Linkage scenarios of relational databases and ontologies: a systematic mapping




relational databases, ontologies, systematic mapping


Relational databases are one of the most used data sources. However, as a storage source, they present a group of shortcomings. It is complex to store semantic knowledge in relational databases. To solve the deficiencies in knowledge representation of relational databases, one trend has been to use ontologies. Ontologies possess a richer semantic and are closer to the end user vocabulary than relational database schemas. The objective of the present research was to carry out a systematic mapping about the scenarios where relational databases and ontologies are linked to provide a better integration, query, and visualization of stored data. The mapping was carried out by applying a methodological proposal established in the literature. As outcomes of the research, it was detected that the mapping of relational databases to ontologies and the ontologies usage for the integration of heterogeneous data sources were the most common scenarios. Likewise, trends and challenges were identified in each scenario, which might deserve further research efforts in the future.



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Abbes, H.; Gargouri, F. (2017). MongoDB-Based Modular Ontology Building for Big Data Integration. Journal on Data Semantics, 7: 1-27.

Ameen, A. et al. (2014). Reasoning in Semantic Web Using Jena. Computer Engineering and Intelligent Systems, 5(4): 39-48.

Bizer, C.; Seaborne, A. (2004). D2RQ-treating non-RDF databases as virtual RDF graphs. In Proceedings of the 3rd international semantic web conference (ISWC2004) (Vol. 2004). Springer.

Capsenta, J. F. S.; Miranker, D. P. (2017). A Pay-As-You-Go Methodology for Ontology-Based Data Access. IEEE Internet Computing, 21(2): 92-96.

Čerāns, K.; Būmans, G. (2015). RDB2OWL: a language and tool for database to ontology mapping. In Proceedings of the CAiSE 2015 Forum at the 27th International Conference on Advanced Information Systems Engineering (CAiSE 2015), Kista, Sweden (81-88).

Freitas, R., et al. (2017). Using linked data in the data integration for maternal and infant death risk of the SUS in the GISSA Project. In Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web (193-196).

Gorskis, H.; Aleksejeva, L.; Polaka, I. (2016). Database Analysis for Ontology Learning. Procedia Computer Science, 102: 113-120.

Haw, S. C.; May, J. W. (2017). Mapping Relational Databases to Ontology Representation: A Review. In Proceedings of the International Conference on Digital Technology in Education, 54-58.

Hazber, M. A., et al. (2019). A survey: Transformation for integrating relational database with semantic Web. In Proceedings of the 2019 3rd International Conference on Management Engineering, Software Engineering and Service Sciences (66-73).

Horridge, M.; Bechhofer, S. (2011). The OWL API: A Java API for OWL Ontologies. Semantic Web, 2(1): 11-21.

Karimi, H.; Kamandi, A. (2019). PT US CR. Expert Systems With Applications, 125: 412-424.

Liu, X.; Gao, F. (2018). An Approach for Learning Ontology from Relational Database. Proceedings of the 2018 International Conference on Algorithms, Computing and Artificial Intelligence.

López Rodríguez, Y. A.; Hidalgo Delgado, Y.; Silega Martínez, N. (2016). Método para la integración de ontologías en un sistema para la evaluación de créditos. Revista Cubana de Ciencias Informáticas, 10(4): 97-111.

Maran, V.; Medeiros, G.; Machado, A. (2017). Database Ontology-Supported Query for Ubiquitous Environments. In Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web, 185-188.

Miller, G. A. (1995). WordNet: A Lexical Database for English. Communications of the ACM, 38(11): 39-41.

Nakhla, Z.; Nouira, K. (2017). Automatic approach to enrich databases using ontology: Application in medical domain. Procedia Computer Science, 112: 387-396.

Petersen, K.; Vakkalanka, S.; Kuzniarz, L. (2015). Guidelines for conducting systematic mapping studies in software engineering : An update. Information and software technology, 64: 1-18.

Pop, C., et al. (2015). M2O: A Library for Using Ontologies in Software Engineering. Intelligent Computer Communication and Processing (ICCP): 69-75.

Reynoso, J. L., et al. (2015). Automatic Mapping Magnetic Resonance Images into Multimedia Database Using SIFT. IEEE Latin America Transactions, 13(8): 2709-2714.

Seo, D., et al. (2014). Development of Korean spine database and ontology for realizing e-Spine. Cluster computing. Recuperado de

Sequeda, J. F.; Miranker, D. P. (2013). Ultrawrap: SPARQL execution on relational data. Journal of Web Semantics, 22: 19-39.

Soylu, A., et al. (2016). Ontology-based end-user visual query formulation: Why, what, who, how, and which? Universal Access in the Information Society, 16: 435-467

Studer, R.; Benjamins, V. R.; Fensel, D. (1998). Knowledge Engineering : Principles and Methods. Data and Knowledge engineering, 25(1): 161-197.

Sujatha, B.; Raju, S. V. (2016). Ontology Based Natural Language Interface for Relational Databases. Procedia Computer Science, 92: 487-492.

Tao, M.; Ota, K.; Dong, M. (2016). Ontology-based Data Semantic Management and Application in IoT- and Cloud-Enabled Smart Homes. Future Generation Computer Systems, 76: 528-539

Thi, P., et al. (2014). RDB2RDF : Completed Transformation from Relational Database into RDF Ontology. In Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication, 88.

Tonella, P., et al. (2007). Empirical studies in reverse engineering : state of the art and future trends. Empirical Software Engineering, 12(5): 551-571.

Urrutia, A., et al. (2017). An Ontology to Assess Data Quality Domains. A Case Study Applied to a Health Care Entity. IEEE Latin America Transactions, 15(8): 1506-1512.

Zdravkovi, M., et al. (2013). Explication and semantic querying of enterprise information systems. Knowledge and information systems, 40(3): 697-724.



How to Cite

Lopez Rodriguez, Y. A., Hidalgo Delgado, Y., & Silega Martinez, N. (2021). Linkage scenarios of relational databases and ontologies: a systematic mapping. Enfoque UTE, 12(4), pp. 58 - 75.