ABSTRACT:Smart cities are applied to an increasing number of application fields. This evolution though urges data collection and integration, hence major issues arise that need to be tackled. One of the most important challenges is the heterogeneity of collected data, especially if those data derive from different standards and vary in terms of geometry, topology and semantics. Another key challenge is the efficient analysis and visualization of spatial data, which due to the complexity of the physical reality in modern world, 2D GIS struggles to cope with. So, in order to facilitate data analysis and enhance the role of smart cities, the 3 rd dimension needs to be implemented. Standards such as CityGML and IFC fulfill that necessity but they present major differences in their schemas that render their integration a challenging task. This paper focuses on addressing those differences, examining the up to date research work and investigates an alternative methodology in order to bridge the gap between those Standards. Within this framework, a generic IFC model is generated and converted to a CityGML Model, which is validated and evaluated on its geometrical correctness and semantical coherence. General results as well as future research considerations are presented.