id/statistical-geography/S01014811

SPARQL Endpoint

Endpoint URL: https://statistics.gov.scot/sparql

The endpoint can be accessed via: - Web interface: https://statistics.gov.scot/sparql - HTTP GET or POST requests - Supports SPARQL 1.1 query syntax

Key Prefixes

PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX qb: <http://purl.org/linked-data/cube#>
PREFIX sdmx: <http://purl.org/linked-data/sdmx/2009/dimension#>

Alternative: CSV Download

If you need comprehensive lookup data including multiple classification types (UR2, UR3, UR6, UR8) and other geographic hierarchies, you can download the CSV file directly:

Download URL: Available from the Data Zone Lookup 2022 dataset page - Dataset: http://statistics.gov.scot/data/data-zone-lookup-2022 - The CSV includes columns: DZ22, IZ22, MMWard, LA, SPC, UKPC, HB, HIA, SPD, SFRLSO, SFRSDA, RRP, LRP, UR2, UR3, UR6, UR8, Country

The CSV approach is more suitable for: - Bulk lookups of many data zones - Obtaining multiple classification types simultaneously - Offline processing

Additional Resources

  • Urban Rural Classification: https://www.gov.scot/collections/agriculture-fisheries-and-rural-statistics/#urbanruralclassification
  • statistics.gov.scot Help: http://statistics.gov.scot/help
  • Data Zone Geography: https://www.gov.scot/collections/small-area-statistics/

Notes

  • The classification is based on population (from National Records of Scotland) and accessibility (drive time analysis)
  • Data zones are assigned based on their population-weighted centroid
  • Some data zones may straddle urban/rural boundaries
  • The classification is updated periodically to incorporate the most recent Population Estimates for Settlements and Localities
  • The current classification is based on 2022 data