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Metadata Management in Statistical Information Processing [electronic resource] : A Unified Framework for Metadata-Based Processing of Statistical Data Aggregates / by Karl A. Froeschl.

By: Contributor(s): Material type: TextTextPublisher: Vienna : Springer Vienna : Imprint: Springer, 1997Edition: 1st ed. 1997Description: XII, 537 p. 98 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783709168561
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 025.04
LOC classification:
  • QA75.5-76.95
Online resources: In: Springer Nature eBookSummary: 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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Holdings
Item type Home library Collection Call number Status Date due Barcode Item holds
E-Book E-Book Biblioteca Digital Colección SPRINGER 025.04 (Browse shelf(Opens below)) Not For Loan
Total holds: 0

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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