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Multimedia reasoning, which is suitable for, among others, multimedia contentanalysis and high-level video scene interpretation, relies on the formal andcomprehensive conceptualization of the represented knowledge domain. However,most multimedia ontologies are not exhaustive in terms of role definitions, anddo not incorporate complex role inclusions and role interdependencies. In fact,most multimedia ontologies do not have a role box at all, and implement only abasic subset of the available logical constructors. Consequently, theirapplication in multimedia reasoning is limited. To address the above issues,VidOnt, the very first multimedia ontology with SROIQ(D) expressivity and aDL-safe ruleset has been introduced for next-generation multimedia reasoning.In contrast to the common practice, the formal grounding has been set in one ofthe most expressive description logics, and the ontology validated withindustry-leading reasoners, namely HermiT and FaCT++. This paper also presentsbest practices for developing multimedia ontologies, based on my ontologyengineering approach.

A Novel Approach to Multimedia Ontology Engineering for Automated Reasoning over Audiovisual LOD Datasets