Among the unique affordances of digital simulations are changes in the possibilities for targets as well as the methods of assessment, most significantly, toward integration of thinking with action, embedding of tasks-as-performance of knowledge-in-action, and unobtrusive observational methods. This paper raises and briefly defines key data challenges of assessing learning in a complex domain of performance within a digital simulation, which at the atomistic level include time and event segmentation, cyclic dynamics, multicausality, intersectionality, and nonlinearity. At the summary level, the key challenge is model building. An example of a simulation designed to develop teachers--simSchool--is integrated with an adaptive content delivery and analytics database--Leverage--which grounds the discussion. [For the full proceedings, see ED562107.]