Expertise is an activity carried out by experts that contributes to societal progress, as it helps to elucidate unknown situations. For example, accident expertise eases accident understanding, by describing how it happened, and by identifying its causes and consequences. As a result, the design of accident expertise in a convenient human-machine structure will enable the querying, reasoning, and reuse of accident knowledge in other tools, such as safety and decision-making systems. However, existing representations of accident knowledge, such as documents, relational databases, or accident ontologies, do not fulfill accident expertise expectations. Moreover, these representations are unlikely to provide the appropriate use of accident expertise knowledge. This study presents a base ontology for accident expertise knowledge representation designed with a model-driven methodology and implemented with semantic web technologies. The study obtained satisfactory results from the evaluation and application of extension and reuse of this ontology with aircraft accident expertise taken from the French bureau of Enquiries and Analysis (BEA) for civil aviation safety.