The Main Elements of SDMX

  • Reinhold Stahl
  • Patricia Staab


To explain the information model underlying the SDMX (Statistical Data and Metadata Exchange) standard, its building blocks, the SDMX artefacts, are first introduced. Starting with the basic elements needed to define a data structure, we then gradually add the surrounding elements, such as those used to describe a data set, build a data exchange process, or manage topic areas, actors and processes.

The conceptual world of SDMX is holistic enough to run an SDMX-based data warehouse. Two real-life examples can be found in the European Central Bank and the Deutsche Bundesbank. Of course, SDMX is also suitable for micro data, and with its multi-dimensionality and coded dimensions it provides the ideal interface for any data analysis software.

There are other standards and models apart from SDMX in statistics, some of which we briefly discuss in this chapter: the Generic Statistical Business Process Model (GSBPM), Generic Statistical Information Model (GSIM), Data Documentation Initiative (DDI) and eXtensible Business Reporting Language (XBRL).


  1. Eurostat (2016) Euro-SDMX metadata structure ESMS. Accessed 20 Feb 2017
  2. Gregory A, Heus P (2007) DDI and SDMX: complementary, not competing standards. Version 1.0. Jul 2007. Accessed 20 Feb 2017
  3. SDMX (2013a) SDMX 2.1 Technical specifications—consolidated version 2013—Section 3B—SDMX-ML. XML schemas, samples, WADL and WSDL (update 2013). Accessed 25 Jan 2016
  4. SDMX (2013b) SDMX 2.1 Technical specifications—consolidated version 2013. Accessed 25 Jan 2016
  5. UNECE (2013) Statistical metadata (METIS)/METIS-wiki/generic statistical information model/the Generic Statistical Business Process Model. Created, and most recently changed, by Thérèse Lalor on 23 December 2013. Accessed 20 Feb 2017
  6. UNECE (2016) Clickable SDMX/Clickable SDMX Home/SDMX Information Model. Created by Chris Jones. Most recently changed by Laura Vignola on 8 July, 2016. Accessed 20 Feb 2017
  7. UNECE (2017) The Generic Statistical Information Model (GSIM). Accessed 20 Feb 2017.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Reinhold Stahl
    • 1
  • Patricia Staab
    • 2
  1. 1.DornburgGermany
  2. 2.FrankfurtGermany

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