qrank (via) Interesting and very niche project by Colin Dellow.
Wikidata has pages for huge numbers of concepts, people, places and things.
One of the many pieces of data they publish is QRank—“ranking Wikidata entities by aggregating page views on Wikipedia, Wikispecies, Wikibooks, Wikiquote, and other Wikimedia projects”. Every item gets a score and these scores can be used to answer questions like “which island nations get the most interest across Wikipedia”—potentially useful for things like deciding which labels to display on a highly compressed map of the world.
QRank is published as a gzipped CSV file.
Colin’s hikeratlas/qrank GitHub repository runs weekly, fetches the latest qrank.csv.gz file and loads it into a SQLite database using SQLite’s “.import” mechanism. Then it publishes the resulting SQLite database as an asset attached to the “latest” GitHub release on that repo—currently a 307MB file.
The database itself has just a single table mapping the Wikidata ID (a primary key integer) to the latest QRank—another integer. You’d need your own set of data with Wikidata IDs to join against this to do anything useful.
I’d never thought of using GitHub Releases for this kind of thing. I think it’s a really interesting pattern.
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