Preprint Open Access
Chades, Iadine; Nicol, Sam
Big data problems have attracted an increasingly large proportion of private and public sector funding, influencing research efforts worldwide (1-4). We welcome the exciting opportunities to gain new insights from big data. However, the research community, funding agencies and the private sector must think critically about how this rapid shift will affect our ability to solve pressing problems for which we do not have ways of obtaining big data, yet urgently require decisions to be made in a fast-changing world. In 2015, the US National Science Foundation awarded funding to five times more big data projects than in 2012; an increase in funding of $100 million in just three years(1). In 2014, Wlodarczyk and Hacker (5) reported a ten-fold increase in big data publications over the last three years. Here, we discuss two situations where big data fails to address major problems facing society: where resources are limited but decisions must be made, and where big data collection is not possible. In both cases, we argue that solutions should come from intelligent use of small data, driven by decision science approaches.