My habilitation provides a high-level overview of my contributions on inducing commonsense knowledge using vector space representations, with a focus on : (1)Learning conceptual space representations (learning entity embeddings and region-based representations of concepts, learning interpretable dimensions) (2) Modelling relational knowledge (relation induction in word embedding and pre-trained language models, learning of distributional relation vectors) (3) Deriving high quality vectors from contextualised LMs and applications to few-shot learning. (4 )Plausible reasoning about ontologies (automated rule base completion, inconsistency handling and belief merging)