Computational modeling through high-performance computing (HPC) is a unique instrument for understanding complex systems such as the brain or the global climate. For example, the conclusions of the Intergovernmental Panel on Climate Change rest on many interrelated physical models, bound together through HPC. However, the challenge is to extend this paradigm to help us understand human life and the underlying causes of societal behaviors. Addressing changes in food production, the spread of infectious disease, crisis management, and the effects on world economics require decision tools based on a greater range of discipline models. Whole-Earth simulations, which bind environmental and ecological models to social and economic systems, could form the basis for a new generation of advanced decision-making tools. But current models are not sufficient as decision tools. They must encompass social as well as physical disciplines, and they must integrate constant feedback from real-world data. An increasingly vast range of data is being used for model insights, ranging from physical sensors and publicly available Internet data to crowd-sourcing. This panel will explore the interplay between the modern deluge of data, modeling and simulation from HPC, and the construction of information-based decision tools for policy-makers in the context of crisis modeling, infectious disease, and multidisciplinary, whole-Earth simulations.