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Using MCV Terminology for Mapping Metadata: Eurostat and OECD Experience

Learn how Eurostat and OECD utilize MCV Terminology for mapping metadata to achieve a common understanding of statistical data. This experience aims to standardize metadata concepts and improve data comparisons.

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Using MCV Terminology for Mapping Metadata: Eurostat and OECD Experience

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  1. Statistical Data and Metadata Exchange Using MCV Terminology for Mapping Metadata: Eurostat and OECD Experience Marco Pellegrino Eurostat Marco.Pellegrino@cec.eu.int Denis Ward OECD Denis.Ward@oecd.org

  2. Starting point Semantics is important to exchange • Problem: No universally accepted metadata framework • Aim: To develop a common understanding on meaning of:- general concepts (metadata, quality,…) - basic “atomic” metadata components MCV developed to partially address this

  3. SDMX MCV Glossary Fields • Title (mandatory) • Definition (mandatory) • Context for the definition (optional, but widely used) • Definition source (mandatory) • Links to related terms within the glossary (optional) • URL to more detailed information (optional)

  4. Terms in the MCV by categories(March 2006) Number of terms 384 of which: synonyms 29 Definitions 355 Terms used for describing statistical practices 209 Quality assessment concepts 100 General Metadata Concepts (ISO, UNECE,…) 147 Data exchange (GESMES/TS, SDMX) 125 Sources: Almost 70 different published documents or glossaries

  5. MCV Availability - SDMX website (Word, database, HTML/XML) – www.sdmx.org • Web glossaries (CODED, OECD) with extraction facilities Contains SDMX high-level concepts – content-oriented guidelines MCV concepts mapped to existing metadata frameworks • Eurostat Data Dissemination Format • OECD Metastore

  6. Glossary relationships Eurostat - OECD Glossaries (6 700) MCV (380) SDMX cross domain concepts (26)

  7. Expected benefits and use • Improved access to a set of standard definitions of metadata terms through a single entry point • Support to standardisation and consistency of metadata compiled • Facilitate comparisons across geographical entities • Support searching and comparing statistical data and metadata • Facilitate mapping of different metadata systems, as the MCV can be used independently from any specific metadata model

  8. OECD – Eurostat mapping to SDMX cross-domain concepts

  9. Glossary relationships Eurostat - OECD Glossaries (6 700) MCV (380) Eurostat / OECD Terminology SDMX cross domain concepts (26)

  10. Glossary relationships Eurostat - OECD Glossaries (6 700) MCV (380) Eurostat / OECD Terminology SDMX cross domain concepts (26) National terminology

  11. Glossary relationships Eurostat - OECD Glossaries (6 700) MCV (380) Eurostat / OECD Terminology SDMX cross domain concepts (26) National terminology

  12. Using MCV Terminology for Mapping Metadata: Eurostat and OECD Experience Thank you

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