IREF380019false2026-05-13T02:06:40ZSDMX 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.CONTEXTThe term "variable" is meant here in the mathematical sense, i.e. a quantity which may take any one of specified set of values. It is convenient to apply the same word to denote non-measurable characteristics, e.g., "sex" is a variable in this sense since any human individual may take one of two "values", male or female. It is useful, but far from being the general practice, to distinguish between a variable as so defined and a random variable (The International Statistical Institute, "The Oxford Dictionary of Statistical Terms", edited by Yadolah Dodge, Oxford University Press, 2003).SOURCESDMX (2016) (https://sdmx.org/)Statistical variableCharacteristic of a unit being observed that may assume more than one of a set of values to which a numerical measure or a category from a classification can be assigned (e.g. income, age, weight, etc. and "occupation", "industry", "disease" etc.).