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- W3046201747 abstract "Scientific data is a very important scientific asset and strategic resource, and it has become an irreplaceable key content in modern science and technology infrastructure. The open sharing of scientific data has received much attention and attention from the academic community, but in fact there is still resistance to wider dissemination and sharing. Based on the above background, the purpose of this article is to research on self-service analysis tools based on open sharing, and to transform the traditional individual self-service data analysis methods into active and efficient information sharing analysis tools through data integration of related information. Its core purpose is to provide open and shared self-service data analysis information and recommend shared resources on the platform with the best matching conditions. This article elaborates on the model from four aspects: overall goals, construction principles, infrastructure, and operation of the model. Finally, based on the investigation and analysis of the existing open sharing self-service analysis tools and their data sharing problems, and compared with the big data technology-driven data open sharing model, suggestions are made for the improvement of the existing model." @default.
- W3046201747 created "2020-08-03" @default.
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- W3046201747 date "2020-06-01" @default.
- W3046201747 modified "2023-09-25" @default.
- W3046201747 title "Self-Service Analysis Tools Based on Open Sharing" @default.
- W3046201747 doi "https://doi.org/10.1109/iwcmc48107.2020.9148510" @default.
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