Accelerating the sustainable development transformation using Big Data and Artificial Intelligence

Gaps in data and limited understanding of how sustainability objectives interact make it difficult to assess progress and identify effective interventions. The project investigates how satellite observations, remote sensing, citizen science and other data sources can complement conventional statistics, particularly for environmental, climate and governance indicators.

Combining mathematical, statistical and network analysis with Artificial Intelligence, the research examines interlinkages between SDG indicators, including nonlinear relationships, synergies and trade-offs. It translates these findings into practical policy insights that reflect countries’ and regions’ different levels of development, supporting the sustainability transformation towards 2030 and beyond.

Project leader: Professor Ranjula Bali Swain
Funded by: Marianne and Marcus Wallenberg Foundation
Project period: 2025–2029