Collaborative Modeling, Simulation, and Analytics with Splash

In the past few years, research around (big) data management has begun to intertwine with research around predictive modeling and simulation in novel and interesting ways. Driving this trend is an increasing recognition that information contained in real-world data must be combined with information from domain experts, as embodied in simulation models, in order to enable robust decision making under uncertainty. This convergence of data management and simulation is exemplified by the IBM Splash prototype framework for combining existing heterogeneous simulation models and datasets to create composite simulation models of complex systems. Such composite modeling across a broad range of disciplines, though highly challenging, is needed to support sound and robust decision making around complex issues such as population health and safety. Splash combines and extends technologies for simulation, information integration, and massive scale analytics. We give an overview of the Splash system, highlight some interesting technologies that we have developed in the course of the project, and point to some of the open questions in the new and evolving research area of collaborative modeling, simulation, and analytics.

Speaker: Peter J. Haas, IBM Aladen Research Center

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