The aim of this paper is to discuss the organizational architecture and standard system for sharing research data at the national level The Data Sharing Network of Earth System Science (DSNESS) is one of the nine pilot projects of the ScientWc Data Sharing Project in China that has become a long-term operational research data-sharing platform in the National Science and Technology Infrastructure (NST1) of China. First, a data sharing union mechanism was designed with the core principle being, "data come from research and will be reused in research '. Second, a data sharing organizational architecture was constructed that consists of three sections: data resource architecture, data management architecture, and data services architecture. A physical data sharing network was constructed that includes one general center and 15 distributed sub-centers based on the architecture. Third, a series of data sharing standards and spec 4fIcations were designed and implemented in the DSJ'IESS. The reference model of the DSJVESS standard system includes three levels of standards: directive standards, general standards, and application standards. In total, 21 high level standards and specUlcations were developed and implemented in the DSJ'JESS. Several core standards and specfications, such as the extensible metadata standard, data quality control specfications, and so on, were analyzed in detail Finally, the data service effect was summarized in three aspects: dataset services, standard and spec Wcat ion services, and international cooperation services. This research shows that the organizational architecture and standard system is a very important soft environment for research data sharing. The practices of DSNESS will provide useful experiences for multi-disciplinary data sharing in Earth science and will hejp to eliminate the data gap between the rich and poor at the national level.
CITATION STYLE
Wang, J., Sun, J., Zhu, Y., & Yang, Y. (2013). A study on the organizational architecture and standard system of the data sharing network of earth system science in China. Data Science Journal, 12, 91–101. https://doi.org/10.2481/dsj.13-031
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