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    Developing the Secretariat’s data management systems

    Request Meeting Document
    Document Number:
    SC-CAMLR-XXXV/BG/25 Rev. 1
    CCAMLR Secretariat
    Submitted By:
    Mr Andrew Wright (CCAMLR Secretariat)
    Approved By:
    Mr Andrew Wright (CCAMLR Secretariat)

    The CCAMLR Secretariat’s data management systems provide the secure infrastructure and repository for CCAMLR data which are submitted by CCAMLR Members to support the policy, scientific and administrative work of the Commission and Scientific Committee. These systems are being redeveloped as part of a long-term program of work which started in 2013. The work has focused on the development of structural and data elements of the enterprise data model, data warehouse, quality assurance, reference data, data extracts and metadata, and the appraisal of candidate systems for automated loading of, and reporting on, data submissions. These elements form the building blocks of the new system.

    This paper provides the background, key achievements to date and work plan for the redevelopment of the CCAMLR data management systems. It updates Members on key tasks associated with transition to a new data warehouse, development of data extracts and metadata, and the establishment of a data management group. The paper also outlines the anticipated changes, and associated benefits for users of CCAMLR data. The work plan implements the advice of SC-CAMLR and its Working Groups on data traceability, system testing and evaluation, user training, data extracts and metadata, and establishing a data management group.

    The user community can expect improvements in data quality assurance, database documentation and ease of use as the new system is progressively rolled out, including increased: integration across CCAMLR data; user-focussed documentation supporting data systems and CCAMLR data; availability of metadata libraries and data dictionaries; engagement, transparency and functionality relating to data submission; data quality assurance; dissemination of CCAMLR data and Secretariat support for data analytics and interrogation. 

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