The digital transformation era is the source of inspiration for most institutions and companies to rethink how to align their document circulation mechanism with their business objectives. Therefore, document management has become one of the most important areas in which technology works to change the mechanisms of document circulation quickly and accurately by giving institutions the ability to automate their document management processes and reduce costs. The main goal of this paper is to propose a new methodology for an ontology-based archiving system. The proposed methodology can be used to design artificial intelligence systems that can analyze and understand document content using natural language processing. In the proposed methodology, an ontology mapping engine is used as pivotal in converting raw data into a semantically rich format. By mapping raw data elements to pre-defined ontological entities, it enriches the data set with context and meaning, making it suitable for advanced processing and inference at later stages of the system. The overall architecture and its components are presented and discussed, followed by an illustrative example demonstrating the accuracy and integrity of the proposal.
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