Contextualization of a RDF Knowledge Base in the VIKEF Project

Abstract

Due to the simplicity of RDF data model and semantics, complex application scenarios in which RDF is used to represent the application data model raise important design issues. Modelling e.g. the temporary evolution, relevance, trust and provenance in Knowledge Bases require more than just a set of universally true statements, without any reference to a situation, a point in time, or generally a context. Our proposed solution is to use the notion of context to separate statements that refer to different contextual information, which could so far not explicitly be tied to the statements. In this paper we describe a practical solution to this problem, which has been implemented in the VIKEF project, which deals with making explicit and intelligently useable information contained in vast collections of documents, databases and metadata repositories

What a Publication Tells You -- Benefits of Narrative Information Access in Digital Libraries

“…Hand-crafted rules were then formulated to determine how to combine contexts and their enclosed statements. VIKEF is an example digital library project supporting explicit context information in an RDF knowledge base [23].…”

The Jump Project: Practical Use of Semantic Web Technologies in Epss Systems

“…The RDFCore component represented in the subsystem architecture is a RDF storage system built on top of the Jena Toolkit; it offers a SPARQL Protocol implementation that, depending on the specific subsystem architecture, can be directly used to implement the subsystem interface to the JUMP framework or can be used to simplify data access. The solution is described in more detail in (Stoermer et al, 2006).…”

Federated description logics for the semantic web

“…Early recognition of the importance of careful treatment of context in artificial intelligence systems [68] was followed by work on non-montonic reasoning [68,67,70,78], propositional and quantificational (first order) logics of context [22,20,19,21] and context-based logics for distributed knowledge representation and reasoning [42,39,38,15]. More closely related to contextualizing information in the semantic web are the references [44,74,88,89,10].…”