The typical approach for declaratively reasoning about phenomena that evolves in time is to use a cognitive system centered on the given problem domain ontology as a vehicle for knowledge representation and processing. Current ontological-based approaches are successful only for the static structural description of a given domain of discourse. We present a modeling approach suitable for building and processing ontologies for applications where time-dependent evolution is of crucial importance. We also present the underlying concepts that form the basis of our modeling method and describe the temporal graph used for linking these concepts in order to encode the model evolution. That graph can be inspected in order to analyze the current and past events that a model generates, and their effects, and can be used for predicting the future model behavior. We present results on the capability of the modeling method to correctly describe temporal knowledge.