This study adopts a statistical approach based on Exploratory Spatial Data Analysis to identify underlying contribution patterns of OpenStreetMap (OSM). Univariate and multivariate analyses on a number of variables computed from OSM history on a regular hexagonal grid in Milan (Italy) allow to detect a number of both local clusters and local outliers, which shed light on the complexity of OSM temporal evolution driven by active local contributors and communities, data imports and mapping parties.