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Tom Morris

@Edent I've noodled around with trying to write some code to turn all of OSM into a Foursquare-style venues database but haven't had the time.

My rough plan—a script that parses the entire OSM dataset and:

- filters out the features one wants based on a predicate (pubs, restaurants, public buildings, etc.)
- flattens ways/relations into points (calculate centroids)
- emits lat, long, label, OSM type+ID

Stick result in DB (SQLite+SpatiaLite appeals to me), index on coords, query N closest.

28 January at 16:19 | Wall-to-wall | Open on mastodon.social
7 comments
Tom Morris

@Edent Most of it is a data quality problem in deciding on the predicate to filter the data.

Do you wanna check into an untitled tree or water fountain in your local park? (Filter things without a name?)

What about checking into a whole city or country? Or a particular borough? Or an area that doesn't line up with a governmental/administrative area (Soho, say)? That's a thing people did on 4sq to tell friends they are visiting.

How about the M25? (This place is not a place of honour etc.)

28 January at 16:33 | Open on mastodon.social
Sam Sneddon 🏳️‍⚧️

@tommorris @Edent also answers aren’t necessarily consistent; you might not have enough data to filter it in the way people want. people might want to check in to Route 66, but not the M25.

28 January at 16:35 | Open on glauca.space
Tom Morris

@Edent (Incidentally, this isn't a "don't do it", it's more a "I've played around with this in the past and you may will encounter fun weird stuff you didn't expect"—but weird stuff is good, please carry on.)

28 January at 16:48 | Open on mastodon.social
Jonty Wareing
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