Wiki source code of Towards FAIR and Interoperable Statistical Data

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2.1	1	{{include reference="SUZ.Permissions.userUIPermissions.WebHome"/}}
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48.2	4	The Semantic Knowledge Management System (SKMS) is a platform for structuring and publishing institutional statistical knowledge using [[Semantic Web>>https://www.w3.org/2001/sw/wiki/Main_Page]] technologies. It transforms internal expertise, documents, and metadata into a coherent, machine-interpretable semantic environment.
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48.2	6	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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48.4	8	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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	10	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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48.2	17	Focus: Labour Statistics
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48.2	19	Labour statistics is the first domain within SKMS and serves as a practical demonstration of the platform’s capabilities. Based on documents from institutions such as the ILO and national statistical offices, key concepts, classifications, and indicators are formalised and semantically enriched.
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48.2	21	This process results in linked open statistical data and smart metadata describing employment, unemployment, working conditions, and other aspects of labour statistics — aligned with international standards and ready for cross-country use.
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48.2	23	The platform is ready to be enlarged by national statistical institutions and international organisations seeking to enhance the semantic quality and interoperability of statistical data.
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	25	[Explore our Semantic Labour Market section →] [[~[~[image:Labour Market Button.png~\|~\|height="52" width="185"~]~]>>doc:working:Main.WebHome]]
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48.3	28	Key Users
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48.3	30	The Semantic Knowledge Management System is designed to support a wide range of stakeholders involved in the production, coordination, and use of statistical knowledge:
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48.3	32	* National Statistical Offices
	33	* International Organisations (e.g. ILO, FAO, Eurostat, UNECE)
	34	* Statistical Methodology Experts
	35	* Knowledge Management Teams
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25.1	38	We welcome contributors, domain experts, and partner organizations to help advance semantic interoperability.
	39	To join the Interoperability Basis community or learn more, write to us at: [[info@semanticip.org>>mailto:info@semanticip.org]].
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