Big data bring great opportunities for both understanding the complex world we live in and making our lives better—but they are also ripe for misuse. In many areas of increasingly powerful technologies allow researchers to generate a whole lot of data, which are then disseminated via digital databases. Having heaps of data available online sounds great, but it raises real problems. How are we to explore and make sense of this enormous quantity of data? Philosophers have had a lot to say about how we can make robust inferences by triangulating between multiple lines of evidence, and how we handle data in order to yield meaningful and reliable knowledge. Leonelli draws on this literature to examine the conditions under which big data should be aggregated and interpreted. She then discusses the ways in which big data misuse could significantly damage the credibility and trustworthiness of scientific research as a whole. About the speaker Sabina Leonelli is a professor in philosophy and history of science at the University of Exeter, UK, where she the Exeter Centre for the Study of the Life Sciences and leads the “Data Studies” research strand. She has widely published in the philosophy of science as well as biology and STS, and her monograph Data-Centric Biology in 2016 with Chicago University Press.