SDMX – STATISTICAL DATA AND METADATA EXCHANGE

Statistical data exchanges often take place in an ad-hoc manner, using all kinds of formats and non-standard concepts, hence the need for common standards, guidelines and tools to enable more efficient processes for exchanging and sharing statistical data and metadata. SDMX (Statistical Data and Metadata eXchange) is an international initiative that aims to standardize and modernize (“industrialize”) the mechanisms and processes for the exchange of statistical data and metadata among international organizations and their member countries. The standard has evolved in recent times, going beyond straightforward data exchange and now enabling more efficient and reliable data storage and dissemination. SDMX is a business choice (as opposed to a technical choice), improving the quality of statistical data-processing and exchange through standardization, automation, validation and data-sharing. SDMX is a standard (indeed an ISO standard, 17369:2013) designed to describe statistical data and metadata, normalize their exchange and enable them to be shared more efficiently among organizations. To meet these three requirements, SDMX has three key components: 1. Technical standards (including the Information Model); 2.Statistical guidelines; 3. An IT architecture and tools. SDMX is therefore much more than a mere data-transmission format. All labour market information (LMI) systems implemented with the assistance of the ILO are based on and make intensive use of SDMX. The International Training Centre of the ILO (ITCILO) in close coordination with the ILO Department of Statistics is proud to present the First Edition of the course SDMX - Statistical Data And Metadata Exchange to take place online between the 6th and the 17th of November, 2023. OBJECTIVES • Assess how to take advantage of SDMX in their day-to-day work; • Understand DSDs and MSDs, and how they reflect requirements for data and metadata exchange; • Work together (statisticians and IT specialists within an organization) in planning for SDMX in their domain; • Learn how to model data in using SDMX for data-exchange, storage and/or dissemination; • Understand the relationship between SDMX and the production of statistics; • Understand the different roles of organizations in the collection and production of statistics and their relationship with SDMX; • Understand (in broad terms) the different tools available in the market, and the architecture that can be developed; • Understand how SDMX enables data harmonization across a system. CONTENT • Introduction to SDMX • SDMX Tools • SDMX data modelling • SDMX implementation scenarios • SDMX dissemination A-to-Z example NUMBER OF HOURS: 25