Using OpenStreetMap Data for Urban Spatial Analysis: Crowdsourced Geography for Research
This event, led by Felipe Valdez, provided a hands-on introduction to OpenStreetMap (OSM) and its applications in urban research. The workshop covered the OSM data model — including nodes, ways, and relations — and introduced participants to the tagging system that describes geographic features. Most of the session focused on writing OverpassQL queries using Overpass Turbo to extract targeted datasets such as hospitals, parks, and transit stations within Philadelphia. With our newly extracted data, we quickly touched on the uses of Overpass Ultra for advanced map styling, including heatmap visualizations, and learned how to import OSM data into QGIS using the QuickOSM plugin.
Through this workshop, I gained practical skills in querying open geospatial data and understanding in the procedures and syntax to use when working with OSM data. I learned how to construct queries using bounding boxes, named areas, and proximity filters to extract specific features from the OSM database, and how to export results in formats like GeoJSON for use in GIS software. The session reinforced the value of open data platforms as accessible alternatives to proprietary mapping tools and expanded my understanding of how community-maintained datasets can be leveraged for research in fields such as public health, urban planning, and transportation.