Data are a valuable asset for companies in the logistics sector to optimize internally and develop new business models. They can be like a magnifying glass, making previously opaque logistical processes transparent and finding previously hidden optimization potentials. Typical applications are tracking the transport status, route optimization, monitoring pharmaceutical products, or monitoring shocks for fragile cargo along the trade lanes. One way to use data is to tap into publicly or commercially available Application Programming Interfaces (APIs). As a result, logistics service providers can get or provide data automatically via a machine-tomachine interface. However, the landscape of API service providers is vast, unstructured, and intransparent in terms of potential data that companies can leverage. Given their high potential for logistics, the paper proposes a taxonomy of API services in logistics based on the inductive analysis of three API databases.