Managing Contextualized Knowledge with the CKR

As large amounts of Linked Data are published on the Web, it is becoming apparent that the validity of published knowledge is not absolute, but often depends on time, location, topic, and other contextual attributes. Therefore, an increasingly perceived need for Semantic Web (SW) applications is the representation of the context of such knowledge and its formalization for using it in reasoning and querying. Recognizing this problem, several extensions of RDF and OWL to support contextual qualification of knowledge have been proposed [1, 3, 5, 7]. Among these, we recently presented the Contextualized Knowledge Repository (CKR) [6], a framework with a well-founded semantics based on established AI principia [2, 4] for contextual representation and reasoning. A distinguishing feature of the CKR is that contextual organization and knowledge propagation among contexts are largely derived from the qualification of knowledge along contextual dimensions: thus, users are not asked to manually express complex bridging axioms to define context relations. While our previous work has mainly focused on the formal definitions and implementation of the CKR framework, the proposed poster illustrates the practical applicability of CKR features in real-world SW applications. The poster presents a concrete example of CKR use under the point of view of the tasks of modelling, reasoning over and querying contextualized knowledge.