Statistical Indicators in the Labour Market and other domains are described using a semantic model developed for the Semantic Knowledge Management System (SKMS). Each description contains rich metadata, built on related concepts, methodologies, applied classifications, and code lists, ensuring semantic clarity and consistency.

LOSD are modelled and published alongside indicators, with direct links between each dataset and the corresponding concepts, variables, and classifications.

All descriptions are fully interlinked: glossary terms, methodological documents, SDMX-based code lists, and other reference materials are connected through hyperlinks. This approach aligns with FAIR principles, ensuring that statistical information is more findable, accessible, interoperable, and reusable, while also supporting its broader dissemination, comparability, and understanding by both humans and machines.

LOSD and semantically rich metadata are produced through a scalable pipeline, which automates the transformation of statistical metadata and reference information into a dynamic, machine-readable knowledge ecosystem. This ensures that indicators and datasets are always up-to-date, interconnected, and ready for integration into analytical tools and linked data workflows.