Workshop on Supporting Standards 2026

Building on core pillars such as centralised data repositories, integrated data-acquisition and statistical compilation processes, and robust governance of reference data and metadata catalogues, Banco de Portugal has been advancing the standardisation and interoperability of its statistical systems.

This work gives particular emphasis on the harmonisation of statistical concepts as a key...

A modernised statistical production will in nature be multi sourced. Administrative registers and other digital data sources will be combined with traditional or complementary sample surveys to create qualitative statistical output while minimising response burden. Furthermore, many new data sources will be useful for several statistical outputs. This situation calls for an architecture that...

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...

The progressing data landscape and the evolving requirements of the modern information ecosystems demand that National Statistical Organizations (NSOs) transition from rigid ""stove-pipe"" systems toward standardized, flexible and modular architectures. This business transformation is increasingly powered by Free and Open Source Software (FOSS), which provides the technical and cultural...

Building Semantic SDMX for AI-ready Statistics and Interoperability: Challenges, Achievements, Prospects

A major challenge for achieving interoperability lies in the insufficient development of standards for the exchange of Linked Open Statistical Data (LOSD). Current data exchange standards — including SDMX, SIMS, DDI and others — have been developed within an object-oriented paradigm,...

The Decision-Making Support System at Local and National Levels (DMSS LL/NL) is a practical use case demonstrating how multi-source statistics can be effectively leveraged to support evidence-based policymaking and governance across different territorial levels. Developed within the framework of the Statistical Office of the Republic of Serbia (SORS), DMSS combines data from various providers...

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...

Across the statistical community, there is growing recognition that high-quality outputs depend on high-quality processes. The Office for National Statistics – the UK’s largest independent producer of official statistics – is currently undertaking an ambitious project to strengthen quality by systematically mapping, visualising, and continuously improving the production ecosystem. The aim is...

We will present preliminary outcomes of an ongoing project at Statistics Netherlands (CBS), to be carried out between February and June 2026. It is an extension of prior efforts and builds upon an existing first proof of concept. The project explores the potential of Large Language Model (LLM)-based Retrieval-Augmented Generation (RAG) to support researchers in efficiently identifying relevant...

National Statistical Offices (NSOs) globally are under pressure to deliver more comprehensive and timely statistics, whilst operating in an increasingly complex survey environment. Declining response rates, rising costs, increasing respondent burden and expanding operational workloads are forcing NSOs to re-evaluate traditional approaches and to pursue innovative alternatives.

In response...

Bank Indonesia’s digital transformation increasingly depends on integrated, secure, and policy-responsive data and information management. In this setting, internal data access governance is a pivotal control to ensure effective data use by Bank Indonesia staff while safeguarding confidentiality, ensuring accountability, and protecting public trust. Yet digitalisation initiatives often...

Insee has been implementing for many years an ecosystem of repositories dealing with standardised metadata for statistical purposes. The finest level is currently the instance variable and its representation (numeric, text, code list, etc.).These objects serve multiple purpose and are consumed by several internal and external stakeholders:
- An internal platform to centralise ready-for-use...

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...

Disruptive change—particularly the rapid adoption of generative AI, machine learning, and multi-source statistics—demands standards and architectures that make official statistics interoperable, transparent, and repeatable. A common barrier is inconsistent use of official geographic identifiers across disseminated datasets and metadata, which increases manual reconciliation, introduces linkage...

Users increasingly expect to talk to statistics in plain language, while official statistics must remain authoritative, confidentiality preserving, and fully verifiable. The Statistical Office of the Republic of Serbia (SORS) is developing an AI dissemination chatbot for its official channels under a trust first design: public and SDC protected content only, transparent referencing and...

The Pacific Community’s Statistics for Development Division (SDD) is implementing a division‑wide business process optimisation programme to modernise statistical production through standards‑aligned process re‑engineering. Core activities, such as mapping the organisational structure to the GSBPM, defining governed data steady states, and redesigning end‑to‑end workflows using BPMN, provide a...

In the context of the ESS Innovation Agenda, quality assurance must evolve to meet the challenges posed by new technologies and data sources. This contribution reflects on three challenges shaping that evolution: the integration of Artificial Intelligence (AI) and Machine Learning in statistical processes, the operationalisation of Statistics under Development (SuD), and the growing reliance...

Official statistics is rapidly adopting cloud based and open-source self-service production platforms, modern programming languages, and more machine learning in production. In parallel, generative AI is becoming a natural part of development and maintenance work. These shifts are often aimed at improving speed, reproducibility, and reuse, but also increase the need for systematic operational...

Some work is being undertaken on a new "Statistical Architecture Framework" under UNECE's Supporting Standards Group. This presentation will give an update on work to date.

The IMF is modernizing how statistical data and metadata are produced and managed to support both AI-enabled access and enterprise data governance. This work is built around two closely related use cases. First, a standardized metadata model mapped to Dublin Core, DCAT, and SDMX Global Data Structure Definitions (DSDs) is used to generate consistent semantic descriptions for the IMF’s SDMX...