SDMX is the standard codifying the exchange of data and metadata across various information systems. SDMX standardizes formats for statistical information to be transferred from one step to another along the entire production process. An important component of SDMX, the common metadata vocabulary (MCV) offers internationally agreed definitions of metadata terminology.
SDMX 2.1 Technical Specification
The website contains reference technical specifications on the various components of SDMX: framework, information model, SDMX-ML, SDMX-EDI, registry specifications as well as web services guidelines.
One of the tools provided by the SDMX framework is the Contents-oriented guidelines. The Content-oriented Guidelines focus on the harmonization of specific concepts and terminology that are common to a large number of statistical domains. They cover Cross-Domain Concepts and Code List, that is definitions and recommended code lists, Metadata Common Vocabulary and Subject Matter Domain list.
SDMX IT tools and SDMX tutorials
This page contains the links to IT Tools repository. All tools have been categorized by feature type and by tool type and they can be searched according to these classifications. From the page it is also possible to access a set of e-learning videos explaining the technical standards and how to use them.
Published in the Conference Proceedings of the International Statistical Conference, Prague, Czech Republic, 14-15 September 2009 - "SDMX and the statistical production process"
In many organizations, the statistical production process is separated in different agencies according to the statistical domain, resulting in lack of harmonisation. The Statistical Data and Metadata eXchange (SDMX) initiative is to provide technical standards and content-oriented guidelines to improve mechanisms and processes for information exchanges between statistical organisations. It provides standard formats for data and metadata, together with content guidelines and IT architecture for their exchange. The document also describes the linkages between SDMX and the statistical production process by looking at the different phases of the statistical business process to identify how SDMX can be applied in each phase in order to gain efficiency.