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SDMX as a Key Success Factor for Data Integration

In: Measuring the Data Universe

Author

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  • Reinhold Stahl
  • Patricia Staab

Abstract

Data integration was already a major challenge for official statistics by the 1990s. The task at that time consisted of professionally harmonising the different national business phenomena and transferring the harmonised data sets via a file-based data exchange process into a uniform database. This was achieved with SDMX (Statistical Data and Metadata Exchange), but SDMX is much more. It is a non-technical model to classify any data world and thus come to a uniform view and approach to its data. Using SDMX, it was possible to build very extensive data collections on a variety of topics. It is, therefore, not worth waiting for a better standard. Since standards draw their strength from their dissemination and less from their genius, this would be futile. It is important to recognise the power in a potential standard, and then expand it and, above all, promote its dissemination.

Suggested Citation

  • Reinhold Stahl & Patricia Staab, 2018. "SDMX as a Key Success Factor for Data Integration," Springer Books, in: Measuring the Data Universe, chapter 0, pages 107-109, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-76989-9_14
    DOI: 10.1007/978-3-319-76989-9_14
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