As the integration of statistical data collected in various subject matter domains becomes more and more important in several socio-economic etc. investigation areas the management of so-called metadata - a formal digital processing of information about data - gains tremendously increasing relevance. Unlike current information technologies (e.g., database systems, computer networks, ...) facilitating merely the technical side of data collation, a coherent integration of empirical data still remains cumbersome, and thus rather costly, very often because of a lack of powerful semantic data models capturing the very meaning and structure of statistical data sets. Recognizing this deficiency, "Metadata Management" proposes a general framework for the computer-aided integration and harmonization of distributed heterogeneous statistical data sources, aiming at a truly comprehensive statistical meta-information system.
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As the integration of statistical data collected in various subject matter domains becomes more and more important in several socio-economic etc. investigation areas the management of so-called metadata - a formal digital processing of information about data - gains tremendously increasing relevance. Unlike current information technologies (e.g., database systems, computer networks, ...) facilitating merely the technical side of data collation, a coherent integration of empirical data still remains cumbersome, and thus rather costly, very often because of a lack of powerful semantic data models capturing the very meaning and structure of statistical data sets. Recognizing this deficiency, "Metadata Management" proposes a general framework for the computer-aided integration and harmonization of distributed heterogeneous statistical data sources, aiming at a truly comprehensive statistical meta-information system.
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