Arctic ice, george clooney, lipstick on a pig, and insomniac fruit flies
R. Colbaugh · 2011
Both knowledge discovery (KD) and modeling and simulation (M&S) have made profound contributions to human understanding, and given their complementary perspectives and shared emphasis on "real-world" phenomena it is natural to suspect that they may be even more powerful when applied in combination. However, the KD and M&S communities have operated and evolved essentially independently, so that this possibility remains largely unexplored. This talk will illustrate, through a series of case studies taken from the predictive analysis domain, some of the substantial benefits of combining these two approaches. I will begin by briefly reviewing two climate dynamics studies which serve as exemplars of two "standard" ways KD and M&S can work together: 1.) KD can uncover regularities and patterns in data which can be incorporated into computational models, 2.) the outputs of (large) M&S runs can be analyzed using KD techniques, enabling rigorous assessments as well as new and unexpected insights.