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Scientific Data Management and Application in High Energy Physics

机译:高能量物理学的科学数据管理和应用

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High energy physics experiments have been producing a large amount of data at PB or EB level, and there will be ambitious experimental programs in the coming decades. The efficiency of data-intensive researches is closely related to how fast data can be accessed and how many computational resources can be used. Changes in computing technology and large increases in data volume require new computing models. This paper will give an overall introduction to scientific data management technologies and applications in high energy physics. The current data management framework and workflow will be investigated at first. These include data acquisition, data transfer, data storage, data processing, data sharing and data preservation. Then some ongoing research and development on data organization, management and access will be introduced. Finally the EventDB, an event-based big scientific data management system will be introduced. The test on more than ten billion physics events shows the query speed is greatly improved than traditional file-base data management system.
机译:高能量物理实验在PB或EB水平上产生了大量数据,在未来几十年中将存在雄心勃勃的实验计划。数据密集型研究的效率与如何访问快速数据以及可以使用多少计算资源密切相关。计算技术的变化和数据量大增加需要新的计算模型。本文将全面介绍科学数据管理技术和高能量物理的应用。首先将研究当前的数据管理框架和工作流程。这些包括数据采集,数据传输,数据存储,数据处理,数据共享和数据保存。然后,将介绍关于数据组织,管理和访问的持续研究和开发。最后,将引入EventDB,将引入基于事件的大型科学数据管理系统。对超过100亿物理事件的测试显示了查询速度大大改善了传统的文件库数据管理系统。

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