Most application that use 3D models in their process or workflows require them to have some kind of correctness. This needs to be assured by a validation process. The result of this process should be stored together with the 3D model for an easy access. This work proposes an ADE for CityGML to store the validation data with in the data structures of CityGML as meta data. This data can then be used in applications to ensure validity of input data.

Advanced analysis of spatio-temporal data is improving our knowledge about natural phenomena such as landslides and volcanic activity. Furthermore, it can contribute to a deeper understanding of the built environment by predicting city development. However, the data produced by the modelling of these observations can easily rise to terra bytes of 4D (3D space plus time) data. Also, the repeatability of such analysis is essential. Thus, repeatable and reliable access to big spatio-temporal data, models and simulation results should be guaranteed. However, today´s Geographic Information Systems (GIS) are not prepared to meet these requirements. Therefore, we present a comprehensive spatio-temporal data model for GIS and geodatabase management systems that can be used as the “heart” of 4D GIS. The comprehensive model enables a flexible management of time- series-based geometric and topological data. It cares of storage reduction and computational efficiency when storing, retrieving, and processing surface- and volume-based data in 3D space plus time. Furthermore, the model can handle geometry and topology changes of 4D data, i.e., mesh changes of triangulated surfaces and tetrahedral volumes over time. The model also allows the attachment of detailed semantic information to geometric and topological entities. The various concepts, implementation and the benefits of our comprehensive model are presented. Finally, conclusions are drawn from the approach and an outlook is given on future research including demanding applications based on multi-scale digital elevation models.

Adopting 3D City Index, a comprehensive 3D data scoring framework encompassing four categories -- data portals, model descriptions, thematic content, and semantic information, we assess and benchmark currently available 3D city models made accessible openly by governments worldwide. The 2025 update, including 47 datasets, reveals both the current situation and advancements in the open 3D data landscape since the previous benchmark 3 years ago. The heterogeneous landscape continues, with European cities demonstrating sustained progress, such as the datasets of Helsinki and Espoo. Japan as a country, performs well in the large-scale availability of 3D geoinformation. The trend analysis between 2022 and 2025 highlights measurable progress in the development of open 3D city models. Among the 28 datasets assessed in both years, 11 models show improvement, with an average increase of 2.5 points. While in general there is an improvement, many aspects declined, such as data portals and semantic richness. Further, the analysis implies an emerging trend toward large-scale harmonised initiatives at the state or national level, such as the PLATEAU project in Japan and Digital Twin Victoria in Australia. Such efforts indicate promise for standardised modelling, interoperability, and collaboration between governments, companies and research institutions. Understanding the current status and development of 3D city models, this work aims to inform improvements of 3D geoinformation and support broader adoption of 3D city models in research and practice.