Abstract
An ontology database system is a basic relational database management system that models an ontology plus its instances. To reason over the transitive closure of instances in the subsumption hierarchy, an ontology database can either unfold views at query time or propagate assertions using triggers at load time. In this paper, we present a method to embed ontology knowledge into a relational database through triggers. We demonstrate that by forward computing inferences, we improve query time. We find that: first, ontology database systems scale well for small and medium sized ontologies; and second, ontology database systems are able to answer ontology-based queries deductively; We apply this method to a Glass Identification Ontology, and discuss applications in Neuroscience.
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Tzacheva, A.A., Toland, T.S., Poole, P.H., Barnes, D.J. (2013). Ontology Database System and Triggers. In: Tucker, A., Höppner, F., Siebes, A., Swift, S. (eds) Advances in Intelligent Data Analysis XII. IDA 2013. Lecture Notes in Computer Science, vol 8207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41398-8_36
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DOI: https://doi.org/10.1007/978-3-642-41398-8_36
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