This document discusses how spatial data analytics can support geo-ontology engineering. It analyzes spatial data from OpenStreetMap for two cities, Milan and London, to identify concepts that have different meanings in different places and characterize urban neighborhoods. The analysis identifies differences in how concepts like pubs are distributed between the cities. It also clusters hotspots of spatial features to define neighborhoods and computes scores to characterize neighborhoods based on prominent features. The results suggest concepts for ontology re-engineering and ways to semantically query and specify neighborhood concepts. Future work includes more tightly integrating the spatial analytics with ontology engineering processes.