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Big Earth Data Volume 6, 2022 - Issue 2: Remotely sensed big data for the oceans and polar regions
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Secondary Literature Review Article

Data science for oceanography: from small data to big data

Chengcheng Qiana Department of Information and Files, North China Sea Marine Forecasting Center of State Oceanic Administration, Qingdao, ChinaORCID Iconhttps://orcid.org/0000-0002-4623-2128View further author information
ORCID Icon,
Baoxiang Huangb College of Computer Science and Technology, Qingdao University, Qingdao, ChinaView further author information
,
Xueqing Yangc Marine Division 1, Piesat Information Technology Co., Ltd, Beijing, ChinaView further author information
&
Ge Chend College of Information Science and Engineering, Ocean University of China, Qingdao, China;e Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, ChinaCorrespondence[email protected]
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Pages 236-250 | Received 04 Aug 2020, Accepted 04 Mar 2021, Published online: 26 May 2021

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Faris Hyder Ali & Shamsulhadi Bandi. (2022) Correlation between BIM data creation and big data attributes in construction. International Journal of Construction Management 0:0, pages 1-10.
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Xiao-Ming Li. (2022) Remotely sensed big data for the oceans and polar regions. Big Earth Data 6:2, pages 141-143.
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