Browse places that are connected by a border, connected as a graph.

This project contains a pipeline to extract from Wikidata all the elements that share a border, and then organize them by categories to present them in a convenient view:

The first version was viewing only French communes; I rewrote the data pipeline in Rust and made it generic to support any Wikidata category. On the website are the top categories, by number of edges and connectivity ratio; minus some categories that are too broad or generic.

Instead of installing Blazegraph and learning SPARQL, I decided to do a first pass to put the data in an sqlite database; then a second pass generates geojson files to be viewed from SQL queries.

• lbzip2's lbzcat
• a recent rust toolchain
• a C compiler (to re-build sqlite)

Crates:

• chrono: for parsing times in the dumps
• rusqlite: for sqlite access - uses a bundled version of sqlite3
• memchr: for fast filtering before json parsing
• serde and serde_json: for JSON parsing and geojson file generation
• reqwest: for fetching category names from Wikidata (< 200 HTTP requests in a run)
• indexmap: for stable output generation

Frontend:

• Maplibre GL JS - for displaying the data on a WebGL-accelerated map widget (fork of Mapbox GL JS)
• Noto font, converted as PBF for OpenMapTiles (from Maplibre demo tiles).
• Earth coastlines extract from OpenStreetMap, converted to geojson.

Build and run on a bz2 JSON dump of Wikidata, storing the extracted information in temporary sqlite database border-explorer.db:

cargo run --release border-explorer.db ./wikidata/latest-all.json.bz2

This will generate the geojson files in web/geojson/; you can then use the website statically with a webserver at the root of web/.

It comes from Wikidata. Usually those categories have a good enough full description, but a very short name, like "district" or "province"; do not hesitate to contribute to Wikidata to improve those in your language!

It comes from Wikidata. Do not hesitate to contribute!

Sometimes there might not even be a name for any locale, so for english we fallback to mul, the multilingual label. But in general, I have only implemented getting the names for those two locales, I might do more if there is interest!

Good question. If you find out, let me know!

I invite you to open a discussion about this on Wikidata's wiki Discussion pages.