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1. When a data collection can or should be regarded as “bigdata”, and the significance of this particular label forresearch, is discussed at length in Leonelli (2016), Kitchin andMcArdle (2016) and Aronova, van Oertzen, and Sepkoski (2017).

2. This understanding of scientific knowledge is also embedded withinpublishing practices. As exemplified by the use of impact factors,scientific excellence is evaluated on the strength of authorship ofarticles, thus placing the production of scientific claims at thepinnacle of knowledge creation. Researchers whose activities focusaway from writing theoretical statements—such as data curatorsor software developers—are often viewed as technicians with alower status. The emergence of big data is challenging these habitsand perceptions, for instance through the rise of Open Sciencepractices, but it is no wonder that within this landscape,philosophers have focused their attention on models and theories ascentral outputs of research, leaving data behind.