When is big data too big? Making data-based models comprehensible

Data-driven mathematical modeling is having an enormous impact on the ability to organize and describe very large data sets, and make inferences and predictions about populations and situations based on sampling data. However, as these models become increasingly complex, the ability of users to understand and apply them represents a growing challenge. The article "A Framework for Considering Comprehensibility in Modeling", which describes this emerging dilemma and a strategy for developing solutions, is published in Big Data.

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