Crafting OWL Ontologies from MongoDB: A Formal Concept Analysis (FCA) Approach

Utilizing ontologies enables the sharing and reuse of knowledge within specific domains. However, developing an ontology from scratch is a time-consuming and error-prone task. This necessitates an approach that simplifies the intricate process by utilizing existing resources. In this study, we introduce an improved method for learning OWL ontology from a NoSQL database, specifically MongoDB. Our approach, grounded in Formal Concept Analysis and a set of mapping rules, automates the generation of a comprehensive ontology from complex NoSQL databases. The process involves three key phases: (1) constructing a Formal Context from MongoDB, (2) employing formal concept analysis to derive a concept lattice from the created context, and (3) transforming the concept lattice into an initial ontology representation. We have validated the efficacy of our proposed learning rules through practical application.