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SDMX as a Key Success Factor for Data Integration

Reinhold Stahl and Patricia Staab

Chapter Chapter 14 in Measuring the Data Universe, 2018, pp 107-109 from Springer

Abstract: 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.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-76989-9_14

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DOI: 10.1007/978-3-319-76989-9_14

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