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An integrated, semantically rich statistical metadata model is designed to cover the major stages of the statistical information processing (data collection and analysis including harmonization, processing of data and metadata and dissemination/output phases), which can minimize complexity of data warehousing environments and compatibility problems between distributed statistical information systems (SIS). The semantics of the model are analyzed, describing each part of the statistical processing. In addition, process metadata (operators) for automatic manipulation of both data and metadata are also defined over their common domain as well as logistic metadata for the location and format of data. Furthermore, we discuss how the proposed framework can facilitate actual information entry and analysis into a SIS. Finally, we demonstrate in a case study how the suggested metadata model can be implemented and integrated into a modern metadata-enabled SIS, thus standardizing the processing environment and assuring the quality of statistical results.