IREF381064false2026-05-13T02:08:25ZSDMX Cross Domain Concept SchemeThe Cross Domain Concept Scheme (starting from v2.0) is created from the set of concepts in the SDMX Glossary, which is an SDMX guideline containing concepts and related definitions that are useful for building and understanding data and metadata exchange arrangements based on SDMX. The Glossary provides definition of terms found in the SDMX Information Model, Data Structure Definitions (DSDs) and Metadata Structure Definitions (MSDs) at the time of the present release. It is recommended as a single entry point to a common SDMX terminology to be used in order to facilitate communication and understanding of the standard.In short, the overall message of the glossary is the following: if a term is used, then its precise meaning should correspond to the SDMX Glossary definition, and any reference to a particular phenomenon described in the SDMX Glossary should use the appropriate term.Version 1.0 of the SDMX Glossary, which replaces the Metadata Common Vocabulary (MCV) published in 2009, was finalised in February 2016. The Cross Domain Concept Scheme v1.0 was created from the MCV concepts.For any question, comment or correction, feel free to contact the SDMX Statistical Working Group (SWG) at the following address: swg@sdmx.org.CONTEXTFor each attribute specified in a data structure, there is a definition of whether this attribute takes: a value for each observation in the data set, or; a value for each time series in the data set, or; a value for each group in the data set, or; a single value for the entire data set. Some metadata concepts (e.g. frequency) may not be meaningful at the observation level, but only when applied to a higher level (e.g. to a time series of observations). Time, on the other hand, is meaningful at observation level, because every observation is associated with a specific point or period in time. Data Structure Definitions and Metadata Structure Definitions provide information about the level at which a particular concept descriptor is relevant: at observation level, time series level, group level, dataset level or even agency level. This is known as the "attachment level" of the concept.RELATED_TERMSAttribute; Attribute relationshipSOURCESDMX (2016) (https://sdmx.org/)Attachment levelProperty of an attribute defining the object to which data or metadata are linked.