Semantic integration of OpenStreetMap and CityGML with formal concept analysis

Volunteered geographic information (VGI) provides geometric and descriptive sources of geospatial data. VGI exchange, reuse, and integration are serious challenges due to the subjective contribution process, lack of organization, and redundancy. This study aims to enhance the quality of VGI semantic data by presenting a new approach to integrating and formalizing the VGI semantic knowledge using formal concept analysis. The proposed approach is assessed using the building tags in OpenStreetMap (OSM) and CityGML. The alignment process discovers the conceptual overlap between the categories of Amenity (Others), Office, and Man-Made in Map Features (OSM) and Business and Trade, Recreation, Sport, and Industry in AbstractBuilding (CityGML). The k-means clustering of the results illustrated that class, usage/function, address, wheelchair, and website/wikidata/wikipedia are significant attributes to describe building categories. Moreover, results showed that the analysis of frequent itemsets and cluster characteristics provides significant information about custom tags in OSM's editing tools.