Abstract
There are many new challenges in building Scientific Data Management System (SDMS), and the most initial and important one of them is designing a reasonably and effectively data architecture. The data architecture should focus on massive metadata, complex data flow, multi-classification data, various data productions and uniform query. Based on the applied projects, we present the classificatory criterions, data architecture, data flow, and query applications of SDMS in this paper as a case study. We propose the common solutions, conclude and share some experiences in the data architecture issues. These industrial experiences will be helpful to design data architecture and system of scientific data.
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