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1. The development of [[glossaries>>doc:working:Glossary.WebHome||target="_blank"]] (the formation of detailed terminological articles), indicators descriptions based on the analysis of methodological documents, and then the generation of corresponding semantic assets. Refinement of hyper-text markup in accordance with modelled glossaries. |
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1. Publishing semantic assets generated in the SKMS. |
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1. Development, aligning and cataloging of necessary SA, code lists or other models of statistical domains in accordance with semantic standards. |
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-1. Importing datasets from external sources or data warehouses (DWH). Transformation of datasets using the [[RDF Data Cube Vocabulary>>https://www.w3.org/TR/vocab-data-cube/]], semantic enrichment. |
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+1. Importing datasets from external sources or data warehouses (DWH). Transformation of datasets using the [[RDF Data Cube Vocabulary>>https://www.w3.org/TR/vocab-data-cube/||target="_blank"]], semantic enrichment. |
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1. Visualization and validation of semantic models and LOSD sets. |
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1. Construction of rich metadata that is transmitted for publishing in external analytical systems. |
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-SKMS is based on the XWiki extension to using semantic technologies. It provides special templates for publishing documents, glossary terms, and indicator descriptions. They are used by domain experts to formalize statistical knowledge and provide their human-readable representation fixed in SAs. The LOSD pipeline is supported by generators and constructors developed to automate the formation of LOSD, semantic models and semantically enriched metadata. SKMS may be integrated with a cataloging service that supports not only the organisation of semantic assets, but also their visualization, access, and dissemination through standard interfaces such as [[OpenAPI>>https://www.openapis.org/]] and [[SPARQL Endpoints>>https://sparql.dev/article/SPARQL_endpoints_and_how_to_use_them.html]]. |
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+SKMS is based on the XWiki extension to using semantic technologies. It provides special templates for publishing documents, glossary terms, and indicator descriptions. They are used by domain experts to formalize statistical knowledge and provide their human-readable representation fixed in SAs. The LOSD pipeline is supported by generators and constructors developed to automate the formation of LOSD, semantic models and semantically enriched metadata. SKMS may be integrated with a cataloging service that supports not only the organisation of semantic assets, but also their visualization, access, and dissemination through standard interfaces such as [[OpenAPI>>https://www.openapis.org/||target="_blank"]] and [[SPARQL Endpoints>>https://sparql.dev/article/SPARQL_endpoints_and_how_to_use_them.html||target="_blank"]]. |
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== Benefits == |
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