Abstract
Many experimental ontologies have been developed for the learning domain for use at different institutions. These ontologies include different OWL/OWL 2 (Web Ontology Language) constructors. However, it is not clear which OWL 2 constructors are the most appropriate ones for designing ontologies for the learning domain. It is possible that the constructors used in these learning domain ontologies match one of the three standard OWL 2 profiles (sublanguages). To investigate whether this is the case, we have analysed a corpus of 14 ontologies designed for the learning domain. We have also compared the constructors used in these ontologies with those of the OWL 2 RL profile, one of the OWL 2 standard profiles. The results of our analysis suggest that the OWL 2 constructors used in these ontologies do not exactly match the standard OWL 2 RL profile, but form a subset of that profile which we call OWL 2 Learn.
Highlights
An ontology is a conceptual specification of a domain that represents concepts, relations and constraints of that domain
Based on the different types of web ontology language (OWL)/OWL 2 constructors used in each ontology of the corpus, we identified the description logic (DL) expressivity of these ontologies (Table 3)
We have found that transitive roles (R+) were included in four ontologies of the corpus (Table 3), which means that their expressivity corresponds to the DL language S (ALCR+) provided that complement is included
Summary
An ontology is a conceptual specification of a domain that represents concepts, relations and constraints of that domain. If it is the case that the learning ontologies in our corpus have different features, it would make sense to propose a new OWL 2 profile for the LD. One of the ontologies in our corpus, the university ontology (university.owl1), is based on a highly expressive DL language. OWL 2 standard profiles and learning ontologies In recent years, research on DL based ontology languages has paid an increasing attention to identifying sublanguages to specify different types of application domains that require restricted expressivity. As a starting point, it is worth analysing the OWL 2 constructors used in proposed learning ontologies and investigate the required expressivity of the DL language which can be used to model this domain.
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