Data science for oceanography: from small data to big data

IF 4.2 3区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Chengcheng Qian, Baoxiang Huang, Xueqing Yang, Ge Chen
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引用次数: 12

Abstract

ABSTRACT 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.
海洋学数据科学:从小数据到大数据
海洋观测技术的快速发展,积累了大量的数据,推动着海洋科学向着数据驱动的方向发展。根据海洋资料的种类和分布,分析了大数据和小数据在海洋科学中的应用现状,并对未来进行了展望。海洋科学还没有完全进入大数据时代。有两种方法可以扩大海洋学数据的数量,以更好地了解和管理海洋。在数据层面,充分挖掘大、小海洋数据的潜在价值,将有限的小数据转化为丰富的大数据,将有助于实现这一目标。在应用层面上,实现核心数据所有者和消费者的联合,海洋数据具有重要的应用价值。海洋学数据不仅将为气候、生态、灾害等科学研究提供可靠的科学依据,而且还将为预测未来提供前所未有的丰富信息来源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Big Earth Data
Big Earth Data Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
7.40
自引率
10.00%
发文量
60
审稿时长
10 weeks
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