Keyword: data-management
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TUPV046 Modification of Data Acquisition System in HLS-II Experimental Station experiment, data-acquisition, controls, synchrotron 506
  • Z. Zhang, G. Liu
    USTC/NSRL, Hefei, Anhui, People’s Republic of China
  With the proposal of the concept of super-facility in recent years, users of experimental stations only need to pay attention to data with scientific significance, and the management of massive experimental data are assisted by the super-facility technical support platform to effectively improve user efficiency. Based on this theory, we modified the data acquisition system of the XMCD experimental station in HLS-II. We continue to use LabVIEW software to reduce development workload. Meanwhile, we have added the interaction program with the high-level application in the original data acquisition process under the principle of keeping the user habits of XMCD experimental station. We have modularized the XMCD experimental software and redesigned the experimental architecture into 4 modules: Swiping Card Module, Experimental Equipment Control Module, Storage System Interaction Module and Data Management System Interaction Module. In this way, we have completed the collection of rawdata and metadata, the docking of the data persistent storage system, and the docking of data centralized management.  
poster icon Poster TUPV046 [1.640 MB]  
DOI • reference for this paper ※  
About • Received ※ 09 October 2021       Revised ※ 06 November 2021       Accepted ※ 15 January 2022       Issue date ※ 15 March 2022
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THPV036 Laser Driver State Estimation Oriented Data Governance experiment, laser, database, data-analysis 942
  • J. Luo, L. Li, Z. Ni, X. Zhou
    CAEP, Sichuan, People’s Republic of China
  Laser driver state estimation is an important task dur-ing the operation process for the high-power laser facility, by utilizing measured data to analyze experiment results and laser driver performances. It involves complicated data processing jobs, including data extraction, data cleaning, data fusion, data visualization and so on. Data governance aims to improve the efficiency and quality of data analysis for laser driver state estimation, which fo-cuses on 4 aspects ’ data specification, data cleaning, data exchange, and data integration. The achievements of data governance contribute to not only laser driver state estimation, but also other experimental data analy-sis applications.  
poster icon Poster THPV036 [0.477 MB]  
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About • Received ※ 10 October 2021       Revised ※ 24 October 2021       Accepted ※ 21 November 2021       Issue date ※ 22 February 2022
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