Proposal Description

The increasing complexity and dynamics of social and economic processes, combined with the growing demand for timely, granular and policy-relevant information, pose significant challenges for regional and urban statistics. Evidence-based decision-making at both national and sub-national levels requires statistical systems to go beyond traditional data sources and methods and to explore innovative approaches to data integration and analysis.

The 2030 Agenda for Sustainable Development, adopted by UN Member States, highlights the need for more detailed, disaggregated and up-to-date data to monitor progress towards sustainable development goals, particularly in urban and regional contexts. In response, National Statistical Institutes are increasingly experimenting with new data sources—such as administrative data, geospatial information, satellite imagery, mobile phone data and other big data sources—as well as advanced statistical and analytical methods.

This session aims to explore how new data sources and methods can be applied in practice to improve the production of regional and urban statistics. It will focus on opportunities and challenges related to data access, data quality, methodological soundness, interoperability and governance. Particular attention will be given to how innovative approaches can enhance spatial granularity, timeliness and relevance of official statistics while maintaining trust, transparency and statistical standards.