aModeling and simulation can best be understood as part of a “meta-modeling” process that involves data acquisition and curation, statistical inference, software development, representation of human behavior, consideration of pragmatics such as logistics, cost-benefit analyses, visualization, and communication of model results. In this process, data are transformed into wisdom (or something like it). Mechanistic insights and appreciations of the value of information continually generate feedback learning loops.