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...
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...
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...