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  • 标题:Data science for oceanography: from small data to big data
  • 本地全文:下载
  • 作者:Chengcheng Qian ; Baoxiang Huang ; Xueqing Yang
  • 期刊名称:Big Earth Data
  • 印刷版ISSN:2096-4471
  • 电子版ISSN:2574-5417
  • 出版年度:2022
  • 卷号:6
  • 期号:2
  • 页码:236-250
  • DOI:10.1080/20964471.2021.1902080
  • 语种:English
  • 出版社:Taylor & Francis Group
  • 摘要:The rapid development of ocean observation technology has resulted in the accumulation of a large amount of data and this is pushing ocean science towards being data-driven. Based on the types and distribution of oceanographic data, this paper analyzes the present and makes predictions for the future regarding the use of big and small data in ocean science. The ocean science has not fully entered the era of big data. There are two ways to expand the amount of oceanographic data to better understanding and management of the ocean. On the data level, fully exploit the potential value of big and small ocean data, and transform the limited, small data into rich, big data, will help to achieve this. On the application level, oceanographic data are of great value if realize the federation of the core data owners and the consumers. The oceanographic data will provide not only a reliable scientific basis for climate, ecological, disaster and other scientific research, but also provide an unprecedented rich source of information that can be used to make predictions of the future.
  • 关键词:Ocean science data;big data;small data
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