UK Explr

Overview

UK Explr (alt. uk-explr) is a scalable ETL pipeline for UK census data that transforms bulk "raw" data (CSV and JSON files) into a unified statistical lookup table with multi-resolution querying capabilities.

To get started, see Usage file.

Example Deployment

A deployment can be accessed via the URL: https://uk-explr.up.railway.app

(test query: https://uk-explr.up.railway.app/v1/query-result?mode=oa&pageSize=50)

Key Features

Flexible Geospatial Querying

Look up statistics by:

✅ Output Area (OA) ✅ Lower/Middle Layer Super Output Areas (LSOA/MSOA) ✅ Local Authority Districts (LAD) ✅ Postal Codes

Integrated Services

🚀 Production-ready REST API for web applications

⚡ MCP (Model Context Protocol) server for system integration — TO DO

Optimised Data Processing

• Efficient handling of large datasets (e.g. UK census data)

• Normalised output structure for consistent analysis

Use Cases

• Real estate investment

• Policy analysis & demographic research

• Location-based service development

• Academic studies requiring unified datasets

Built with reliability and scalability in mind, this pipeline serves as a robust foundation for applications requiring granular UK geospatial statistics.

Structure

data/
├─ raw/             # Source data files before processing (CSV, JSON, etc.)
etl-pipeline/       # Scripts for schema generation and data transformation
libs/               # Shared utilities and helper functions (project-wide)
web-api/            # REST API server implementation
├─ controllers/     # Business logic for handling requests/responses
├─ libs/            # API-specific utilities and helpers
├─ middleware/      # Express/HTTP middleware functions
├─ models/          # Data validation schemas (request/response shapes)
├─ services/        # Business logic and external service integrations
├─ types/           # TypeScript interfaces and type definitions
├─ index.ts         # web server entry point
node_modules/       # Installed npm dependencies

TO DO

Major features in the current roadmap:

Key:
🔴 — scheduled: very important
🟠 — scheduled: important
🟡 — scheduled
🔘 — backlogged

• Implement MCP (Model Context Protocol) Server for AI integration. 🔴

• Create schema-derived .../help route (e.g. GET /v1/query-result/help) as documentation. 🟠

• Implement HATEOAS (Hypermedia as the Engine of Application State) best practises in RESTful API implementation. 🟠

• Ingest street names to associate with postal codes. 🟡

• Ingest point geocoordinates for streets. 🔘

• Ingest boundary geocoordinates for Output Area (OA), Lower-layer Super Output Area (LSOA), Middle-layer Super Output Area (MSOA), and Local Area District (LAD). 🔘

Contribution

Contributions are welcome!

Feel free to discuss improvements by opening an issue.

Alternatively, feel free to make improvements by submitting a pull request (PR).

License

MIT; please see LICENSE file for more information.