IEEE Access (Jan 2020)

stRDFS: Spatiotemporal Knowledge Graph Modeling

  • Lin Zhu,
  • Nan Li,
  • Luyi Bai,
  • Yunqing Gong,
  • Yizong Xing

DOI
https://doi.org/10.1109/ACCESS.2020.3008688
Journal volume & issue
Vol. 8
pp. 129043 – 129057

Abstract

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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.

Keywords