Innovative methods of nowcasting using artificial intelligence, UN World Data Forum 2023

At the mid-point of the time foreseen for enacting the 2030 Agenda for Sustainable Development, there is an urgent need for more timely information for measuring the progress achieved so far and identifying the main bottlenecks and areas lagging behind. The COVID-19 crisis put in clear evidence the importance of timely and granular information for monitoring trends and for guiding the policy responses. However, many SDG indicators rely on official data that still suffer from long publication delays or that is only available incompletely or with insufficient coverage. In recent years, statistical methodologies, space technologies, and online data tools, including those based on machine learning methods, satellite remote sensing images, cloud-end big data platforms, and new data sources have been applied to comprehensively address those information gaps.

UNCTAD co-organizes an event on ways for increasing timeliness and coverage of SDG indicators at the 4th UN World Data Forum (24-27 April, Hangzhou, China). The forum will bring together 1 500 in-person and nearly 20 000 virtual participants from national statistical offices, international organizations, the geospatial community, academic organizations, the private sector, and civil society organizations to showcase innovations and build impactful partnerships. The Forum is organized under the guidance of the UN Statistical Commission and the High-level Group for Partnership, Coordination, and Capacity-Building for Statistics for the 2030 Agenda for Sustainable Development, in close consultation with UN Member States and international partners.

This session will highlight some recent examples of the works utilizing statistical methods and earth observation data in relation to specific SDG indicators. Rather than focusing on technical or computational details, the panelists will highlight the main challenges faced when applying their methods/utilities, as well as solutions and lessons learned that could help other actors to continue improving timeliness of SDG indicators at the national and international levels.

Daniel Hopp, Statistician at UNCTAD, will present innovative methods of nowcasting using artificial intelligence. Daniel Hopp has a strong experience in data ecosystems, machine learning, and programming to drive innovation in the domains of trade statistics, economic forecasting, and official statistics.

Seakers:

• Qunli Han, Executive Director, Integrated Research on Disaster Risk (IRDR) International Programme Office
• Huadong Guo, Academician & Director General, International Research Center of Big Data for Sustainable Development Goals
• Yana Gevorgyan, Secretariat Director, Group on Earth Observations (GEO)
• Jianhui LI, Professor, Vice-President, CODATA of the International Science Council
• Gretchen Kalonji, School of Disaster Reconstruction and Management, Sichuan University - The Hong Kong Polytechnic University
• Daniel Hopp, Statistician, United Nations Conference on Trade and Development (UNCTAD)
• Charles Brigham, Geographer, Esri · Stephen Keppel, President, PVBLIC Foundation