Philosophers of science need to be familiar with the object of their study. Part of this familiarity can come from their own scientific training, interviews, and interactions with working scientists, or case studies of historical developments. However, the picture emerging from these localized methods is likely to be incomplete: Modern science is fast, vast, and difficult to grasp in its interdisciplinary entirety. Data-driven methods have emerged in philosophy of science as one way to address this problem. In this paper, I introduce the audience to a new interactive tool that I have built to link philosophical investigations to large corpora of scientific material: OpenAlex Mapper (https://tinyurl.com/OAmapper).

OpenAlex Mapper allows users to project arbitrary search queries to the OpenAlex database (the largest open database of scientific material available) onto an interactively explorable, machine-learning-generated base-map of the sciences. This enables philosophers to quickly check whether hypothesized patterns in the structure, development, and interrelation of scientific fields hold up at scale. As a serendipitous search tool, it also opens the door to exploration of unexpected details and connections.