The increasing availability of geospatial data has created new opportunities for urban planning, but it has also highlighted the challenges associated with managing heterogeneous datasets originating from different sources, formats, and collection methods. This thesis investigates the process of preparing pedestrian infrastructure data for integration into the municipal cartographic database of the City of Turin, with particular attention to the requirements of the INSPIRE framework for spatial data interoperability. The research focuses on the case study of Circoscrizione 1, the central district of Turin, where pedestrian-related datasets were collected and analyzed, according to the INSPIRE Transport Networks data model; the methodology involved the selection of the most appropriate INSPIRE layer, the harmonization of local data structures, and a validation process aimed at assessing the consistency, completeness, and geometric accuracy of the resulting dataset.