1/14/2024 0 Comments 010 editor w3d templateThe logical foundations and CityGML-based conceptual schema used to describe cities in terms of the OntoCityGML ontology, together with the system of intelligent autonomous agents based on the JPS Agent Framework, make such systems capable of assessing and maintaining ground truths with certainty. We designed a Distance Agent to track the interactions with the model members on the web, calculate distances between objects of interest, and add new knowledge to the Cities Knowledge Graph. We developed a City Information Agent to help retrieve contextual information, provide data concerning city regulations, and work with a City Energy Analyst Agent that automatically estimates the energy demands for city model members. We designed a Thematic Surface Discovery Agent to automatically upgrade the model's level of detail to interact with thematic parts of city objects by other agents. We designed and developed a GeoSpatial Processor, an SQL2SPARQL Transformer, and a Geospatial Tiles Ordering tasks and integrated them into a City Export Agent to visualise and interact with city models on an augmented 3D web client. This paper presents a system architecture and a set of interfaces that can build scalable information systems capable of large city modelling based on dynamic geospatial knowledge graphs to avoid pitfalls of Web 2.0 applications while blending artificial and human intelligence during the knowledge enhancement processes. This knowledge persistence layer, developed to be compliant with the semantic web standards and recommendations provided by the W3C, is coupled with a system of intelligent autonomous agents designed upon principles of a cognitive architecture. As a knowledge graph built around the Semantic 3D City Database that is a semantic equivalent of the 3D City DB, originally developed at the Technische Universität München (TUM) for relational geospatial databases, it is designed to produce and process multi dimensional representations of urban environments modelled in accordance with the CityGML 2.0 standard by the Open Geospatial Consortium (OGC). Cities Knowledge Graph (CKG), an active research project collaboratively worked on by the Cambridge Centre for Advanced Research and Education in Singapore (CARES) and the Singapore-ETH Centre (SEC), is an example of a dynamic geospatial knowledge graph based on sustainable digitisation practices. This was achieved by evaluating scalable and dedicated data storage hardware capable of hosting expansible file systems, which strengthened the architectural foundations of the target system. The use of named graphs and namespaces for data partitioning ensured the system performance stayed well below its capacity limits. Efficient geospatial search algorithms allowed us to retrieve building data from any point in a city using coordinates. The structural isomorphism of the CityGML schemas and the OntoCityGML Tbox allowed the data to be transformed without loss of information. We also evaluated scalable hardware data solutions and file systems using the publicly available CityGML 2.0 data of Charlottenburg in Berlin, Germany as a working example. We compared various scalable technologies for this semantic data storage and chose Blazegraph™ as it provided the required geospatial search functionality. This allowed for the transformation of original data into a form of semantic triples. A corresponding data transformation tool, originally designed to work alongside CityGML, was extended. We comprehensively evaluated, repaired and refined an existing CityGML ontology to produce an improved version that could pass the necessary tests and complete unit test development. This paper presents a dynamic geospatial knowledge graph as part of The World Avatar project, with an underlying ontology based on CityGML 2.0 for three-dimensional geometrical city objects.
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