I did a check in my area in western Washington State - they were all okay.
One new stations (more on that later) but some additional information on
others. The existing stations used existing nodes so spatial accuracy is
the same as what is there today. The additional information available might
be worth adding. For addresses that might mean having to process by country
or countries with similar addressing schemes.
In my area, the data included Shell and ARCO stations. Unfortunately
neither website provides and structured data (schema.org) that could be
used to improve the richness of the data. ARCO website didn't even list any
stations in my area, even though there are many.
The one new station actually is in OSM, but only with a name and building
tag. The spatial accuracy was very good.
I also found three stations to be deleted:
I would say go ahead with an import but ideally see if address information
could be added.
On Wed, Mar 7, 2018 at 9:07 AM, Ilya Zverev <i...@zverev.info> wrote:
> Hi everyone,
> Following the recent UK Shell stations import, I've got ahold of the
> entire NavAds dataset. A major part of it are fuel stations all across the
> world: UK, US, France, Germany, Australia, and many other countries. We
> have the full permission to use the data, it is very recent (we get updates
> monthly) and quite precise: all locations are manually tweaked after
> geocoding. It has fuel stations of major brands (Shell, BP, Total) and
> smaller, non-chain owners (ProxiFuel, Lotherol, Edeka).
> You can see the numbers and check a few stations yourself at the
> validation website (it will be very slow, please bear with it):
> I want to import this data to OpenStreetMap. Which means, to update tags
> on 38k fuel stations and add 21k stations not present on OSM. For that, I
> need you to have a look at the data. Of course it is impossible to manually
> check every object, and to do that afterwards each month up to eternity.
> But you can help check that tags are correct, that there are no duplicates
> being created, and that postcodes on objects are good to import.
> The source dataset has much more information than I upload. For example,
> it has flags for grocery stores, car washes, restaurants in fuel station
> buildings, and I don't know tags for these. It has street addresses, but
> they need to be parsed, and that isn't easy ("62 Rue Du General Leclerc",
> "Pritzwalker Straße 20", "Allée de Provence Bld Des Alpes De Haute
> Provence"). It has town and state and country for each fuel station. You
> can see a sample of the source json here, and maybe suggest on using some
> of the extra information:
> Please be gentle. I know some of you despise large-scale imports, but this
> one to me is as good as imports get. I'd like to get it to completion, even
> if all that remains from the source data are the type and the brand name.
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