 This prominent role of values in shaping data-related epistemic practices is not surprising given existing philosophical critiques of the fact/value distinction (e.g., Douglas 2009), and the existing literature on values in science—such as Helen Longino’s seminal distinction between constitutive and contextual values, as presented in her 1990 book Science as Social Knowledge—may well apply in this case too. Similarly, it is well-established that the technological and social conditions of research strongly condition its design and outcomes. What is particularly worrying in the case of big data is the temptation, prompted by hyped expectations around the power of data analytics, to hide or side-line the valuing choices that underpin the methods, infrastructures and algorithms used for big data extraction.