This paper tackles the problem of computing views of OWL ontologies using a forgetting-based approach. In traditional relational databases, a view is a subset of a database, whereas in ontologies, a view is more than a subset; it contains not only axioms contained in the original ontology, but may also contain newly-derived axioms entailed by the original ontology (implicitly contained in the original ontology). Specifically, given an ontology , the signature of is the set of all the names in , and a view of is a new ontology obtained from using only part of ’s signature, namely the target signature, while preserving all logical entailments up to the target signature. Computing views of OWL ontologies is useful for Semantic Web applications such as ontology-based query answering, in a way that the view can be used as a substitute of the original ontology to answer queries formulated with the target signature, and information hiding, in the sense that it restricts users from viewing certain information of an ontology.

This paper describes a Java-based forgetting system UI-FAME for creating views of ontologies. In relational databases, a view is a subset of the database, while in ontologies, a view is more than a subset; it contains not only axioms that are contained in the original ontology, but also newly-derived axioms that are entailed by the original ontology. Forgetting is a form of non-standard reasoning that can be used to create views of ontologies by eliminating from the ontologies a set of concept and role names, namely the forgetting signature, while keeping all logical consequences over the names in the remaining signature. We compared UI-FAME with publicly accessible forgetting systems, namely LETHE and an early prototypical version of UI-FAME, over the 'AL'-TBox fragment of 494 ontologies taken from the Oxford Ontology Library. The results showed that UI-FAME had better success rates than LETHE and its prototypical version, and outsped LETHE by a large margin. UI-FAME has been integrated as back-end support in Babylon Health's (a leading digital healthcare company based in London) knowledge base (formed by the merger and alignment of medical ontologies from different sources) interfaces for their main concerns of ontology analysis and keeping track of the changes in different versions of its knowledge base.