Towards FAIR and Interoperable Data through Semantics

Although semantic technologies are widely recognized as essential for digital transformation, their adoption in official statistics remains limited. Many existing data and metadata exchange standards — such as SDMX and SIMS — are developed within object-oriented frameworks and lack integration with Semantic Web technologies. Classifications and reference systems used in statistics often have no persistent URIs, making it difficult to build sustainable semantic metadata.

Interoperability Basis addresses these challenges through an open, non-profit platform that semantically enables existing standards. The platform supports semantic alignment, enrichment, and publication of models using a knowledge management system, modeling tools, namespace control, and persistent URI infrastructure.

By fostering international collaboration around semantic assets such as code lists and glossaries, the project supports the broader adoption of FAIR principles, scalable integration of Semantic Web technologies into information sharing and linked data dissemination, as well as the seamless use of interoperable data in AI-powered and user-friendly applications.
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