Abstract
In Semantic Web, modeling knowledge graph based on RDF becomes more and more popular. There is quite a lot of spatiotemporal information in Semantic Web, and recent works focus on not only general data but also spatiotemporal data. Existing efforts are mainly to add spatiotemporal labels to RDF, which expand RDF triple into quad or quintuple. However, extra labels often cause additional overhead for the system and lead to inefficient information organization management. In order to overcome this limitation, we propose an stRDFS model by labeling properties with spatiotemporal features and the corresponding determination methods of topological relations among different spatiotemporal entities. stRDFS considers spatiotemporal attribute as a part of the RDF model, which can record spatiotemporal information without changing the current RDF standard. Our approach improves the ability of recording and linking spatiotemporal data. More importantly, depending on formatting of spatiotemporal attributes in stRDFS, it will improve the semantic inferring ability, and the users are not required to be familiar with the underlying representations of spatiotemporal data.
Highlights
With the prompt development of the Internet, knowledge graph is rapidly emerging, which contributes a lot to the knowledge organization and intelligent application on the Internet [39], [40], and has significant meanings for artificial intelligence
RDF (Resource Description Framework), a language proposed by the World Wide Web Consortium (W3C), which can express the semantics of knowledge graph formally
This paper focuses on stRDF model, a structured spatiotemporal RDF developed from the spatial model GeoRDF, which is proposed by Koubarakis et al [28] and extended on the RDF
Summary
With the prompt development of the Internet, knowledge graph is rapidly emerging, which contributes a lot to the knowledge organization and intelligent application on the Internet [39], [40], and has significant meanings for artificial intelligence. Batsakis and Petrakis [5] establish standards of the Semantic Web and the 4D-fluents approach for representing the evolution of temporal information in entities. Spatial information in the RDF data model is usually represented as serializations of geometries accompanied with a Coordinate Reference System (CRS). Batsakis and Petrakis [6], [7] put forward SOWL, which Builds upon well established standards of the semantic Web and the 4D-fluents approach for representing the evolution of temporal information in ontologies. It is important to improve the model to record changing data and relations, and capture changes of massive dynamic spatiotemporal attribute values Motivated by such an observation, this paper aims to provide a spatiotemporal knowledge graph model on the basis of RDF without changing current RDF standard.
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