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    Data quality screening for data reported from vessels and observers in the krill fishery

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    Numéro du document:
    WS-KFO-2023/04
    Auteur(s):
    K. Huang, D. De Pooter and S. Parker
    Soumis par:
    Daphnis De Pooter (Secrétariat de la CCAMLR)
    Approuvé par:
    David Agnew (Secrétariat de la CCAMLR)
    Résumé

    This study focuses on addressing data quality issues in the CCAMLR krill fishery database, particularly related to data consistency and accuracy. Historical data links between observer data and C1 vessel data were examined which resulted in 5660 newly created links. Data accuracy issues were also identified, including unit errors and missing values, which affect the analysis of fish by-catch in the krill fishery. To improve data quality, suggestions include enhancing the types of data checks, conducting regular diagnostics, and providing diagnostic tools for observers.