As in many countries, in The Netherlands governmental organisations are acquiring 3D city models to support their public tasks. However, this is still being done within individual organisation, resulting in differences in 3D city models within one country and sometimes covering the same area: i.e. differences in data structure, height references used, update cycle, data quality, use of the 3D data etc. In addition, often only large governmental organisations can afford investing in 3D city models (and the required knowledge) and not small organisations, like small municipalities. To address this problem, the Dutch Kadaster is collaborating with the 3D Geoinformation research group at TU Delft to generate and disseminate a 3D city model covering the whole of the Netherlands and to do this in a sustainable manner, i.e. with an implementation that ensures periodical updates and that aligns with the 3D city models of other governmental organisations, such as large cities. This article describes the workflow that has been developed and implemented.

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3D environments allow advanced spatial navigation and visualization, but have traditionally provided limited support for performing non-spatial data analysis operations like filtering, joining, and integrating data on-the-fly. Linked Open Data provides advanced support for performing filters and joins over datasets that can be dynamically combined through SPARQL federation. Unfortunately, Linked Data results often lack intuitive visualization capabilities, making it relatively difficult to interpret the data for a data analyst. In this paper we present our integration of 3D visualization into the read-evaluate-print-loop of SPARQL query execution. We show how the inclusion of 3D visualization has concrete benefits for the SPARQL query writing process, and how our integrated solution is used to answer specific use cases that could not be answered before.@en