We seek to develop intelligent cloud services to support more productive use of simulations for complex computational experimentation.

The integration between on the one hand data, modeling and algorithms, and on the other hand the specification, coordination and execution of large scale and data-intensive computational experiments poses a fundamental problem in all scientific disciplines relying on modeling and simulation. While high quality data, well-parametrized models and efficient and accurate simulation algorithms are the fundamentals of successful computational experimentation they are in themselves not nearly sufficient for productive, collaborative and reproducible computationally-driven scientific discovery: software to orchestrate the experiments is needed.  Today it is largely left to the modeler or engineer to manually tune models to fit data, to choose algorithms, to configure simulation workflows and to analyze simulation result. This is a big burden to place on e.g. a biologist who is mainly interested in how she can use modeling and simulation to learn new things about a biological system of interest.

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