SDMX, which stands for Statistical Data and Metadata eXchange is an international initiative that aims at standardising and modernising (“industrialising”) the mechanisms and processes for the exchange of statistical data and metadata among international organisations and their member countries.[1]

The SDMX sponsoring institutions are the Bank for International Settlements (BIS), the European Central Bank (ECB), Eurostat (the statistical office of the European Union), the International Monetary Fund (IMF), the Organisation for Economic Co-operation and Development (OECD), the United Nations Statistics Division (UNSD), and the World Bank.

These organisations are the main players at world and regional levels in the collection of official statistics in a large variety of domains (agriculture statistics, economic and financial statistics, social statistics, environment statistics etc.).

The latest version of the SDMX – SDMX 2.1 – was released in May 2011[2], and was approved by ISO as International Standard (ISO 17369:2013) [3] in 2013.

People who are new to SDMX are invited to consult the “Learning about SDMX Basics” page which will provide them with the necessary basic material for understanding SDMX.

Users who are already familiar with the SDMX standard will find on the website all material, such as the technical standards and guidelines necessary for properly implementing SDMX in a statistical domain.

Technical Standards

SDMX message formats have two basic expressions, SDMX-ML (using XML syntax) and SDMX-EDI (using EDIFACT syntax and based on the GESMES/TS statistical message). The standards also include additional specifications (e.g. registry specification, web services). Version 1.0 of the SDMX standard has been recognised as an ISO standard in 2005.[4] The RDF Data Cube vocabulary implements the cube model underlying SDMX as Linked Data.[5]

See also


  1. ^ "SDMX – Statistical Data and Metadata eXchange - Welcome to the SDMX website". Retrieved 5 April 2018.
  2. ^ "Learning". SDMX – Statistical Data and Metadata eXchange. Retrieved 25 July 2018.
  3. ^ "ISO 17369:2013 - Statistical data and metadata exchange (SDMX)". Retrieved 5 April 2018.
  4. ^ "ISO/TS 17369:2005 - Statistical data and metadata exchange (SDMX)". Retrieved 5 April 2018.
  5. ^ "Three Linked Data Vocabularies are W3C Recommendations". W3C. 16 January 2014.

Free SDMX tools

  • There exist a number of free tools for conversion, visualisation and validation of SDMX, as well as free implementations of the SDMX registry. An overview of the available tools by function and source is available in the tools section of the SDMX web site.
  • SdmxSource is a Java implementation of the SDMX standard supporting SDMX-ML 2.1, 2.0, 1.0 and SDMX-EDI.

External links


A census is the procedure of systematically acquiring and recording information about the members of a given population. The term is used mostly in connection with national population and housing censuses; other common censuses include agriculture, business, and traffic censuses. The United Nations defines the essential features of population and housing censuses as "individual enumeration, universality within a defined territory, simultaneity and defined periodicity", and recommends that population censuses be taken at least every 10 years. United Nations recommendations also cover census topics to be collected, official definitions, classifications and other useful information to co-ordinate international practice.The word is of Latin origin: during the Roman Republic, the census was a list that kept track of all adult males fit for military service. The modern census is essential to international comparisons of any kind of statistics, and censuses collect data on many attributes of a population, not just how many people there are. Censuses typically began as the only method of collecting national demographic data, and are now part of a larger system of different surveys. Although population estimates remain an important function of a census, including exactly the geographic distribution of the population, statistics can be produced about combinations of attributes e.g. education by age and sex in different regions. Current administrative data systems allow for other approaches to enumeration with the same level of detail but raise concerns about privacy and the possibility of biasing estimates.A census can be contrasted with sampling in which information is obtained only from a subset of a population; typically main population estimates are updated by such intercensal estimates. Modern census data are commonly used for research, business marketing, and planning, and as a baseline for designing sample surveys by providing a sampling frame such as an address register. Census counts are necessary to adjust samples to be representative of a population by weighting them as is common in opinion polling. Similarly, stratification requires knowledge of the relative sizes of different population strata which can be derived from census enumerations. In some countries, the census provides the official counts used to apportion the number of elected representatives to regions (sometimes controversially – e.g., Utah v. Evans). In many cases, a carefully chosen random sample can provide more accurate information than attempts to get a population census.

Data dissemination

Data dissemination is the distribution or transmitting of statistical, or other, data to end users. There are many ways organisations can release data to the public, i.e. electronic format, CD-ROM and paper publications such as PDF files based on aggregated data.

The most popular dissemination method today is the ‘non-proprietary’ open systems using internet protocols. “They are used in data dissemination through various communication infrastructures across any set of interconnected networks.” Data is made available in common open formats.

Some organisations choose to disseminate data using ‘proprietary’ databases in order to protect their sovereignty and copyright of the data. Proprietary data dissemination requires a specific piece of software in order for end users to view the data. The data will not open in common open formats. The data is first converted into the proprietary data format, and specifically designed software is provided by the organisation to users.

Dissemination formats and standards

Under the Special Data Dissemination Standard, the formats are divided into two categories: "hardcopy" and "electronic" publications

Some examples of Hardcopy publications:


panorama of municipalities

monthly review



periodicalSome examples of electronic copy publications:

CD Rom



Downloadable Databases for private use in 3rd party software applicationsStandards

Standards have been developed in order to provide an internationally accepted statistical methodology for the dissemination of statistical data. The ‘International Organization for Standardization’ (ISO) are one such international standard-setting body made up of representatives from various national standards organizations. They created the SDMX standard widely used around the world.

SDMX stands for ‘Statistical Data and Metadata Exchange’. It is commonly used in national and international statistical and economic data sharing systems. This standard is for the exchange of essential social and economic statistics, for example between European national agencies and Eurostat and the European Central Bank.

SDMX is used for the dissemination of multi-dimensional aggregated data.

The Data Documentation Initiative (DDI) was created by the DDI Alliance. DDI is an open metadata specification and covers the full data life cycle from planning through to dissemination and archiving data. It is most popularly used for social statistics micro data but is not limited to this subject area.

There are some examples online where these two standards are in use in proprietary data form. The following portals provide users with access to statistical data online from leading statistical agencies:

Some examples of proprietary data dissemination online

Public Transport Victoria Online Portal

Health Workforce Australia Online Portal

Cancer Council Victoria Online Portal

Catholic Education Office Canberra Online Portal

Department of Workplace and Pensions UK Online Portal

Australian Bureau of Statistics Table builder Table Builder Online Portal

King Faisal Specialist Hospital Research Centre Online Portal


DevInfo is a database system developed under the auspices of the United Nations and endorsed by the United Nations Development Group for monitoring human development with the specific purpose of monitoring the Millennium Development Goals (MDGs), which is a set of Human Development Indicators. DevInfo is a tool for organizing, storing and presenting data in a uniform way to facilitate data sharing at the country level across government departments, UN agencies and development partners. It is distributed royalty-free to all UN member states. It is a further development of the earlier UNICEF database system ChildInfo.

The Global DevInfo Initiative, led by UNICEF on behalf of the UN system, is dedicated to furthering human development by offering information technology-based solutions aimed at addressing development-related challenges. This is achieved by integrating management information systems, geographic information systems, software training, technical support services, data dissemination solutions and technical publications. The DevInfo Initiative takes a strategic approach towards strengthening the monitoring and evaluation capacity of governments and agencies by developing innovative technological solutions to better track human development progress.


GESMES/TS (GEneric Statistical MESsage for Time Series) is a data model and message format

appropriate for performing standardised exchange of statistical data and related metadata.

It is based on the GESMES message (a UN/CEFACT standard using the EDIFACT syntax).

Its most common use is in the exchange of official statistics.

The data model is optimised to represent multi-dimensional arrays of floating point numerical data where one dimension is time.

The essential design pattern resembles a star schema.

GESMES/TS promotes automation by its ability to explicitly declare the dimensions and allowable metadata fields in a standardised way.

Software can then translate these declarations into a database schema suitable to hold the multi-dimensional data.

This mechanism makes GESMES/TS versatile enough for efficient use in many domains.

The initial name of GESMES/TS was GESMES/CB (GEneric Statistical MESsage for Central Banks),

but has been changed in order to reflect its wider application.

The model and format are maintained under the auspices of the SDMX initiative.

In this context, GESMES/TS is known as SDMX-EDI.

Google Public Data Explorer

Google Public Data Explorer provides public data and forecasts from a range of international organizations and academic institutions including the World Bank, OECD, Eurostat and the University of Denver. These can be displayed as line graphs, bar graphs, cross sectional plots or on maps. The product was launched on March 8, 2010 as an experimental visualization tool in Google Labs.In 2011 the Public Data Explorer was made available for anyone to upload, share and visualize data sets. To facilitate this, Google created a new data format, the Dataset Publishing Language (DSPL). Once the data is imported, a dataset can be visualized, embedded in external websites, and shared with others like a Google Doc.In 2016, this toolset was enhanced with the Google Analytics Suite, particularly Data Studio 360, whose release expanded to a free public beta in May 2016, which enabled import of public or individual datasets and overlaid user-friendly (non-coding) data visualization tools.

International Financial Statistics

The IMF International Financial Statistics (IFS) is a compilation of financial data collected from various sources, covering over 200 countries worldwide, which is published monthly by the International Monetary Fund (IMF).

Lighting control console

A lighting control console (also called a lightboard, lighting board, or lighting desk) is an electronic device used in theatrical lighting design to control multiple lights at once. They are used throughout the entertainment industry and are normally placed at the Front of House (FOH) position or in a control booth.All lighting control consoles can control dimmers which control the intensity of the lights. Many modern consoles can control Intelligent lighting (lights that can move, change colors and gobo patterns), fog machines and hazers, and other special effects devices. Some consoles can also interface with other electronic performance hardware (i.e. sound boards, projectors, media servers, automated winches and motors, etc.) to improve synchronization or unify their control.

Lighting consoles communicate with the dimmers and other devices in the lighting system via an electronic control protocol. The most common protocol used in the entertainment industry today is DMX512, although other protocols (e.g. 0-10 V analog lighting control) may still be found in use, and newer protocols such as ACN and DMX-512-A are evolving to meet the demands of ever increasing device sophistication.

List of International Organization for Standardization standards, 16000-17999

This is a list of published International Organization for Standardization (ISO) standards and other deliverables. For a complete and up-to-date list of all the ISO standards, see the ISO catalogue.The standards are protected by copyright and most of them must be purchased. However, about 300 of the standards produced by ISO and IEC's Joint Technical Committee 1 (JTC1) have been made freely and publicly available.

List of types of XML schemas

This is a list of notable XML schemas in use on the Internet sorted by purpose. XML schemas can be used to create XML documents for a wide range of purposes such as syndication, general exchange, and storage of data in a standard format.


Metadata is "data [information] that provides information about other data". Many distinct types of metadata exist, among these descriptive metadata, structural metadata, administrative metadata, reference metadata and statistical metadata.

Descriptive metadata describes a resource for purposes such as discovery and identification. It can include elements such as title, abstract, author, and keywords.

Structural metadata is metadata about containers of data and indicates how compound objects are put together, for example, how pages are ordered to form chapters. It describes the types, versions, relationships and other characteristics of digital materials.

Administrative metadata provides information to help manage a resource, such as when and how it was created, file type and other technical information, and who can access it.

Reference metadata describes the contents and quality of statistical data

Statistical metadata may also describe processes that collect, process, or produce statistical data; such metadata are also called process data.

ISO standards by standard number

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