Import/Past Problems

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Imports invoke a complex set of issues within OSM. Past OSM imports have created problems at a variety of levels, including data and community, among others. This page is designed to outline a few case studies and lessons learned from those imports with the goal of helping bring OSM newcomers up to speed on these issues.

You can find more detail in the past threads on the imports@ mailing list, found here: Here are some selected threads worth reading:

General Import Problems

Not all data should be imported

Example: Parcel data

  1. Parcels change. A major task for a tax assessor's office is keeping the parcel layer up to date. Lots are merged and split all the time.
  2. Parcels are not "surveyable." You can't go look for the parcel lines on the ground or in an aerial to see if they are correct.
  3. Parcels aren't useful on a map. When you are going somewhere you go to an address not a parcel.

They are not good for addresses because sometimes a parcel has one address, sometimes hundreds (e.g. an apartment complex or mobile home park.) Some parcels have only one address, but if it is a very large lot (a farm for example) even that can be ambiguous.

Example: Terrain data

Explanation of why it shouldn't be imported.

Not all external data should be trusted

Example: Parcel data

Explanation of why it shouldn't be imported.

Imports might reduce mapper responsibility for/ownership of the imported data

Example: Imports: technical method & social impact - thread at imports@ mailing list.

Node Tag duplication

Example: Israel / Gaza Import

Example: KSJ2 Import - see: Japan KSJ2 Import - thread from imports @


Address catalog of Moscow, Russia (one of layers at Digital Atlas of Moscow), published by city government in 2016, contains building outlines with "document date" attribute. Dates after 2004 seem to be reflecting dates of official registration (roughly equal to construction completion date), but it's impossible to verify this property for all those objects. Therefore, it's better to avoid copying information like that, since without any third-party source, it's impossible to confirm, if specific date is correct.

Stale Data

Address catalog of Moscow, Russia (one of layers at Digital Atlas of Moscow), published by city government in 2016, contains significant amount of outlines of buildings, which no longer exist for a couple of years. Those buildings were demolished or rebuilt, but this dataset doesn't reflect it, since current regulation requires government to publish open data, but doesn't establish any formal requirements for its quality and responsibility for publishing bad quality data.

Therefore, every outline should be checked against an independent source to confirm it still exists.

Other GIS data formats don't always translate well to OSM data formats

Example: large polygons

Massive Polygons - thread from imports@ mailing list.

Fixing later can be very difficult


And we've also shown that finding error is far harder than entering new data. So starting with a clean slate and adding data in is easier than starting from a dataset and discovering errors- especially when (like in this example) you'd be starting from the same dataset.

Cross-referencing databases

UUIDs, etc.


  • Usually not best done through object tags
  • Too hard to trace back later
  • Difficult to understand how to manage when modifying (e.g. splitting, merging) objects

Data Density Problems for Editors

As the data in OSM becomes richer and richer and information density increases, editing can become more difficult. S

Past Import Lessons Learned

US: TIGER Import

Import page:

Issues: see: TIGER_fixup

French Parcel Imports

Import page: French parcels


Corine Data

Import page


UK Ordnance Survey

Import page

Issues: Consider, for the moment, Ordinance Survey. A study was done once comparing OSM and OS in terms of data quality. The guy running the study took OSM data and compared it to OS data (before OS was released under a Free license) and checked where they differed. He then went out and manually surveyed the areas.

It turned out that OS and OSM had approximately the same number of errors, but not the same errors. In other words, the error rate for the two datasets was the same. But here's the difference: Once you find an error in OSM, you can fix it.

US National Hydrography Dataset

Import page

Issues: See: Talk:National_Hydrography_Dataset#Dec_2012_Cleanup_Request_and_Notes

Alternate/Non-Import Approaches to Adding Data to OSM Maps

Map Layers / Overlays / Mashups

See Also: