The metrological culture in the context of big data: managing data-driven decision confidence

Abstract

In recent years, data sets are steadily growing in size because of the huge sensing, storage, computation, and transmission capabilities offered at very low cost by current Information Technology systems, which are increasingly driving ubiquitous data acquisition from the empirical world. Moreover, massive amounts of data can be collected very efficiently- sometimes at zero marginal costs—from the internet. The concept of Big Data (BD) epitomizes this phenomenon among the experts and the general public (for an accessible, application-oriented introduction to BD in the broad context of data science, see, e.g., [1]).