Ontologies and similar artefacts are used in a myriad of ontology-driven information systems and increasingly also linked to data analytics. Algorithmic bias in data analytics is a well-known notion, but what does bias mean in the context of ontologies that provide a structuring mechanism for, e.g., an algorithm’s or query’s input? What are the sources of bias there, and cognitive bias in particular, and howdo they manifest in ontologies? We examined and enumerated eight broad sources that can cause bias that may affect an ontology’s content. They are illustrated with examples from extant ontologies and samples from the literature. We then assessed three concurrently developed COVID-19 ontologies on modelling bias and detected different subsets of types of bias in each one, to a greater or lesser extent.This first characterisation aims contribute to a sensitisation of bias in ontologies primarily regarding representation of the knowledge
