Workshop on Supporting Standards 2026

The presentation “Boosting data accessibility with SDMX & AI” will present the new experimental AI-based approach for discovering OECD data powered by the .Stat Suite SDMX API and by the Inlook.ai technology. After reminding the audience about how SDMX can facilitate the classical web dissemination of statistical data, e.g., with the .Stat Suite Data Explorer, as well as the global discovery...

Theme:
Generative AI (GenAI) and Machine Learning (ML) in statistical production.

Abstract:
This study outlines a practical initiative by the Department of Statistics, Malaysia (DOSM) with the purpose of developing a responsible, low-risk pathway for exploring Artificial Intelligence in official statistics. Our goal was to understand how AI, when firmly guided by established...

Statistics Estonia receives data from more than 100 administrative data sources, which may come with minimal metadata. While a new metadata information system (Colectica) is being implemented, our data warehouse remains the same (Oracle DB with a schema for each statistical activity/administrative data source). Schema types for administrative data sources and statistical activities are...

This talk will introduce the Semantic Croissant ecosystem created around Croissant for Machine Learning standard, with a focus on ontology alignment with ML and the linkage of metadata to external controlled vocabularies through the Cross-Domain Interoperability Framework (CDIF). It will also highlight how these components support semantic consistency and interoperability across research...

Istat’s statistical modernisation programme relies on the consistent use of international standards and architectural models to manage the growing complexity arising from multi-source data integration and the adoption of Machine Learning (ML) and Generative AI (GenAI) in statistical production. Rather than viewing AI as a standalone innovation, Istat has adopted a standards-first approach,...