  CityGML is a widely adopted standard by the Open Geospatial Consortium (OGC)
for representing and exchanging 3D city models. The representation of semantic
and topological properties in CityGML makes it possible to query such 3D city
data to perform analysis in various applications, e.g., security management and
emergency response, energy consumption and estimation, and occupancy
measurement. However, the potential of querying CityGML data has not been fully
exploited. The official GML/XML encoding of CityGML is only intended as an
exchange format but is not suitable for query answering. The most common way of
dealing with CityGML data is to store them in the 3DCityDB system as relational
tables and then query them with the standard SQL query language. Nevertheless,
for end users, it remains a challenging task to formulate queries over 3DCityDB
directly for their ad-hoc analytical tasks, because there is a gap between the
conceptual semantics of CityGML and the relational schema adopted in 3DCityDB.
In fact, the semantics of CityGML itself can be modeled as a suitable ontology.
The technology of Knowledge Graphs (KGs), where an ontology is at the core, is
a good solution to bridge such a gap. Moreover, embracing KGs makes it easier
to integrate with other spatial data sources, e.g., OpenStreetMap and existing
(Geo)KGs (e.g., Wikidata, DBPedia, and GeoNames), and to perform queries
combining information from multiple data sources. In this work, we describe a
CityGML KG framework to populate the concepts in the CityGML ontology using
declarative mappings to 3DCityDB, thus exposing the CityGML data therein as a
KG. To demonstrate the feasibility of our approach, we use CityGML data from
the city of Munich as test data and integrate OpenStreeMap data in the same
area.
