QualiOSM: An Architecture to Improve Data Completeness on OpenStreetMap - B. de Medeiros, Gabriel F.; C. Degrossi, Lívia; Holanda, Maristela (Journal of Information and Data Management, 2021)
OpenStreetMap (OSM) is a large spatial database in which geographic information is voluntarily contributed by thousands of users. In Geographic Information Systems (GIS), and more specifically, in Volunteered Geographic Information (VGI), as in the case of OSM, the issue of data completeness is a constant concern, since users without technical knowledge actively participate in the processes of including, editing and excluding data. Also in the case of OSM, users can add information to the objects assigning special labels for them. These labels are popularly called tags, and the process of assigning them to objects contributes to improving the attribute completeness, an important metric of data quality. In this context, this article proposes the QualiOSM architecture, which generates an automatic tag adder with the purpose of improving the completeness of address information for OSM objects in Brazil, using the reverse geocoding tools Nominatim, CEP Aberto and the database from Correios. The QualiOSM architecture showed good results for improving the completeness of city, neighborhood and street information in OSM objects, especially in scenarios of large urban centers, where the level of mapping is usually better compared to scenarios in rural or peripheral environments.