An ontology-based approach to modeling ocean eddies in spatio-temporal objects

Yu Ma; Ting Li; Min Ji; Yawen He; Xiaodong Zhang

doi:10.1117/12.3007523

30 August 2023 An ontology-based approach to modeling ocean eddies in spatio-temporal objects

Yu Ma, Ting Li, Min Ji, Yawen He, Xiaodong Zhang

Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 127971N (2023) https://doi.org/10.1117/12.3007523
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China

Abstract

Due to the problem of the heterogeneous nature of ocean eddy data sets and the difficulty of expressing their spatio-temporal processes, there have been no satisfactory tools for integrated ocean eddy data management and spatio-temporal process analysis so far. Based on the semantic analysis idea of ontology, this paper proposes and constructs an ontology model of ocean eddies that provides a normative framework for organizing ocean eddy data based on the five-tuple O=(C,T,S,P,R) to solve the problem of heterogeneous sources and heterogeneity of data collection. For the continuous gradual change process of eddies, this paper constructs an evaluation system of ocean eddy development stages based on the entropy weight method, and provides a more accurate numerical analysis of the eddy evolution process through evaluation indexes. Finally, under the constraints of the above model, this paper proposes and constructs a spatio-temporal object data model of the ocean eddies, and maps the eddies into a graphical database based on "nodes" and "relations", which provides a new idea for the data organization and spatio-temporal process expression of the ocean eddies. The research results show that this strategy can effectively solve the heterogeneous problem of ocean eddy data and improve the efficiency of storage, retrieval and fusion of eddy data in different development stages, and provide reference for the integration and sharing of ocean eddy data and tracking and prediction.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yu Ma, Ting Li, Min Ji, Yawen He, and Xiaodong Zhang "An ontology-based approach to modeling ocean eddies in spatio-temporal objects", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 127971N (30 August 2023); https://doi.org/10.1117/12.3007523

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KEYWORDS

Data modeling

Semantics

Data storage

Modeling

Databases

Classification systems

Einsteinium

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