As the title indicates, this page will cover the statistical aspects of the SDMX initiative. The activities concerned are twofold: a) harmonisation of concepts and terminology (Content-Oriented Guidelines), and b) development of guidelines for the creation and maintenance of SDMX artefacts such as code lists, data structure definitions, etc. This webpage is maintained by the SDMX Statistical Working Group (SWG), made of 20 members coming from national and international banking and statistical organisations.
CONTENT-ORIENTED GUIDELINES (COG)
The SDMX Content-Oriented Guidelines (COG) recommend practices for creating interoperable data and metadata sets using the SDMX technical standards. They are intended to be applicable to all statistical domains. The guidelines focus on harmonising specific concepts and terminology that are common to a large number of statistical domains. Such harmonisation is useful for achieving an even more efficient exchange of comparable data and metadata, and builds on the experience gained in implementations to date.
|● PART I – Introduction (Last update: 1 March 2014)|
|● PART II – Cross-Domain Concepts: PDF format, SDMX-ML format (from SDMX Global Registry), SDMX-ML format (from SDMX Technical Viewer) (Published in January 2009)|
|● PART III – Cross-Domain Code Lists|
|● PART IV – Statistical Subject-Matter Domains (Published in January 2009)|
|● PART V – Metadata Common Vocabulary (Published in January 2009)|
- Governance of commonly used SDMX metadata artefacts (Version 1.2, published on 26 March 2014)
These guidelines describe the SDMX governance model and the governance principles of the artefacts. They also deal with maintenance issues related to these artefacts. These guidelines are the basis when the SDMX standards are implemented in statistical domains.
- Guidelines for SDMX Data Structure Definitions (Version 1.0, published in June 2013)
The development of SDMX Data Structure Definitions (DSDs) in many statistical domains raised the need for guidance on the design of DSDs. The SDMX initiative now releases such guidelines based on conceptual considerations and first hand experiences with the development of DSDs.
The guidelines outline general design principles for DSDs such as reuse of existing concepts and code lists, and principles such as keeping the DSDs simple. They describe the different uses of DSDs, based on different user needs. The guidelines discuss the pros and cons of data structures in different domains. They provide context-specific recommendations instead of prescribing “the best” one-size-fits-all approach. For DSD designers, a step-by-step guide for designing the DSDs is also included.
- Guidelines for the creation and Management of SDMX Cross-Domain Code Lists (Version 1.0, formaly adopted 16 January 2014)
These guidelines are intended to support the creation of cross-domain code lists to be used all along the statistical business process and in particular when SDMX is implemented in statistical domains. They are strongly recommended for use when SDMX-compliant data structure definitions (DSDs) are built-up and implemented in statistical domains.
Additional information is provided in the following files:
- Mapping of SDMX Cross-Domain Concepts to metadata frameworks at international organisations (IMF-Data Quality Assessment Framework, Eurostat-SDMX Metadata Structure and OECD-Metastore) (Published in January 2009).
- Use of Cross-Domain Concepts in Data and Metadata Structure Definitions (Published in January 2009).
Draft versions of the Content-Oriented Guidelines (2006-2008) are available on request.
2. Additional statistical standards and guidelines
Under this heading we present additional statistical standards and guidelines produced by the different SDMX sponsoring or other organisations. These standards and guidelines are not part of the SDMX standards and guidelines; they might, however, be upgraded to SDMX standards and guidelines if the SDMX sponsors so decide.
Cross-domain code lists produced within the European Statistical System:
RAMON – the Eurostat Metadata Server.