1. What is SDMX?
2. SDMX Tutorials and related Material
– 2.1. The Business Case for SDMX
– 2.2. SDMX in a Nutshell
– 2.3. General and Technical Tutorials
– 2.4. Practical Use of SDMX-ML for the Publication of Statistical Data
– 2.5. Further Capacity Building Activities
– 2.6. Mapping of Existing Training Material available with Capabilities and Tools -draft
3. SDMX Use Case Examples
SDMX, which stands for Statistical Data and Metadata eXchange, is an ISO standard designed to describe statistical data and metadata, normalise their exchange, and improve their efficient sharing across statistical and similar organisations. It provides an integrated approach to facilitating statistical data and metadata exchange, enabling interoperable implementations within and between systems concerned with the exchange, reporting and dissemination of statistical data and their related meta-information.
It consists of:
- technical standards (including the Information Model)
- statistical guidelines
- an IT architecture and tools
But SDMX is not just a format for data exchange. Taken together, the technical standards, the statistical guidelines and the IT architecture and tools can support improved business processes for any statistical organisation as well as the harmonisation and standardisation of statistical metadata.
The first version of the SDMX technical standard (1.0) was finalised in 2004 and approved in 2005 by the International Organization for Standardization (ISO) as a Technical Specification (ISO/TS 17369: 2005 SDMX). Version 2.0 was approved in November 2005. Version 2.1 was issued in May 2011. In 2013, SDMX was published by the International Organization for Standardization (ISO) as International Standard (IS) 17369.
The Information Model which forms the core of SDMX has been developed to support statistics as collected and used by governmental and international statistical organisations, and this model is also applicable to other organisational contexts involving statistical data and related metadata.
The statistical guidelines aim at providing general statistical governance as well as common (“cross-domain”) concepts and code lists, a common classification of statistical domains and a common terminology. The first set of guidelines was published in January 2009.
Many IT tools have been developed to support the use and implementation of SDMX. Most of these tools are of an open source nature, so that they can be used as components for building IT systems in statistical organisations. Examples of such tools are the SDMX Registry, the Data Structure Wizard (DSW) and the SDMX Reference Infrastructure (SDMX-RI).
The work processes of SDMX are fully transparent: public consultations are conducted when major revisions are envisaged.
The first global SDMX data exchanges were implemented in 2013 by the seven sponsor organisations and covered National Accounts, Balance of Payments and Foreign Direct Investment. Many additional data exchanges are presently under development, both between international organisations and between international organisations and their constituencies.
2. SDMX Tutorials and related Material (Back to Table of Contents)
2.1. The Business Case for SDMX (Back to Table of Contents)
The purpose of this document is to introduce the business case for SDMX (English, French). The expected audience for this document is senior and middle management as opting for SDMX is a critical business choice rather than a technical choice.
Since the publication of version 1.0 of the technical specifications in 2004 the SDMX tools have been continuously improved and fine-tuned, and the number of global implementations is constantly growing, covering such domains as education statistics, labour statistics, national accounts, and sustainable development goals. The current revision work of the standard will be a step further towards a tailor-made solution for the exchange of statistical information. In this context any statistical organisation will at some point be confronted with the question of considering SDMX as a solution for harmonising and automating their data and metadata exchanges with international organisations or within their organisation, e.g. in the case of National Statistical Systems. Even countries that in the past did not adopt SDMX may reconsider their decision, taking into account the significant progress made over the years.
It is hoped that this business case will help the reader in making a well-informed analysis on the SDMX implementation.
Business case aspects for SDMX are also explained in detail in a document called “SDMX Starter Kit for National Statistical Agencies“.
2.2. SDMX in a Nutshell (Back to Table of Contents)
The “SDMX in a Nutshell” poster provides a general picture of the SDMX initiative.
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This poster presents, in a synthesised way, two types of information:
- The global framework in which SDMX operates. The document shows the interactions between SDMX and the three major statistical frameworks developed by the United Nations, namely the Generic Statistical Business Process Model (GSBPM), the Common Statistical Production Architecture (CSPA) and the General Statistical Information Model (GSIM).
- The general structure and organisation of SDMX. The SDMX governance structure has three levels: Sponsors Committee, SDMX Secretariat and SDMX working groups. The SDMX Sponsor Organisations are represented by the head of their statistical function in the SDMX Sponsors Committee. It is the ultimate decision-making body. The SDMX Secretariat, which is comprised of senior experts from the sponsoring organisations, provides executive support to the SDMX Sponsors Committee and is the interface between the sponsors and the working groups. The SDMX Technical Working Group (TWG) and the Statistical Working Group (SWG) report to the SDMX Secretariat. They maintain, improve or further develop the SDMX technical and statistical standards. The work processes of SDMX are fully transparent: public consultations are conducted when major revisions are envisaged.
2.3. General and Technical Tutorials (Back to Table of Contents)
The Statistical Office of the European Union (Eurostat) maintains two public portals for communicating, promoting and supporting the use of the SDMX standard. The SDMX InfoSpace is an official section of the Eurostat website dedicated to introducing users to all aspects of the Statistical Data and Metadata eXchange as well as providing answers to questions such as What, Why, Who and How SDMX is implemented. Tutorials on key components of the standard such as the Information Model, Data Structure Definition and Metadata Structure Definitions are available in English and Spanish. The Data and Metadata exchange group is hosted on Eurostat’s CROS Portal and enables interested users to learn about Eurostat’s IT architecture for data and metadata transmission and validation. The site includes information on each IT tool as well as dedicated user manuals. In addition, a number of short explanatory videos displaying some of the most common functionalities and corresponding test files are also accessible.
All these resources can be used as self-learning packages by any user who wishes to advance their SDMX knowledge via a concrete implementation case of the SDMX standard, supporting readers to:
- Learn what SDMX is about
- Learn why SDMX might be of interest to you and your organisation
- Find out about where and how SDMX is already making a difference
- Learn how data and metadata are exchanged across the European Statistical System
- Discover the standards that are used in the production, transmission and validation of data and metadata
- Find out more about Eurostat tools and learning opportunities that are available
- Get access to tools documentation, videos and most frequently questions that support self-learning
- Be informed about ongoing cooperation projects
More insight into the technicalities of SDMX can be found in the “SDMX User Guide“. The principal intention of this guide is help organisations and individuals to determine how best to use SDMX so as to help them to improve the statistical production process. In order to achieve this objective, examples are taken from real implementation scenarios that enable the reader to understand the scope of the SDMX standards and guidelines vis-à-vis the activities required to collect, process and publish statistical data and reference metadata.
2.4. Practical Use of SDMX-ML for the Publication of Statistical Data (Back to Table of Contents)
The website of the European Central Bank (ECB) offers a tutorial that introduces SDMX-ML using a practical example, i.e. the publication of the euro foreign exchange reference rates.
The tutorial looks at the technology from both sides of the fence: the side of the data provider (“How can we use SDMX-ML to publish statistical data on our website?”), and the side of the data consumer (“What kind of useful things can we do with an SDMX-ML data file?”).
To make the most of this tutorial, a basic knowledge of XML and XML-related technologies, such as XML schemas, XSLT and SAX, is required. Some of the tasks described in the tutorial will also require the use of an XML-validating parser and an XSLT processor.
2.5. Further Capacity Building Activities (Back to Table of Contents)
In odd years, the SDMX consortium organises SDMX Global Conferences. These conferences are generally organised in two parts: one where achievements and future developments are presented by the SDMX bodies and one for capacity building. It is also a major forum for listening to the needs of the wider statistical community. These conferences are publicly announced on the SDMX official website under “Events“.
In even years, the OECD organises meetings of the Expert Group on Statistical Data and Metadata Exchange. These meetings are organised in a similar way to the Global Conferences, and are also announced on the SDMX official website.
The training offer proposed by Eurostat can be found at this address. These training sessions are open to people from countries outside the European Union.
The training offer proposed by the OECD led SIS-CC .Stat Academy initiative can be found at this address. These online self-paced courses are free and open to everyone.
The “SDMX Implementation Checklist to Manage a SDMX Project ” presents a recommended step-by step approach to implement SDMX in a statistical domain.
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A specific checklist called “Checklist for SDMX Data Providers” has also been developed to help statistical agencies implement the provision of SDMX data based on existing structures, such as Global DSDs.
A LinkedIn page is also available to the SDMX community.
2.6. Mapping of Existing Training Material available with Capabilities and Tools -draft (Back to Table of Contents)
The SDMX Sponsor organisations are currently developing the SDMX Capacity Building Strategy which aims at improving the SDMX training cycle from design to delivery. In order to achieve this goal, and based on the identified capabilities, the existing SDMX training material has been grouped by capabilities and/or tools that are covered by them.
The early draft mapping will continue to be developed with existing training material not covered at this point as well as the identification of new capabilities. To access the excel file please click “here“
3. Use Case Examples (Back to Table of Contents)
Some “visualisation applications” based on SDMX can be accessed via the links below:
- The “Our statistics” website of the European Central Bank and the national central banks of the Eurosystem: the site aims to facilitate the understanding, use and comparison of euro area and national statistics. It gives a visual presentation of the statistics, uses user-friendly terms and is available in all official EU languages.
- International Monetary Fund Data Mapper: an application for plotting and comparing data from different countries and regions.
- European Central Bank ECBstatsApp mobile application: offers predefined data visualisations in a number of sections, e.g. key euro area indicators, government finance, exchange rates and prices. The app is available free of charge for iOS tablets via the link below (we stopped supporting the Android version since early March 2021)