Background: 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 objective of the course is to enable participants to understand the scope, architecture and features of SDMX, in particular those features that support more efficient processes for reporting, exchanging and disseminating statistical data and metadata. This will enable the to: - 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 marke, and the architecture that can be developed; - Understand how SDMX enables data harmonization across a system.
National statistical offices (NSOs); IT specialists; ministries of labour and related Institutions (such as labour observatories); governmental agencies responsible for labour-market data analysis and national SDG reporting; ILO social partners (employers' and workers' organizations); research and academic institutions; international organizations; development agencies; non-governmental organizations.