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18 18  
19 19  == Linked Data ==
20 20  
21 -The World Wide Web Consortium (W3C) recommends Linked Data as the most effective way to publish data on the Internet. Linked Data is developed according to the principles of the Semantic Web — a global semantic infrastructure and a set of fundamental rules for representing data on the Internet in a way that allows information systems to interpret its meaning correctly.
21 +The World Wide Web Consortium ([[W3C>>https://www.w3.org/||rel="noopener noreferrer" target="_blank"]]) recommends Linked Data as the most effective way to publish data on the Internet. Linked Data is developed according to the principles of the [[Semantic Web>>https://www.w3.org/standards/||rel="noopener noreferrer" target="_blank"]] — a global semantic infrastructure and a set of fundamental rules for representing data on the Internet in a way that allows information systems to interpret its meaning correctly.
22 22  
23 -Linked Open Statistical Data (LOSD) refers to statistical datasets published as Linked Data under an open license such as CC BY 4.0, promoting free reuse and wide dissemination. Interoperability is achieved by creating, exchanging, and using LOSD in ways that preserve the meaning and context of the data, regardless of the systems involved.
23 +Linked Open Statistical Data (LOSD) refers to statistical datasets published as Linked Data under an open license such as [[CC BY 4.0>>https://creativecommons.org/licenses/by/4.0/||rel="noopener noreferrer" target="_blank"]], promoting free reuse and wide dissemination. Interoperability is achieved by creating, exchanging, and using LOSD in ways that preserve the meaning and context of the data, regardless of the systems involved.
24 24  
25 25  Human understanding and machine interpreting of statistical data is often difficult due to the lack of formalised domain knowledge and the absence of machine-readable, semantically enriched data. Poor semantic structure means that even published linked data can be hard to discover and accurately relate to domain concepts.
26 26  
27 -The High-Level Group for the Modernisation of Official Statistics (HLG-MOS), under the United Nations Economic Commission for Europe (UNECE), addresses the challenges of data interoperability within national statistical systems. It develops and promotes methods, models (including semantic models such as ontologies), and standards through coordinated initiatives. One of these initiatives is the Data Governance Framework for Statistical Interoperability (DAFI), published in 2023. This framework provides a reference model for implementing governance programs that support the creation, sharing, and use of data in ways that preserve semantic meaning across systems.
27 +The High-Level Group for the Modernisation of Official Statistics ([[HLG-MOS>>https://unece.org/statistics/networks-of-experts/high-level-group-modernisation-statistical-production-and-services||rel="noopener noreferrer" target="_blank"]]), under the United Nations Economic Commission for Europe ([[UNECE>>https://unece.org/ru]]), addresses the challenges of data interoperability within national statistical systems. It develops and promotes methods, models (including semantic models such as ontologies), and standards through coordinated initiatives. One of these initiatives is the Data Governance Framework for Statistical Interoperability (DAFI), published in 2023. This framework provides a reference model for implementing governance programs that support the creation, sharing, and use of data in ways that preserve semantic meaning across systems.
28 28  
29 29  Another priority of HLG-MOS is the development of rich (“smart”) metadata — metadata that is standardised (understandable and reusable across contexts), active (capable of driving statistical processes), and aligned with the FAIR principles: Findable, Accessible, Interoperable, and Reusable.
30 30  
31 31  We share these goals and move forward in step with HLG-MOS initiatives — SKMS already reflects key principles and objectives that resonate with this international agenda.
32 32  
33 -A key enabler of FAIR implementation in statistics is the use of semantic technologies for both data dissemination and the formalization of knowledge in the form of semantic models (semantic assets).  Semantic assets (SAs) are reusable formal representations of data such as: (1) metadata schemas (e.g. XML or RDF), (2) core data models or common models, (3) ontologies, thesauri, and reference data (e.g. code lists, taxonomies, glossaries). These assets are published as open data standards and used in the development of knowledge management systems, harmonizing indicators and classifications, and preparing LOSD. Semantic models support unambiguous interpretation, semantic search, and the discovery of data across disparate sources.
33 +A key enabler of FAIR implementation in statistics is the use of semantic technologies for both data dissemination and the formalization of knowledge in the form of semantic models (semantic assets). Semantic assets (SAs) are reusable formal representations of data such as: (1) metadata schemas (e.g. XML or RDF), (2) core data models or common models, (3) ontologies, thesauri, and reference data (e.g. code lists, taxonomies, glossaries). These assets are published as open data standards and used in the development of knowledge management systems, harmonizing indicators and classifications, and preparing LOSD. Semantic models support unambiguous interpretation, semantic search, and the discovery of data across disparate sources.
34 34  
35 35  The adoption of LOSD creates new opportunities for discovering, searching, comparing, and integrating statistical data from multiple sources through Semantic Web technologies, including semantic integration methods. This approach enables the achievement of the highest level of data maturity according to the 5-star model proposed by Tim Berners-Lee.
36 36  
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85 85  The Semantic Knowledge Management System relies on a set of well-established Semantic Web standards and vocabularies:
86 86  
87 87  * **FOAF (Friend Of A Friend)** – a vocabulary of named properties and classes for describing people and their relationships, built using RDF and OWL.
88 -[[url:https://xmlns.com/foaf/spec/]]
88 +[[url:https://xmlns.com/foaf/spec/||rel="noopener noreferrer" target="_blank"]]
89 89  * **vCard (The Electronic Business Card)** – a data format for representing and exchanging contact information about individuals and organizations (e.g. for phonebooks or email clients).
90 -[[https:~~/~~/www.w3.org/TR/vcard-rdf/>>url:https://www.w3.org/TR/vcard-rdf/]]
90 +[[https:~~/~~/www.w3.org/TR/vcard-rdf/>>url:https://www.w3.org/TR/vcard-rdf/||rel="noopener noreferrer" target="_blank"]]
91 91  * **OWL (Web Ontology Language)** – a language for defining and linking ontologies, supporting formal descriptions of concepts, properties, and relationships in the Semantic Web.
92 -[[https:~~/~~/www.w3.org/OWL/>>url:https://www.w3.org/OWL/]]
92 +[[https:~~/~~/www.w3.org/OWL/>>url:https://www.w3.org/OWL/||rel="noopener noreferrer" target="_blank"]]
93 93  * **Dublin Core™ Metadata Initiative (DCMI)** – a standard set of metadata terms used to describe a wide range of resources, including elements, encoding schemes, and syntax guidelines.
94 -[[https:~~/~~/www.dublincore.org/specifications/dublin-core/dces/>>https://https:www.dublincore.orgspecificationsdublin-coredces]]
94 +[[https:~~/~~/www.dublincore.org/specifications/dublin-core/dces/>>https://https:www.dublincore.orgspecificationsdublin-coredces||rel="noopener noreferrer" target="_blank"]]
95 95  * **RDF 1.1 Concepts and Abstract Syntax** – the foundational knowledge representation model of the Semantic Web, defining how RDF data is structured using triples.
96 -[[https:~~/~~/www.w3.org/TR/rdf11-concepts/>>url:https://www.w3.org/TR/rdf11-concepts/]]
96 +[[https:~~/~~/www.w3.org/TR/rdf11-concepts/>>url:https://www.w3.org/TR/rdf11-concepts/||rel="noopener noreferrer" target="_blank"]]
97 97  * **RDFS (RDF Schema 1.1)** – a vocabulary extension to RDF, providing classes and properties for defining basic ontologies and structuring RDF resources.
98 -[[https:~~/~~/www.w3.org/TR/rdf-schema/>>url:https://www.w3.org/TR/rdf-schema/]]
98 +[[https:~~/~~/www.w3.org/TR/rdf-schema/>>url:https://www.w3.org/TR/rdf-schema/||rel="noopener noreferrer" target="_blank"]]
99 99  * **RDF Data Cube Vocabulary** – a W3C vocabulary for publishing multidimensional statistical data in RDF, compatible with the SDMX cube model.
100 -[[https:~~/~~/www.w3.org/TR/vocab-data-cube/>>url:https://www.w3.org/TR/vocab-data-cube/]]
100 +[[https:~~/~~/www.w3.org/TR/vocab-data-cube/>>url:https://www.w3.org/TR/vocab-data-cube/||rel="noopener noreferrer" target="_blank"]]
101 101  * **SDMX (Statistical Data and Metadata Exchange)** – an international standard for the exchange of statistical data and metadata, supported by key statistical organizations.
102 -[[https:~~/~~/sdmx.org/>>url:https://sdmx.org/]]
102 +[[https:~~/~~/sdmx.org/>>url:https://sdmx.org/||rel="noopener noreferrer" target="_blank"]]
103 103  * **SKOS (Simple Knowledge Organization System)** – a W3C standard for representing knowledge organization systems such as thesauri, taxonomies, and classifications.
104 -[[https:~~/~~/www.w3.org/TR/skos-reference/>>url:https://www.w3.org/TR/skos-reference/]]
104 +[[https:~~/~~/www.w3.org/TR/skos-reference/>>url:https://www.w3.org/TR/skos-reference/||rel="noopener noreferrer" target="_blank"]]
105 105  * **SKOS-XL (SKOS eXtension for Labels)** – an extension of SKOS that allows for richer descriptions and relationships between lexical labels.
106 -[[https:~~/~~/www.w3.org/TR/skos-reference/skos-xl.html>>url:https://www.w3.org/TR/skos-reference/skos-xl.html]]
106 +[[https:~~/~~/www.w3.org/TR/skos-reference/skos-xl.html>>url:https://www.w3.org/TR/skos-reference/skos-xl.html||rel="noopener noreferrer" target="_blank"]]
107 107  * **XKOS (SKOS extension for statistical classifications)** – a vocabulary extending SKOS for describing statistical classifications and code lists, jointly developed by INSEE and Eurostat.
108 -[[https:~~/~~/rdf-vocabulary.ddialliance.org/xkos.html>>url:https://rdf-vocabulary.ddialliance.org/xkos.html]]
108 +[[https:~~/~~/rdf-vocabulary.ddialliance.org/xkos.html>>url:https://rdf-vocabulary.ddialliance.org/xkos.html||rel="noopener noreferrer" target="_blank"]]