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Artur 1.2 1 (% class="wikigeneratedid" id="HTheproject22InteroperabilityBasis22isanopen2Cnon-profitinitiativeaimedatovercomingtechnologicalandorganizationalbarriersthathindertheeffectiveexchangeanddisseminationofLinkedData.Itsmaingoalistointegrateexistingdataexchangestandards2Cclassifications2CandreferencesystemsintotheSemanticWebenvironmenttoachievesustainablesemanticinteroperabilityacrossawiderangeofusersandusecases." %)
2 The project "//**Interoperability Basis**//" is an open, non-profit initiative aimed at overcoming technological and organizational barriers that hinder the effective exchange and dissemination of Linked Data. Its main goal is to integrate existing data exchange standards, classifications, and reference systems into the [[Semantic Web>>https://www.w3.org/2001/sw/wiki/Main_Page||rel="noopener noreferrer" target="_blank"]] environment to achieve sustainable semantic interoperability across a wide range of users and use cases.
Artur 1.1 3
4 == Relevance and Challenges ==
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6 Semantic Web technologies are among the key enablers of digital transformation. Over the past 15 years, the [[Linked Data (LD)>>https://www.w3.org/DesignIssues/LinkedData||rel="noopener noreferrer" target="_blank"]] approach has become a globally recognized practice for publishing and interlinking structured data on the web. Today, thousands of data providers worldwide follow these principles, publishing open datasets, metadata services via [[SPARQL>>url:https://www.w3.org/TR/sparql11-overview/||rel="noopener noreferrer" target="_blank"]] endpoints (interfaces for querying data using SPARQL), ontologies, and knowledge graphs.
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8 Despite this progress, the number of LD datasets in critical domains such as economics, statistics, and finance remain limited. Our research reveals several systemic barriers:
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Artur 1.4 10 * **Paradigm mismatch**: Modern data exchange standards (such as [[SDMX>>url:https://sdmx.org/||rel="noopener noreferrer" target="_blank"]], [[SIMS (ESS, ESMS, ESQRS)>>url:https://ec.europa.eu/eurostat/documents/64157/4373903/SIMS-2-0-Revised-standards-November-2015-ESSC-final.pdf/47c0b80d-0e19-4777-8f9e-28f89f82ce18||rel="noopener noreferrer" target="_blank"]], [[DDI>>https://ddialliance.org/||rel="noopener noreferrer" target="_blank"]], [[XBRL>>url:https://www.xbrl.org/Specification/XBRL-2.1/REC-2003-12-31/XBRL-2.1-REC-2003-12-31+corrected-errata-2013-02-20.html||rel="noopener noreferrer" target="_blank"]], [[UN/EDIFACT>>url:https://unece.org/trade/uncefact||rel="noopener noreferrer" target="_blank"]], [[NIEM>>url:https://www.niem.gov/||rel="noopener noreferrer" target="_blank"]], [[HL7>>url:https://www.hl7.org/||rel="noopener noreferrer" target="_blank"]]) are developed within an object-oriented paradigm, which is not inherently compatible with Semantic Web principles.
Artur 1.1 11 * **Lack of identifiers**: Widely used classifications and reference systems are typically published as tables, codelists, and hierarchies without persistent identifiers ([[URIs>>https://www.w3.org/Addressing/URL/uri-spec.html||rel="noopener noreferrer" target="_blank"]]), making integration in a Linked Data environment difficult.
12 * **URI persistence issues**: There is limited support for persistent URIs for elements of standards, classifications, and references, as well as poor handling of URI dereferencing, which reduces the long-term usability of data.
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14 **//Interoperability Basis//** aims to address these issues and support a broad transition to semantic technologies, enabling Linked Data to become a universal medium for data exchange and dissemination, in line with the [[FAIR principles>>url:https://www.go-fair.org/fair-principles/||rel="noopener noreferrer" target="_blank"]].
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16 == Goals and Objectives ==
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18 The goal of the //**Interoperability Basis**// is to overcome systemic barriers to the widespread adoption of Linked Data by semantically enabling existing object-oriented standards, classifications, and reference frameworks.
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20 We have created an open, non-profit platform that:
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22 * Enables the transformation of existing data exchange standards into semantic formats and loads them into a semantic knowledge management system.
23 * Supports a controlled namespace environment.
24 * Builds robust infrastructure for persistent URI management and dereferencing.
25 * Provides semantic models for constructing Linked Data and semantically annotated web services.
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27 We envision a future in which organizations, researchers, and developers interact with data without technological or semantic barriers. Semantic enrichment and contextual description within knowledge management systems ensure precise and unambiguous interpretation of information across diverse domains.
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29 //**Interoperability Basis**// is not just a tool, but a comprehensive platform for the collaborative creation, evolution, and sharing of knowledge, in which every participant becomes part of a global semantic network of interoperable data, standards, and tools.
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31 We transform interoperability from an abstract promise into a tangible and achievable reality.
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33 == Collaboration ==
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35 We invite partners to join us in the collaborative development of the //**Interoperability Basis**// international initiative:
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Artur 2.2 37 * **International organizations**: institutions developing and maintaining data standards (e.g., [[SDMX>>url:https://sdmx.org/]], [[SIMS>>url:https://ec.europa.eu/eurostat/documents/64157/4373903/SIMS-2-0-Revised-standards-November-2015-ESSC-final.pdf/47c0b80d-0e19-4777-8f9e-28f89f82ce18]], [[XBRL>>url:https://www.xbrl.org/]], [[DDI>>url:https://ddialliance.org/]], [[NIEM>>url:https://www.niem.gov/]])
38 ** (((
39 Can benefit from using a sustainable platform for expressing their standards as semantic assets: transform, enrich and align their structures and semantics; apply tools to convert/develop data schemas, vocabularies, and code lists into RDF/OWL; assign persistent URIs; manage the sections of their standards in the common namespace; maintain these discoverable, reusable, and interoperable assets across domains.
40 )))
41 * **Governments and public administrations**: state institutions seeking to improve data transparency, openness, and interoperability in public sector data and metadata
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43 Can release high-value datasets and classification systems based on semantically transformed, enriched and aligned standards provided by the platform. They can also benefit from sustainable publishing of public data using persistent URIs, semantically enhanced classifications, and interoperable APIs, while also aligning their open data with semantic standards to ensure long-term transparency and cross-border interoperability.
44 )))
45 * **Enterprises**: organizations focused on building corporate ecosystems based on semantic core to implement innovative semantic applications, web services, and data integration solutions
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47 Can leverage the platform as a foundation for building a corporate semantic core and for managing enterprise metadata in a consistent, standards-based way. This shared semantic infrastructure accelerates information sharing, supports digital transformation, and enables the development of AI applications that rely on high-quality, interoperable data. The platform’s persistent URIs and standardized semantic models help reduce implementation costs for scalable enterprise solutions
48 )))
49 * **Academic and research institutions**: universities and research centers working on semantic technologies and knowledge management across various domains
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51 Can benefit from an open, authoritative interoperability infrastructure that fosters international collaboration across research teams and disciplines. The platform supports joint pilot projects, semantic modeling studies, and contributions to the development and alignment of data standards, enabling researchers to actively participate in shaping the semantic foundations of global data exchange
52 )))
53 * **Semantic Web technology developers**: experts creating tools and platforms for working with [[RDF>>url:https://www.w3.org/RDF/]], [[OWL>>url:https://www.w3.org/OWL/]], [[SPARQL>>url:https://www.w3.org/TR/sparql11-overview/]], and other linked data technologies
54 ** (((
55 Can use the platform’s namespace to build and publish their own semantic assets with persistent URIs. Participation enables integration with real-world data ecosystems, early access to new semantic standards, and visibility within a community working on applied Linked Data solutions.
56 )))
Artur 1.1 57
58 == Stakeholders ==
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60 //**Interoperability Basis**// significantly increases the effectiveness of organizations committed to publishing Linked Data and smart metadata, promoting sustainable data exchange and integration, and establishing a reliable foundation for interoperability.
61 The project is designed for:
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63 * **Organizations publishing open data**
64 * **Statistical and analytical agencies**
65 * **Governmental and international bodies**
66 * **Academic and research groups**
67 * **IT companies and startups**
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69 By using //**Interoperability Basis**//, organizations not only apply advanced approaches in their work but also help shape an environment where high-quality data and open standards drive digital transformation and innovation.
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71 == Future Development ==
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73 //**Interoperability Basis**// is a growing initiative committed to enabling true interoperability, semantic integration of data, and accelerating the transition to Linked Data. The project will continue to expand the use of semantic technologies across domains such as statistics, finance, healthcare, international trade, and more.
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75 To support AI-driven applications, effective use of [[LLMs>>https://arxiv.org/html/2402.06196v2||rel="noopener noreferrer" target="_blank"]]: requires access to high-quality, structured, and semantically enriched data. //**Interoperability Basis**// enables:
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77 * **Access to formalized knowledge and classifications** — through RDF and OWL, AI models receive well-defined concepts with clear contextual relationships.
78 * **Machine-processable structures** — semantic models and annotated APIs allow LLMs to interpret data without manual reformatting.
79 * **Enrichment of training datasets** — integrating semantically described thesauri, glossaries, standards, and statistical datasets into model training pipelines.
80 * **Support for explainable AI** — modern LLMs can leverage ontologies and knowledge graphs not just to generate responses, but to construct logical, interpretable outputs when analyzing Linked Data, referencing verifiable sources and using contextualized semantics.
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82 //**Interoperability Basis**// provides a vital layer of infrastructure for the development of intelligent agents capable of interpreting and applying structured knowledge in both applied and research domains.