Collaborative toponyms in OpenStreetMap: an open-source framework to investigate the relationship with intrinsic quality parameters

Toponyms are crucial in providing spatial identities, as they characterize and give meaning and relevance to named geographical features. OpenStreetMap (OSM) has become a promising source of collaborative toponymic data, offering the potential to complement and update authoritative gazetteers by taking advantage of the dynamic nature of data updates and the local knowledge of contributors. However, updating official databases with collaborative data requires careful consideration and detailed understanding of the data quality. Although OSM is increasingly used in various geospatial applications, its role in supporting authoritative toponymic mapping remains relatively underexplored in the academic literature, particularly in terms of systematic methods for quality assessment. This study addresses this gap by presenting an open-source and reproducible framework capable of processing long-term OSM history data and extracting toponymic information across regular spatial grids, along with intrinsic quality indicators. The framework was applied in two different urban areas in Brazil, focusing on OSM features (amenity, building and leisure tags) with high potential for containing toponyms and semantic alignment with the Brazilian topographic mapping. The tool operates on 16 years of OSM data, demonstrating the spatial patterns of collaborative toponym contributions through the implementation of spatial statistical analysis. Moreover, the approach offers practical value for National Mapping Agencies (NMAs), providing a scalable method for assessing and potentially integrating collaborative toponyms into authoritative databases.