IREF499199false2026-05-13T05:25:18ZSDMX 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 a specific key variable this indicator can be calculated in two forms: a) for data producers, and b) for data users. The indicator shows to what extent statistics are available compared to what should be available. For producers, It can be used to evaluate the degree of compliance by a given Member State for a given dataset and period. For users, it can be used to: identify whether important variables are missing for some individual Member State or alternatively; give users an overall measurement (aggregate across countries and/or key variables) of the availability of statistics. The indicator should be accompanied by information about which variables are missing and the reasons for incompleteness as well as, where relevant, the impact of the missing data on aggregates, and plans for improving completeness in the future.RECOMMENDED_REPRESENTATIONStringRELATED_TERMSRelevance; Relevance - completeness; Relevance - user needs; Relevance - user satisfactionSOURCESDMX (2016) (https://sdmx.org/)Relevance - data completeness rateRatio of the number of data cells provided to the number of data cells required or relevant. The ratio is computed for a chosen dataset and a given period.