The knowledge used in most AI applications does not rely on a formal model of the domain. Therefore, it has to be normalized to ensure that the formal exploitation of its representation conforms to its meaning in the domain. Considering the intensional (non extensional) nature of concepts, which reflects the essences of the objects they denote, this normalization relies on a commitment on type definitions by necessary and sufficient conditions at the knowledge level. Our claim is that the taxonomic structure that accounts for the intensional nature of the ontology can be nothing but a tree. From this starting point, we derive methodological principles to constrain and justify the structuring of ontological types. Based on this methodology, we advocate understandability of an ontology rather than a putative reusability. 1 Introduction The ontology is the heart of any knowledge description: knowledge is intimately related to the ontology, since it is necessarily expre...