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

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## Abstract

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## 1. Introduction

## 2. Graphs

#### 2.1. Structural Graphs

#### 2.2. Spatial Graphs and Spatio-Temporal Graphs

#### 2.2.1. Spatial Graphs

#### 2.2.2. Granularity in Graphs

#### 2.2.3. Spatio-Temporal Graphs

#### 2.2.4. Spatio-Temporal Graphs and Semantic Graphs

#### 2.2.5. Graph Analysis

## 3. Knowledge Graphs

#### 3.1. Knowledge Graphs: Main Principles

#### 3.2. Spatio-Temporal Knowledge Graphs

## 4. Graphs and Knowledge Graphs in the Field of Maritime Transportation

#### 4.1. Large Maritime Graphs

#### 4.2. Ontology-Based and Knowledge Graph-Based Approaches in the Maritime Transport Domain

## 5. Discussion

#### 5.1. From Knowledge Graphs to Spatio-Temporal Graphs

#### 5.2. From Spatio-Temporal Graphs to Knowledge Graphs

## 6. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Conflicts of Interest

## References

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**Figure 2.**A spatio-temporal graph from [8]. $A,B,C,D$ and $CD$ are four spatial entities present at the first time ${t}_{1}$. $X\left({t}_{i}\right)$ represents the set of spatial entities present at time ${t}_{i}$. Spatial relations are denoted with plain lines, filiations are shown with dotted lines with labels $\gamma $ and $\delta $ to denote continuations and derivations and spatio-temporal relations are shown with a double line. C and D combine at time ${t}_{2}$ to a new entity $CD$ which derives from them. $CD$ continues at ${t}_{3}$ while A and B combine at ${t}_{3}$ to a new entity $AB$.

**Figure 3.**An RDF triple (N-Triples notation), referring to a Web resource about the Queen Mary boat, and its graphical representation.

**Figure 4.**A K-graph representing knowledge about a sailing ship A and a trawler B sharing the same home port P. Through the predicate

`rdf:type`, two ontologies, available in the LOD Cloud and describing a universe of boats and ports, respectively, are referred to.

**Figure 5.**An STK-graph extending the K-graph of Figure 4. Spatial knowledge (predicates in blue) has been added as the latitude and longitude coordinates of the port P and boats A and B, using the geonames ontology (https://www.geonames.org/ontology/documentation.html (accessed on 1 August 2021)) (prefix $gn$ is used). We suppose that time is contextual to the K-graph and corresponds to 12 July 2021 at 2:33 p.m. and 22 s, UTC +2.

**Figure 7.**Spatial distribution of ports in different trading communities [12].

**Figure 8.**Hub influence and diffusion in 2013 and 2016 [103].

**Figure 9.**An excerpt of the Maritime Container Ontology [112].

**Figure 10.**An excerpt of the DMG K-graph [118].

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**MDPI and ACS Style**

Del Mondo, G.; Peng, P.; Gensel, J.; Claramunt, C.; Lu, F. Leveraging Spatio-Temporal Graphs and Knowledge Graphs: Perspectives in the Field of Maritime Transportation. *ISPRS Int. J. Geo-Inf.* **2021**, *10*, 541.
https://doi.org/10.3390/ijgi10080541

**AMA Style**

Del Mondo G, Peng P, Gensel J, Claramunt C, Lu F. Leveraging Spatio-Temporal Graphs and Knowledge Graphs: Perspectives in the Field of Maritime Transportation. *ISPRS International Journal of Geo-Information*. 2021; 10(8):541.
https://doi.org/10.3390/ijgi10080541

**Chicago/Turabian Style**

Del Mondo, Géraldine, Peng Peng, Jérôme Gensel, Christophe Claramunt, and Feng Lu. 2021. "Leveraging Spatio-Temporal Graphs and Knowledge Graphs: Perspectives in the Field of Maritime Transportation" *ISPRS International Journal of Geo-Information* 10, no. 8: 541.
https://doi.org/10.3390/ijgi10080541