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Conceptual modeling plays a fundamental role in information systems engineering, and in data and systems interoperability. To play their role as instruments for domain modeling, conceptual models must contain the exact set of constraints that represent the worldview of the relevant domain stakeholders. However, as empirical results show, conceptual modelers are subject to cognitive limitations and biases and, hence, in practice, they systematically produce models that fall short in that respect. Moreover, automating the process of formally assessing conceptual models in this sense (i.e., model validation) is notoriously hard, mainly because the intended worldview at hand lies in the mind of these stakeholders. In this paper, we provide a novel approach to model validation and automated constraint learning that combines, on one hand, Model Finding via the visual simulation of that model’s valid instances and, on …