Towards the Automatic Ontology Generation and Alignment of Bim and Gis Data Formats

Abstract

Abstract. Establishing semantic interoperability between BIM and GIS is vital for geospatial information exchange. Semantic web have a natural ability to provide seamless semantic representation and integration among the heterogeneous domains like BIM and GIS through employing ontology. Ontology models can be defined (or generated) using domain-data representations and further aligned across other ontologies by the semantic similarity of their entities - introducing cross-domain ontologies to achieve interoperability of heterogeneous information. However, due to extensive semantic features and complex alignment (mapping) relations between BIM and GIS data formats, many approaches are far from generating semantically-rich ontologies and perform effective alignment to address geospatial interoperability. This study highlights the fundamental perspectives to be addressed for BIM and GIS interoperability and proposes a comprehensive conceptual framework for automatic ontology generation followed by ontology alignment of open-standards for BIM and GIS data formats. It presents an approach based on transformation patterns to automatically generate ontology models, and semantic-based and structure-based alignment techniques to form cross-domain ontology. Proposed two-phase framework provides ontology model generation for input XML schemas (i.e. of IFC and CityGML formats), and illustrates alignment technique to potentially develop a cross-domain ontology. The study concludes anticipated results of cross-domain ontology can provides future perspectives in knowledge-discovery applications and seamless information exchange for BIM and GIS.

Leveraging Standards in Model-Centric Geospatial Knowledge Graph Creation

“…-Geospatial XML Schema [25] extending the mappings based on [24] to take advantage of geospatial standards in the Semantic Web -Geospatial OWL ontologies created from UML models using the ISO 19150-2 standard [26] Thus far, an initial comparison of the resulting ontologies and datasets has been performed using the CityGML 2.0 and 3.0 conceptual models [26] within the context of improving the integration of 3D city model snapshots to model spatio-temporal building evolution. These data models were chosen for their rich vocabularies and widespread use in nD urban data research and industry.…”

“…-Conceptual data models (such as UML models) [6,11] -Physical data models (such as XML schema) [24] Top-down approaches using conceptual data model formats such as UML can exploit the similar modeling concepts and relationships to OWL (e.g. classes, attributes, properties, cardinality, etc.)…”

“…After a data model is expressed in OWL, it can be integrated with other OWL ontologies through alignment and ontology matching techniques [21]. In nD urban data integration, much research has been proposed with commonly implemented data models in Geographic Information Systems (GIS) and Building Information Modeling (BIM) [7,18,24], 3D Cultural Heritage Applications [17], and 4D urban data modeling [22].…”

Towards an Automated Transformation of an nD Urban Data Model to a Computational Ontology Network: From UML to OWL, From CityGML 3.0 to “CityOWL”

“…Alignments are typically declared pairwise between a set of ontologies in order to define an ontology network. There currently exist several automatic and manual ontology alignment approaches for nD urban data models and data (Usmani et al, 2021, Vilgertshofer et al, 2017.…”

A model-driven methodology for integrating heterogeneous 3D geospatial urban entities

“…The use of a model-driven transformation approaches towards knowledge graphs formats also allows users to reuse existing geospatial urban data knowledge graphs. Approaches such as ontology alignment (sometimes referred to as ontology matching) are powerful methods for integrating data models and data instances (Euzenat and Shvaiko;Usmani et al, 2021). This involves proposing links or correspondences between the concepts, relationships, or data instances of two ontologies.…”