Ontology Driven for Mapping a Relational Database to a Knowledge-based System

The mapping of a relational database system to a knowledge-based system is a key stage in developing an online analytical processing (OLAP) system. OLAP is a cornerstone in discovering hidden knowledge in any business. Hence, the existence of an OLAP system is one of the modern success factors in a business environment. Mapping has proven benefits for knowledge-based systems in terms of enabling the discovery of hidden relationships among objects and the inference of new information. However, there remains room for improvement in respect of the quality of the mapping output. Therefore, in this paper, a rule-based method for mapping a relational database to a knowledge-based system is introduced. First, the proposed mapping process, which involves converting the tables and relationships of a relational database into facts and rules for a knowledge-based system, is illustrated through the use of a detailed case study. Then the correctness of the proposed method is proved by testing the tautology results against equivalent SQL queries. In addition, the completeness of the proposed method is proved by demonstrating that the used predicates are sufficient to allow a complete modeling of the required system. Furthermore, the experimental results show that the performance of the knowledge-based system that was developed using the proposed method is much better than that of an equivalent relational database.

@article{Elfaki2024,
  title     = {Ontology Driven for Mapping a Relational Database to a Knowledge-based System},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {5},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Abdelrahman Osman Elfaki and Yousef H. Alfaifi},
  doi       = {10.14569/IJACSA.2024.0150562},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150562}
}