Teaching Data Co-Production and AI at the SPACERAISE International Summer School

June 15, 2026

In May 2026, CIESIN’s Associate Director of Science Applications Dana R. Thomson participated as an invited lecturer in the SPACERAISE International Summer School , a three-week interdisciplinary training program hosted by the Gran Sasso Science Institute (GSSI) in L’Aquila, Italy. SPACERAISE brings together master's students, doctoral researchers, early-career scientists, and professionals from around the world to explore emerging applications of robotics, artificial intelligence, and geospatial data for space, environmental, and societal challenges. The 2026 program attracted students from nearly 40 countries across Africa, Asia, Europe, North and South America, and Oceania, creating a uniquely international environment for learning and collaboration.

Dr. Thomson taught during the third week of the program, which focused on Geospatial Data and Quantitative Analysis in Social Science. The week featured leading researchers from universities, international organizations, and government agencies working at the intersection of Earth observation, spatial analytics, economics, urban studies, disaster response, and public policy. Lectures explored how satellite imagery, geospatial data, and quantitative methods can be used to better understand cities, environmental change, migration, conflict, vulnerability, and resilience.

Her lecture, titled Data Co-Production at Scale in the Era of AI, examined how artificial intelligence and geospatial technologies are transforming the production and use of social and environmental data. Drawing on work from the IDEAMAPS Network and the POPGRID Data Collaborative, she discussed emerging approaches to combining Earth observation, machine learning, official statistics, and community-generated data to support more equitable and effective decision-making. The lecture explored the opportunities and challenges of scaling data co-production, highlighting the importance of governance, participation, and data justice as AI-enabled data systems become increasingly central to climate adaptation, urban planning, disaster preparedness, and public service delivery.