Semantic data access for relational databases using an ontology

Abstract

Data analysis-based decision-making is performed daily by domain experts. As data grows in size and heterogeneity, accessing relevant data becomes challenging. In an Ontology-based data access (OBDA) approach, ontologies are advocated as a suitable formal tool to address complex data access. This technique falls within the Semantic Web domain, combining a domain ontology with a data source by using a declarative mapping specification to enable data access using a domain vocabulary. In this research, we investigate this approach by: a) studying the theoretical background that enables this technique; b) conducting a literature review on the existing open source tools that implement OBDA; c) implementing OBDA on a “real-world” relational dataset using an OBDA tool; and d) providing results and analysis of query answering. We selected Ontop (https://ontop-vkg.org) among various OBDA tools to illustrate how this technique enhances the data usage of the GitHub community. Ontop is an open-source tool applying OBDA in the domain of relational databases. We used the GHTorrent dataset, a relational database, in combination with the SemanGit ontology for our implementation.