Multisource spatial data integration for use cases applications

Abstract

The reuse and integration of data give big opportunities, supported by the FAIR data principles. Seamless data integration from heterogenous sources has been an interest of the geospatial community for a long time. However, 3D city models, building information models, and information supporting smart cities present higher semantic and geometrical complexity, which pose new challenges never tackled in a comprehensive methodology. Building on previous theories and studies, this article proposes an overarching workflow and framework for multisource (geo)spatial data integration. It starts from the definition of use case-based requirements for the integrated data, guides the analysis of integrability of the involved datasets, suggesting actions to harmonize them, until data merging and validation. It is finally tested and exemplified in a case study. This approach allows the development of consistent, well-documented, and inclusive data integration workflows, for the sake of use case automation in various geospatial domains and the production of interoperable and reusable data.