A common way to provide the logical underpinning of ontologies is to formalize the axioms with description logics, which can then be translated to any serialization of RDF, such as RDF/XML or Turtle. Beyond the description logic axioms, ontologies might also contain SWRL rules. The concept definitions can be mapped to any kind of resource or resource segment in RDF, such as images, videos, and regions of interest, to annotate objects, persons, etc., and interlink them with related resources across knowledge bases, ontologies, and LOD datasets. This information, based on human experience and knowledge, is valuable for reasoners for the automated interpretation of sophisticated and ambiguous contents, such as the visual content of multimedia resources. Application areas of ontology-based reasoning include, but are not limited to, information retrieval, automated scene interpretation, and knowledge discovery.
