Spatiotemporal Data Modeling Based on RDF

Abstract

In semantic web, modeling knowledge graphs based on RDF is becoming more and more popular. 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 and lead to inefficient information organization management. Accordingly, the authors propose a spatiotemporal data model based on RDF, called stRDFS. This model achieves its functionality by labeling properties with spatiotemporal feature tags and determining the topological relations among different spatiotemporal entities. stRDFS considers spatiotemporal attributes as a part of the RDF model, which can record spatiotemporal information without changing the current RDF standard. This approach improves the ability to record and linking spatiotemporal data. More importantly, depending on the formatting of spatiotemporal attributes, it will improve the semantic inferring ability, and the users are not required to be familiar with the underlying representations of spatiotemporal data.