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

Leslie Sikos

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    10 Citations (Scopus)


    Multimedia reasoning, which is suitable for, among others, multimedia content analysis and high-level video scene interpretation, relies on the formal and comprehensive conceptualization of the represented knowledge domain. However, most multimedia ontologies are not exhaustive in terms of role definitions, and do not incorporate complex role inclusions and role interdependencies. In fact, most multimedia ontologies do not have a role box at all, and implement only a basic subset of the available logical constructors. Consequently, their application in multimedia reasoning is limited. To address the above issues, VidOnt, the very first multimedia ontology with SROIQD expressivity and a DL-safe ruleset has been introduced for next-generation multimedia reasoning. In contrast to the common practice, the formal grounding has been set in one of the most expressive description logics, and the ontology validated with industry-leading reasoners, namely HermiT and FaCT++. This paper also presents best practices for developing multimedia ontologies, based on my ontology engineering approach.

    Original languageEnglish
    Title of host publicationIntelligent Information and Database Systems - 8th Asian Conference, ACIIDS 2016, Proceedings
    EditorsNgoc Thanh Nguyen, Bogdan Trawinski, Tzung-Pei Hong, Hamido Fujita
    PublisherSpringer Nature
    Number of pages10
    ISBN (Print)9783662493809
    Publication statusPublished - 2016

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    • Knowledge representation
    • Linked Open Data
    • MPEG-7
    • Ontology
    • OWL
    • Video metadata
    • Video retrieval


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