London Uncovered

A mobile-first London exploration game built on an interactive map of the English Heritage blue plaque scheme. Explore the map, find plaques near you, collect the discoveries you make, and watch your London fill in.

Live site: https://nyatasha.github.io/blueplaques/

Discover the stories hiding around you.

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What it does

• Map — the English Heritage scheme's London plaques, clustered, with markers that show fame tier and whether you have collected them.
• Search — people, places and categories, with grouped suggestions.
• Categories — every plaque is classified into one of nine top-level categories (Writers & Literature, Art & Design, Science & Technology, Film & Theatre, Music, Politics & Society, Architecture, Sport, Other).
• Find my next discovery — ranks nearby uncollected plaques by distance, fame and context, and points you at one.
• Collecting — collect a discovery on location (verified within 100 m) or mark one as seen from anywhere. Progress earns XP and levels.
• Walks — four curated self-guided routes built from plaques already on the map, each with its stops in walking order, the distance and the walking time.
• Quest — five fixed goals that answer "what should I do next?".
• My London — discoveries, percentage of London uncovered, level, recent finds, category collections and achievement badges.
• Themed collections — fourteen sets that cut across the categories, each finishable: Iconic Londoners, Swinging Sixties, Georgian London, South of the River, Where They Worked and more. All derived from the data, none hand-listed.
• Iconic moments — collecting one of the 49 Iconic plaques draws it as a plaque and tells you something true about the person.
• Backup links — move a collection to another browser or device without an account. The whole save travels inside a URL fragment.
• A shareable card — a 1080×1350 image of your progress, rendered in the browser, with a dot for every plaque on the map and yours filled in.
• Add to Home Screen — offered after a third discovery, because Safari clears site storage after a week away and a home-screen install is exempt.

Progress lives in this browser's localStorage. There are no accounts, no backend and no tracking of your location.

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Running it locally

No build step and no dependencies — it is static files plus Leaflet from a CDN.

python3 -m http.server 8000
# open http://localhost:8000

A server is required: the app uses native ES modules and fetch, neither of which works from a file:// URL.

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Tests

bash tests/run.sh

Three suites, all dependency-free:

Suite	Runner	Covers
tests/logic.test.mjs	JavaScriptCore (ships with macOS)	XP and levels, Haversine distances, localStorage robustness, derived progress, achievements, quests, recommendation ranking, dataset integrity
tests/seo.test.py	Python 3	slug stability and collisions, HTML and URL escaping, generated page content, canonical URLs, relative paths, the internal link graph (category, nearby, walks), category and walk page contents, walk definitions and derived distances, the plaque URL map, sitemap contents
tests/smoke.html	headless Chrome via tests/cdp.py	boot, marker rendering, layout and touch targets at 390 px, search, the collect flow, tab navigation, filters, categories, reset, ?plaque= deep links

tests/cdp.py is a small self-contained Chrome DevTools Protocol client; it also takes screenshots:

python3 tests/cdp.py shot http://localhost:8000/ shot.png 390 844

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Data pipeline

Three scripts run in order. Each one reads and rewrites data/plaques.geojson, so run them in sequence:

python3 scripts/fetch_plaques.py         # OpenPlaques CSV → GeoJSON
python3 scripts/add_fame.py              # + Wikipedia pageviews → fame 0–3
python3 scripts/classify_categories.py   # + category + category_label

A fourth script turns the finished dataset into the crawlable half of the site — a page per plaque, a page per category, a page per curated walk, the URL map the app links with, and the sitemap. Run it whenever the data changes:

python3 scripts/generate_seo_pages.py    # plaques/ + categories/ + walks/ + data/plaque-urls.json + sitemap.xml

The share card and app icons are generated too, and committed rather than built per deploy. The card carries the plaque count, which it reads from the dataset, so re-run it after a data refresh as well as after a branding change:

python3 scripts/make_social_image.py     # assets/social/og-cover.png

fetch plaques → add fame → classify categories → data/plaques.geojson
                                                       ↓
                                        generate SEO pages → deploy

generate_seo_pages.py also rewrites the plaque count in index.html — in the Twitter description, the JSON-LD and the <noscript> block — from the dataset it just read. Those numbers live inside <!--gen:NAME-->…<!--/gen:NAME--> regions and must not be edited by hand; a refresh would overwrite them anyway.

What the dataset covers

Every plaque in the OpenPlaques London datapull of 14 December 2025 (accessed 2026-09-06) tagged into the scheme administered by English Heritage — 1,001 rows, whatever colour the plaque is. The scheme's early plaques are brown terracotta, stone, bronze, black, grey, white and green, and selecting on colour == "blue" used to discard 76 of them (decision-log #24).

This is the beginning of the README. Read the rest at the original. Read the full README ↗