Here is German Open Data portal for geodata - http://www.geodatenzentrum.de/geodaten/gdz_rahmen.gdz_div?gdz_spr=eng&gdz_akt_zeile=5&gdz_anz_zeile=0&gdz_user_id=0
It has administrative areas, zipcodes and geo names (cities, points of interests), etc available for download (Shapefiles) and as webservices (WMS).
Specifically German addresses data ...
You mention you want data sources, so I'm going to focus on where you can get information that helps match street addresses to coordinates, rather than APIs. If you can, go with a web service, but there's a certain masochistic pleasure in building your own geocoder from raw data!
OpenStreetMap is the most comprehensive worldwide source, and has good ...
OpenStreetMap has quite an easily accessible database of restaurants (and other places), which you can easily query using their Overpass API. An example query for Overpass's Query Form which gets all restaurants in greater London:
<has-kv k="amenity" v="restaurant"/>
<bbox-query s="51.28" n="51.686" w="-0.489" e="0.236"...
I don't know specifics on how Zillow, etc acquired their data - other than assuming they (or 3rd party) obtains the data on a per county basis.
As cities/counties open up open data portals, this data will become more accessible to developers.
When searching these portals, you want to look for tax lots, property tax, or parcels.
A lot of these datasets are ...
The SimpleGeo point of interest dump of 21m places is the best open data set I know of, though it's getting pretty long in the tooth these days and so won't have the up-to-date-ness you're looking for:
For a wider listing of diplomatic entities, consider using Open Street Maps.
For example, you can use the Tag: amenity=embassy. This data source includes the following dimensions:
FWIW, Karsten W.'s suggestion uses R, so I'm not sure what your tool of choice is, but here're two other options:
1.) A Python client, geopy, that hooks into the geocoders from:
• geocoder.us (free for non-commercial use, accounts available for commercial uses)
• Semantic MediaWiki
I've used it for years. It's ...
Here you can find some http://schnipsel.dianacht.de/2010/07/15/shapefiles-fuer-bundeslaender-und-kantone
Also as part of the global administrative borders service you can find some.
In both cases I don't know the depth of it.
If this is not good enough, maybe openstreetmap has more data for you. Look for this at geofabrik http://www....
Germany is one of the best mapped countries in Open Street Maps. You could extract the administrative boundaries from OSM. Using Osmosis, you might do something like
osmosis --read-xml germany.osm --way-key-value keyValueList="boundary.administrative" --used-node --write-xml germany_admin.osm
Wikidata has a lot of data about embassies and consulates.
I wrote a SPARQL request to download the data:
Go to https://github.com/nicolas-raoul/database-of-embassies
Press the link called "Click here to see the data or download it" (the SPARQL request is so big I can not paste it here).
Press the "Play" button at the left.
Waiting for about a ...
OpenAddresses.io does not have nearly 100% coverage but you may get lucky: http://results.openaddresses.io/
Open Street Map ("OSM") is another potential source: https://gis.stackexchange.com/questions/121266/extracting-list-of-addresses-in-particular-region-from-openstreetmap-osm-data
One less expensive option may be to buy voter registration lists from ...
It says: Data: OpenStreetMap in the image.
You can download OpenStreetMap data dumps in a variety of formats, such as shape-files. Like a database, it will contain nodes of certain types, including one for pubs. They will all include geographic coordinates. Simply extract all the nodes that are pubs and you're there.
Official lists maintained by government bodies:
The dc.gov (Washington, DC) has a dataset for all embassies in Washington, DC:
This data.gov dataset lists all US embassies/consulates in the World:
This open.canada dataset lists ...
Wikivoyage has open data about restaurants and bars, worldwide, pretty up-to-date.
The data is licensed under Creative Commons Attribution/Share-Alike.
The format is like this:
| name=Atelier de Joel Robuchon | url=http://www.robuchon.jp/latelier | email=
| address=Roppongi Hills Hillside 2F, 6-10-1 Roppongi
| lat=35.660197 | long=139.728804 | ...
The French government has just launched a national open database that aims to contain all currently valid addresses: http://adresse.data.gouv.fr
It is a collaboration between the government, the French National Geographic Institute, the postal service, and OpenStreetMap.
800 megabytes, one CSV file per French departement, WIN1252 encoding.
The data can be ...
Natural Earth has public-domain shapefiles for some of those types of geographies, but they're not as in-depth as the country-specific sources others have mentioned. They still might be worth a look, though, depending on your application: http://www.naturalearthdata.com/downloads/
I will answer this in the more general term (leaving the consumer out). Invariably when data is aggregated and coalesced from plural data sources you will have conflicts in records. Just think of all the wacky occupants you receive in your mailbox or the wacky places you supposedly lived when you do a FREE background search.
These data sources need to ...
While I don't have direct experience with Japanese material, a quick search for Japan cadastral material reveals that this data might not exist in a digital form.
"[The] lack of progress in surveying land in the Tokyo metropolitan area has become a serious problem" – Japan Times, "Property borders: Where to draw the line", 2 January 2015
The Ministry of ...
Firstly, "geocoding" is the name of the task you're trying to achieve (might help with future Googling). The Geocommons geocoder is one example of an open-data-driven geocoder; I think they mostly use US Census data.
(As that example illustrates, a lot of this kind of data is country-specific, so a bit more detail in your question may produce better ...
The US NGA/GNS Server contains geographic datasets for every country in the world. It does not contain shapefiles, but does have area centroids for at least:
Capitals (both country and administrative divisions).
Other Populated Localities.
I think the best approach is to start with a small random sample of conflicts and investigate them if this is possible. If you can understand the type of error (out of date data, for example) then you can make an educated decision regarding which one to trust.
If that is not possible and you can get a tiebreaker, then go with that. If this is not possible ...
Just to detail my findings about Andrew's first link (embassies in Washington, DC):
The data file can be found at http://geospatial.dcgis.dc.gov/dc_kmz/Culture_and_Society/DCG9_Miscellaneous_EmbassyPt/DCG9_Miscellaneous_EmbassyPt/DCG9_Miscellaneous_EmbassyPt.kmz
Once unzipped, open the doc.kml file, it contains such an item for each embassy:
How you can improve it depends very much on how you want to use it, and who you want it to be useful for. 'Valid' RDF is fine, but may not be useful depending on your intended application! If you want it to be helpful to open/linked types, publishing it using other 'accepted' vocabularies is good (although schema.org is the best catch-all, it is not always ...
You can find the dataset here -:
P.S- I worl for datazar, an open source datalibrary, where people can share, discover and work with data.
In the first link in the original post, among the many datasets available in Japanese there is a resource from the Ministry of Land, Infrastructure and Transport that provides geocoordinates for addresses in most Tokyo wards and cities. The resource is
For example, there are around 178,000 building ...
Do you have reasons to believe that addresses of these establishments (the casino being a structure) can change?
Anyway, my best bet is to look for their EIN (Employer Identification Number) with the IRS and go over the forms they submitted through the years. For the Wheeling Island Hotel-Casino-Racetrack I found a SEC filing mentioning it, as part of the ...
Good question. The first address added to a company in Crunchbase is assigned the headquarter relationship. If a new HQ is subsequently added, it can be selected and reset on crunchbase.com on the top card.
Why not use OSM Buildings data?
Microsoft released US Building Footprints dataset but you are going to want to ensure accuracy. I've read/seen examples where it is not 100% accurate.
OSM Buildings References:
Fetching Building Data with OSM
Extracting Building Footprints from OpenStreetMap
How to Download OSM 3D Building Data