Research on collaborative management method of Argo data

doi:10.3969/j.issn.1001-909X.2017.03.001

Abstract

Abstract: Argo data have become an important data source in basic researches of ocean and atmosphere sciences. But with the hybrid storage of profile metadata and its observations, it is difficult for existing shared platforms to realize the real-time visualizing of the drift trajectory and profile chart. A method of collaborative management of structured and semi-structured Argo data were proposed. Based on the analysis of Argo data structure and characteristics, Argo data were separated as structured and semi-structured data. By means of extended support of relational database to a semi-structured property, a relationship between profile metadata and observation data was established. Faced of the rapid growth of data, a multi-table storage method was used to reduce storage pressure of single data table. Finally, an Argo database was set up and global Argo data in period of 1997-2016 are parsed and imported. The results indicate that the method has good scalability of both storage and query, as well as high efficiency of float trajectory query, and it is able to support real-time visualization of float trajectory and profile chart. Our result will offer a reference for management of other similar observation profile data.

Key words: Argo data, profile, structured and semi-structured, collaborative management

CLC Number:

P71
TP311.52

DONG Gui-ying, CAO Min-jie, ZHANG Feng, DU Zhen-hong, LIU Ren-yi, WU Sen-sen. Research on collaborative management method of Argo data[J]. Journal of Marine Sciences, 2017, 35(3): 1-8.

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