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Statistical glossaries, classifications, and indicators are extracted, formalised, and semantically enriched through the analysis of materials collected in the document Library. These assets are then represented as semantic models ([[RDF>>https://www.w3.org/RDF/]], [[SKOS>>https://www.w3.org/2009/08/skos-reference/skos.html]], [[XKOS>>https://rdf-vocabulary.ddialliance.org/xkos.html]]), with persistent [[URIs>>https://www.w3.org/Addressing/URL/uri-spec.html]] and alignment across institutions, and serve as the foundation for the preparation and dissemination of linked open statistical data and smart metadata. |
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-For [[SDMX>>https://sdmx.org/]]-based structures, SKMS integrates with the [[Interoperability Basis platform>>https://basis.semanticip.org/xwiki/bin/view/Main/]], enabling the semantic transformation and publication of [[SDMX>>https://sdmx.org/]] [[concepts>>https://basis.semanticip.org/xwiki/wiki/sdmx/view/Glossary/]], [[code lists>>https://basis.semanticip.org/xwiki/wiki/sdmx/view/Models/]], and data structures in accordance with [[Linked Data>>https://www.w3.org/DesignIssues/LinkedData]] principles. |
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+For SDMX-based structures, SKMS integrates with the Interoperability Basis platform, enabling the semantic transformation and publication of SDMX concepts, code lists, and data structures in accordance with [[Linked Data>>https://www.w3.org/DesignIssues/LinkedData]] principles. |
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SKMS fosters the discovery, reuse, and interoperability of statistical data and metadata, providing a robust foundation for implementing the [[FAIR principles>>https://www.go-fair.org/fair-principles/]] across organizational and national boundaries. |
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