A Conceptual Framework of Representing Semantics for 3D Cadastre in Singapore

Abstract

The Land Survey Division of Singapore Land Authority (SLA) has recently embarked on LandXML to replace the existing in-house cadastral submission format for cadastral job processing. The rationale of adopting LandXML is to support automated job processing for cadastral job submissions from registered surveyors. LandXML is capable of capturing surveying data, such as traverses, parcels, and geometries; however, it falls short when representing the semantics of what is captured for automated job processing. This paper discusses a conceptual framework on how to support the semantic representation for LandXML using ontology in 3D cadastres. Ontology is not novel in the geospatial domain. It has been proven useful in many applications. Ontology is used to explicitly describe semantics by using a formal language, Web Ontology Language (OWL). OWL is a World Wide Web Consortium standard and a variant of XML (eXtensible Markup Language), but different from a standard XML, OWL is enriched with axioms for semantic definitions to build ontology. By interpreting the knowledge in the ontology, a system is able to perform certain operations automatically. In this paper, a 3D cadastral ontology is engineered to describe the concepts used in 3D cadastre for the context of Singapore. Important concepts such as land lots, airspace lots, subterranean lots, and strata lots are formalized in OWL. Using the axioms from OWL, such as ObjectAllValuesFrom and ObjectIntersectionOf, the paper demonstrates how these concepts can be described and represented more explicitly. In addition, each concept in OWL is referred with a unique URI (Uniform Resource Identifier). To support semantic representation for LandXML, the DocFileRef element in LandXML is linked with the corresponding URI in the OWL. When a LandXML is processed, the respective data can be reasoned with respect to the associated ontology in OWL. This eventually forms a two-tier framework, which consists of the Data Tier and the Knowledge Tier. The Data Tier stores the surveying data, while the Knowledge Tier captures the ontological knowledge. With this conceptual framework in place, it logically sets an important step to achieve the vision of ”Smart Cadastre”, which also emphasizes the semantic aspect of 3D cadastres.