Numerical Designs of Experiments (DoE) are used in a product development process for several purposes as optimization, surrogate modelling
or sensitivity analysis. Methods used to shorten the execution of DoE demands advanced knowledge and expertise to be selected and
configured. A knowledge management approach can be applied to capitalize and reuse knowledge. There is a real lack in term of models for
this specific application. Thus, an ontology for the numerical DoE process is proposed. It is linked to existing ontologies and data models
developed for numerical simulations. This ontology will be used as a support for a decision-aid system.