Open-data evidence for a winning plan to reconnect a city district.

The evidence toolkit behind The Innovation Spine, a team proposal to reconnect Birmingham's Knowledge Quarter to the city centre. Route legibility scoring, wayfinder placement, traffic and collision evidence and a costed plan, shipped as an interactive map.

Sector
Urban planning
Method
Geospatial analytics and optimisation
When
Jun 2026
Context
Team entry: West Midlands winners, UKREiiF 2026 Next-Gen Challenge
Role
Built the open-data evidence toolkit and the web app

Key figures

  • 86% of 4,000 random weightings keep the top route
  • 12 wayfinders placed by a coverage optimiser
  • £693k indicative cost after sponsorship, inside £1M
SpineLens AI: a dark map of central Birmingham with the walking route to the Knowledge Quarter, wayfinder points, and a panel showing 35,141 vehicles a day and 20 injury collisions nearby.

How it works

From open data to a public app
  1. Acquire : Open data: OSM, DfT traffic and collisions, NaPTAN, Land Registry
  2. Audit : Every source tagged on an evidence ladder from 0 to 5
  3. Model : Route legibility, wayfinder coverage, crossing and pavilion
  4. Cost : Low, central and high estimates against £1M
  5. Sanitise : A build check stops internal notes reaching the app
  6. Publish : A static map app on Cloudflare Pages

Architecture and results

  • A model runs here
  • Deterministic code
  • An outside source
  • A stored artefact
  • A boundary the design refuses
  1. Open data to a public map, with no model in the loop

    Four open sources, each tagged on an evidence ladder, feed a tested Python package. Three independent analyses, route legibility, wayfinder placement and the crossing, feed one costed plan, and a build step turns the evidence file into a static map app, failing if internal notes would leak. Everything is transparent scoring and optimisation.

    Four open-data sources in a panel feed three independent analyses, route legibility, wayfinders and the crossing, which feed a costed plan and then a static map app. Open full size: Open data to a public map, with no model in the loop
  2. How often each approach ranks most legible

    The Route Legibility Index was re-run with 4,000 random weightings of its components. Colmore Row ranked most legible in 86% of them, so the ranking does not hang on one choice of weights.

    Share of 4,000 random weightings in which each approach ranks first

    How often each approach ranks most legible
    Item Ranked first
    Colmore Row 86%
    Nechells and Dartmouth 14%
    New Street 0%
    Moor Street 0%
    Snow Hill 0%

Numbers from the project's public repository (README and route-legibility outputs).

The question

Birmingham’s Knowledge Quarter, home to Aston University, BCU and Millennium Point, is minutes from the city centre but cut off by wide, fast roads and by routes that tell a pedestrian nothing. For the UKREiiF 2026 Next-Gen Challenge, our team proposed The Innovation Spine. The question for its first, £1M phase: where does the walk become hard to follow, and which low-cost changes make it clearer per pound? My part was the open-data evidence behind the answer and the web app that presents it.

Evidence, with its level stated

Every output is tagged on an evidence ladder from 0, not tested, to 5, validated in the field. Most of this work sits at level 3, audited, and nothing is presented as funding-grade.

What the evidence found

  • Route legibility. A transparent Route Legibility Index ranks the approaches: Colmore Row reads clearest, Snow Hill hardest. Re-run with 4,000 random weightings, Colmore Row stays first in 86% of them, so the order does not hang on one choice of weights.
  • The crossing. Dartmouth Middleway carries 35,141 vehicles a day but 43 cyclists, with 20 injury collisions, 5 of them serious, within 150 m between 2020 and 2024. That supports a signalised crossing rather than paint.
  • Wayfinders. A maximal-coverage optimiser places them where people can take a wrong turn. About seven cover roughly 90% of the city-centre confusion, and twelve once the network extends across the crossing.
  • The pavilion. A reversible wooden information hub, matched by Land Registry data to a single registered parcel.
  • The budget. At the central estimate the whole package fits the £1M phase, at about £693,000 after sponsorship. The high estimate does not fit, and the chart keeps that visible.

From notebooks to a public app

The work runs in three layers. Notebooks and a tested Python package produce one evidence file. A build step turns it into the app’s content and fails if internal notes or source codes would leak. A static React and MapLibre app presents it in five views, tested for WCAG 2.2 AA, on Cloudflare Pages at no running cost.

Limits

  • The scores are transparent hypotheses on documented weights, not measured outcomes.
  • All costs are indicative until a quantity surveyor prices them. Fieldwork, costing and consents are listed in a validation register with owners and next steps, but are not done.
  • This covers Phase 1 only; the £10M and strategic phases are proposals.
  • The code has no licence yet, so it is not open for reuse.

Built with

  • Python
  • OSMnx
  • GeoPandas
  • NetworkX
  • React
  • MapLibre

Map data © OpenStreetMap contributors; traffic and collision data from the Department for Transport.

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