The dataset claims there are significantly more Citibank locations than McDonalds worldwide which I don’t think can be correct?
It also lists over 56,000 Wildberries worldwide but a quick Google search shows they are a large online retailer. I wonder what is going on with the brand POIs…
There should be enough SQL in the blog to re-purpose extracting out the Wildberries locations and seeing where they land on top of. I've never heard of this firm before you mentioned it.
From Google:
> Citibank operates over 2,300 ATMs within more than 600 U.S. branches, with a total network of over 65,000 fee-free ATMs
So the 57,163 Citibank locations are probably a combination of their branches and ATMs.
Update: I reviewed Alltheplaces a while back, they scrape company websites for store locations. They reported 68,227 locations for Wildberries. ATP is one of the sources Overture use but they seem to use 1.55M of the records from their 19M-record dataset. https://tech.marksblogg.com/alltheplaces.html
Ideally ATP's "located_in" and "located_in:wikidata" fields would be populated for these wildberries pickup locations, making it clear the pickup location is part of a parent feature (e.g. fuel station, supermarket). These fields are specific to ATP and are not OSM fields. OSM would expect features to be merged and a hypothetical field such as "pickup_brands:wikidata=Q1;Q2;Q3" be used instead on the parent feature.
ATP has a much more inclusive set of features it can extract than what Overture Maps, TomTom et al care about. As Overture Maps is more opinionated on what they aggregate they will filter out ATP extracted features such as individual power poles, park bench seats, local government managed street and park trees, stormwater drain manholes, cemetery plots, weather stations, tsunami buoys, etc. I think there might be some exceptions if it helps TomTom et al with their products such as speed camera locations, national postal provider drop-off/pick-up locations within other branded retail shops, etc.