World-scale OpenStreetMap data in CSV

Welcome to the free download server of the SLIPO project. This server provides monthly updates of data extracted from the OpenStreetMap database to CSV files.

In SLIPO, we have developed tools for geospatial data integration, which are able to perform efficiently from the local to the global level using Linked Data technologies. SLIPO specifically supports quality-assured integration of Big data regarding Points of Interest (POIs). One of the most valuable global sources of such data for the industry, innovators and researchers, is OpenStreetMap (OSM), a community of volunteers whose open geospatial data currently powers thousands of services and products. We have received multiple requests from POI value chain stakeholders to streamline and automate the data transformation process of OpenStreetMap POI data to comma-separated values (CSV), and more generally of OpenStreetMap entities to CSV format. Extracting this wealth of data into a neutral tabular format can greatly facilitate loading of the file contents in DBMSs and GIS for further analysis, since CSV is widely used for data exchange in the industry. Thus, we launched this free service offering tens of millions of geospatial OSM entities worldwide, which demonstrates the scalability and performance of SLIPO tools at a world-scale. More specifically, we offer two types of archives:

Transformation to CSV

The original OpenStreetMap data is transformed to CSV using our OSMWrangle software for Extract-Transform-Load (ETL) of geospatial entities, developed in the context of projects SLIPO (No 731581) and SmartDataLake (No 825041), both funded by European Commission's Horizon 2020 Programme. OSMWrangle draws much of its functionality from the source code of TripleGeo, an ETL tool that extracts spatial features and their thematic attributes from a variety of geographical files and spatial DBMSs and transforms them into RDF triples. As its name suggests, OSMWrangle specifically supports extraction of OpenStreetMap features to RDF, CSV, or both.

All features retain their original OpenStreetMap identifiers for nodes, ways, and relations. Certain tagged values of the original OSM features (if present) are extracted in specific attributes as denoted in the header of each CSV file:

while all remaining OSM tags are listed under the OTHER_TAGS column as key-value pairs in JSON format.

Note this difference between the two archives of exported data:

Abiding to data protection regulations in the European Union, the OpenStreetMap data provided through this server does not contain any user-related metadata (names, IDs or changeset IDs of the OpenStreetMap features).

Export files

We provide two separate archives of data extracted from OpenStreetMap: (i) POIs only, and (ii) all geospatial entities having a name. Both archives are provided as zip files of CSV records organized per continent (or subcontinent), per country, and optionally per region (for larger countries). The same organization in continents, countries, and regions is applied in both archives.

IMPORTANT! Since comma appears frequently in the contents of attribute values, note that | is used as the delimiter character between columns in each CSV file of this archive.

All exports from OpenStreetMap are updated once a month, allowing users to download the latest CSV data regarding any part of the world for their line of work. Select a continent and then a country or region of interest from the folder list of your chosen archive to download the respective CSV dataset.


The files in each archive are made available under the Open Database License (ODbL) by the OpenStreetMap Foundation (OSMF). Any rights in individual contents of the data are licensed under the Database Contents License. Please visit OpenStreetMap for details. This download service of open data extracted from OpenStreetMap in RDF is offered free of charge.


The SLIPO project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 731581.
The SmartDataLake project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 825041.

This service is available from the Information Management Systems Institute, at Athena Research Center, Greece.
Archives contain data extracted from OpenStreetMap as of: