Abstract
The use of computational simulation in science is now pervasive. However, while model development environments have advanced to a degree that allows scientists to build sophisticated models, there are still impediments that limit their utility within the broader context of the scientific method. Despite availability of effective tools that assist scientists in routine aspects of scientific workflow management and analytics, other steps, including explanation, evidential reasoning, and decision-making, continue to limit the process of causal reasoning in knowledge discovery and evaluation. This chapter examines the types, functions, and purposes of models in relation to the scientific method, identifies the issues and challenges pertaining to information abstraction and cognitive support for computational discovery , and delineates a model-driven cognitive systems approach for simulation-based science .
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Yilmaz, L. (2017). Simulation-Based Science. In: Mittal, S., Durak, U., Ören, T. (eds) Guide to Simulation-Based Disciplines. Simulation Foundations, Methods and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-61264-5_9
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