Abstract

Statistical organizations need to manage a comprehensive set of explicit metadata relating to the statistical data it manages to fully exploit the value of data. Data and metadata standards are foundational in a common understanding of the semantics of the data to ensure proper use and interpretation for data users. Statistics Canada has adopted international data and metadata standards, such as GSIM, SKOS/XKOS, DCAT, DDI, SDMX, and others as a means to deliver modern statistical capabilities. Over the last couple of years, Statistics Canada through the Enterprise Information and Data Management (EIDM) initiative has been elaborating the expected target state for data and metadata. As a key information system architecture principle, existing standards are used where applicable and are necessary for building sustainable architectures in support of statistical capabilities with optimal interoperability in mind.