TRUE

TRUE establishes a scientific foundation for interpretable and trustworthy situational understanding over multivariate time series by integrating spatio-temporal learning, argumentation-based causal inference, and uncertainty-aware risk assessment.

The goal is to understand not only what is happening in a complex system, but also which causes are most plausible, how reliable each inference is, and how to support cautious decisions when data is only partially representative.