Towards Self-explanatory Ontology Visualization with Contextual Verbalization

• Published in: arXiv.org
• Main Authors: Liepiņš, Renārs, Bojārs, Uldis, Grūzītis, Normunds, Čerāns, Kārlis, Celms, Edgars
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 06.07.2016
• Subjects: Axioms; Computer Science - Artificial Intelligence; Computer Science - Computation and Language; Knowledge representation; Natural language; Ontology; Programming languages; Semantic web; Semantics; Subject specialists
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.1607.01490

Ontologies are one of the core foundations of the Semantic Web. To participate in Semantic Web projects, domain experts need to be able to understand the ontologies involved. Visual notations can provide an overview of the ontology and help users to understand the connections among entities. However, the users first need to learn the visual notation before they can interpret it correctly. Controlled natural language representation would be readable right away and might be preferred in case of complex axioms, however, the structure of the ontology would remain less apparent. We propose to combine ontology visualizations with contextual ontology verbalizations of selected ontology (diagram) elements, displaying controlled natural language (CNL) explanations of OWL axioms corresponding to the selected visual notation elements. Thus, the domain experts will benefit from both the high-level overview provided by the graphical notation and the detailed textual explanations of particular elements in the diagram.