Generating Ontologies from Templates: A Rule-Based Approach for Capturing Regularity
This work addresses the challenge of consistent and transparent ontology generation for knowledge representation, but it appears incremental as it builds on existing template frameworks.
The authors tackled the problem of succinctly specifying ontologies by introducing a second-order language based on ontology templates (OTTR) to capture recurring patterns, and they showed results on the decidability of reasoning tasks for this language.
We present a second-order language that can be used to succinctly specify ontologies in a consistent and transparent manner. This language is based on ontology templates (OTTR), a framework for capturing recurring patterns of axioms in ontological modelling. The language and our results are independent of any specific DL. We define the language and its semantics, including the case of negation-as-failure, investigate reasoning over ontologies specified using our language, and show results about the decidability of useful reasoning tasks about the language itself. We also state and discuss some open problems that we believe to be of interest.