4.5 Article

Leveraging Spatio-Temporal Graphs and Knowledge Graphs: Perspectives in the Field of Maritime Transportation

Journal

Publisher

MDPI
DOI: 10.3390/ijgi10080541

Keywords

graphs; spatio-temporal; knowledge graphs; maritime transportation

Funding

  1. French National Research Framework MAGIS [CNRS 2340]
  2. National Natural Science Foundation of China [41631177, 42001391]
  3. China Postdoctoral Science Foundation [2020T130644, 2019M660774]
  4. Chinese Academy of Sciences President's International Fellowship Initiative [2021VTA0002]

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This paper introduces a prospective study of the potential of spatio-temporal graphs and knowledge graphs for the modelling of geographical phenomena. It focuses on the principles behind K-graphs, their data representation, manipulation capabilities, and the integration of ST-graphs and K-graphs. The approach is illustrated and discussed in the context of maritime transportation.
This paper introduces a prospective study of the potential of spatio-temporal graphs (ST-graphs) and knowledge graphs (K-graphs) for the modelling of geographical phenomena. While the integration of time within GIS has long been a domain of major interest, alternative modelling and data manipulation approaches derived from graph and knowledge-based principles provide many opportunities for many application domains. We first survey graph principles and how they have been applied to GIS and a few representative domains to date. A comprehensive analysis of the principles behind K-graphs, respective data representation and manipulation capabilities is discussed. The perspectives offered by a close integration of ST-graphs and K-graphs are explored. The whole approach is illustrated and discussed in the context of maritime transportation.

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