The inference layer supports rule-based reasoning, i.e. given a set of rules it computes all possible inferences on the given dataset. Technically, forward-chaining  is applied, i.e. it starts with the available data and uses inference rules to extract more data. This is sometimes also referred to as “materialization”.
Currently, three fixed rulesets are supported, namely RDFS, OWL-Horst, and OWL-EL. Later versions will contain a generic rule-based reasoner such that a user can define it’s own set of rules which will be used to materialize the given dataset.