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BiBTeX citation export for THPV036: Laser Driver State Estimation Oriented Data Governance

  author       = {J. Luo and L. Li and Z. Ni and X. Zhou},
  title        = {{Laser Driver State Estimation Oriented Data Governance}},
  booktitle    = {Proc. ICALEPCS'21},
  pages        = {942--946},
  eid          = {THPV036},
  language     = {english},
  keywords     = {experiment, laser, database, data-analysis, data-management},
  venue        = {Shanghai, China},
  series       = {International Conference on Accelerator and Large Experimental Physics Control Systems},
  number       = {18},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {03},
  year         = {2022},
  issn         = {2226-0358},
  isbn         = {978-3-95450-221-9},
  doi          = {10.18429/JACoW-ICALEPCS2021-THPV036},
  url          = {https://jacow.org/icalepcs2021/papers/thpv036.pdf},
  abstract     = {{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.}},