The number of applications being developed that require access to knowledge about the
real world has increased rapidly over the past two decades. Domain ontologies, which …

Ontology helps semantic systems to establish a model of the world in order to derive
machine processed knowledge. It represents formally the concepts, objects, properties and …

Multiple choice questions (MCQs) are considered highly useful (being easy to take or mark)
but quite difficult to create and large numbers are needed to form valid exams and …

Although an increasing number of RDF knowledge bases are published, many of those
consist primarily of instance data and lack sophisticated schemata. Having such schemata …

Tool development for and empirical experimentation in OWL ontology engineering require a
wide variety of suitable ontologies as input for testing and evaluation purposes and detailed …

Ontologies are formal knowledge models that describe concepts and relationships and
enable data integration, information search, and reasoning. Ontology Design Patterns …

Ontology reasoning is typically a computationally intensive operation. While soundness and
completeness of results is required in some use cases, for many others, a sensible trade-off …

Enabling data processing at the network edge, as close to the actual source of data as
possible, is a challenging, yet realistic goal to be achieved by the Internet of Things (IoT) …

Representing knowledge with ontologies and performing reasoning with semantic
reasoners is important in many intelligent applications. However, existing reasoners do not …

For expressive ontology languages such as OWL 2 DL, classification is a computationally
expensive task—2NEXPTIME-complete in the worst case. Hence, it is highly desirable to be …