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Distributed processing of spatiotemporal ocean data: a survey

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Abstract

Ocean data exhibits interesting yet human critical features affecting all creatures around the world. Studies on Hydrology and Oceanology become the root of many disciplines, including global resource management, macro economy, environment protection, climate predictions, etc, which motivates our further exploration on the underlying feature behind the ocean data. However, with high dimensionality, large quantities, heterogeneous sources, and especially, the spatiotemporal manner, the diversity between the specific knowledge required and massive data chunk puts forward unique challenges in data representation and knowledge mining, effectively. This paper tends to provide a summary of studies on these issues, including the data representation, data processing, knowledge discovery, and algorithms on finding unique patterns on ocean environment changes, such as temperature, tide height, waves, salinity, etc. In detail, we comprehensively discuss about ocean spatiotemporal data processing techniques. We further summarize related representation works on ocean spatiotemporal data, the construction of a ocean knowledge graph, and the management of ocean spatiotemporal data. At last, we combine and compare the collection of the evolution and multiple state-of-the-arts on ocean spatiotemporal data processing.

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Acknowledgements

We also acknowledge the editorial committee’s support and all anonymous reviewers for their insightful comments and suggestions, which improved the content and presentation of this manuscript.

Funding

This work is supported by National Key Research and Development Program of China No. 2018YFB1404303 and ICT Grant CARCHB202017. When we work on this manuscript, we also received grant QHWX-KY-22002 from NUDT and Provincial Key Research and Development Program of JiangXi 012031379055.

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Authors and Affiliations

  1. College of Meteorology and Oceanography, National University of Defensive Technology, Changsha, 410073, China

    Xiaoyong Li & Kaijun Ren

  2. College of Mathematics and Computer Science, Nanchang University, Nanchang, 330031, China

    Jingyun Gu, Guolong Tan, Wenjing Jiang, Ao Cui, Leiming Shu & Zichen Xu

  3. College of Computer Science and Technology, National University of Defensive Technology, Changsha, 410073, China

    Kaijun Ren

  4. Institute of Systems Engineering, Beijing, 100000, China

    Haoyang Zhu

  5. Thinvent Technology Co. LTD., Nanchang, 330000, China

    Jedi S. Shang

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  1. Xiaoyong Li
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  10. Zichen Xu
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Contributions

Xiaoyong Li worked on the full manuscript, Jingyun Gu wrote the Section 2-4, Guolong Tan and Wenjing Jiang prepared Section 5-6 and Figure 1-3, Ao Cui and Leiming Shu worked on the Section 1. Kaijun Ren, Haoyang Zhu and Jedi S. Shang participated in proofreading. Zichen Xu contributed to the proofreading work as well as Abstract and Section 7.

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Li, X., Gu, J., Tan, G. et al. Distributed processing of spatiotemporal ocean data: a survey. World Wide Web 26, 1481–1500 (2023). https://doi.org/10.1007/s11280-022-01067-6

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