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Access open-source global map data including roads, buildings, points of interest, land use, and administrative boundaries from OpenStreetMap. Used in geospatial data engineering pipelines for routing analysis, map enrichment, address geocoding, and building location-aware datasets with Python using the OSMnx library.
Engineers use `osmnx` to download street networks and building data by city or bounding box, and `overpy` for custom Overpass API queries. OSM data is processed with `geopandas` and `shapely` for spatial analysis and stored in PostGIS for geographic applications.
OpenStreetMap is the world's largest free geographic knowledge base, enabling location-aware AI applications at global scale. Use OSM POI data to build place-aware RAG systems, or train geospatial ML models on building density and road network features for urban planning AI.
# pip install osmnx geopandas
import osmnx as ox
# Download street network for a city
G = ox.graph_from_place("Amsterdam, Netherlands", network_type="bike")
nodes, edges = ox.graph_to_gdfs(G)
print(f"Nodes: {len(nodes)}, Edges: {len(edges)}")
ox.plot_graph(G)Official dataset source
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