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.
Knowledge is essential for organizations’ growth as it allows them to solve problems, make decisions, innovate, and stay competitive. Within organizations, there is, on the one hand, explicit knowledge that is easy to capture, represent, and share. On the other hand, there is tacit knowledge possessed and acquired by individuals during their activities. Unlike explicit knowledge, tacit knowledge is difficult to capture and formalize. Organizations have granted more interest and efforts in representing, sharing, and reasoning from explicit knowledge. However, for tacit personal knowledge, they rely on methods such as meetings, mentoring, questions answering, or interviews which are limited in capitalizing on personal knowledge. This study elaborates on the construction of interpersonal activity graphs for representing, sharing, and reasoning on organizations’ tacit knowledge possessed by individuals. The established graph is based on an extended activity theory framework and an ontology for common semantics. The proposed representation captures tacit knowledge in a graph form, making it shareable while offering means to reason and query it.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.