Abstract: Using web standards, such as uniform resource identifiers (URIs), XML and HTTP, for naming and describing resources which are not information objects is the key difference between the Web as we know it today and the Semantic Web. Naming and interlinking this type of resources by HTTP URIs (instead of individual constants in a formal language) is the key feature which distinguishes traditional knowledge representation from web-scale knowledge representation. However, this use of URIs brought back attention to the old philosophical problem of identity and reference in a new form. In this paper, we analyze the new version of the problem, provide a formal model for dealing with it when interlinking knowledge on the Web, and argue for the need of a distinction between the use of URIs for describing and accessing resources, and the use of URIs for fixing the reference. We show that in the current practice of linking data these roles are not clearly distinguished, and that this fact may cause unwanted effects and prevent some basic forms of data integration. We also discuss the role of an entity name system as a potential piece of infrastructure for fixing the reference in the Semantic Web.
Abstract: The very simple structure of the RDF data model and semantics can lead to a number of issues when more complex scenarios are supposed to be represented in RDF. Aspects such as temporary evolution of a knowledge base, relevance and trust require more than just a model that consists of 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 because of the simplicity of RDF. In this paper we describe a practical solution to this problem, which has been implemented in the VIKEF project.
Abstract: Knowledge Representation in the Semantic Web is mainly characterized by the capabilities of the languages OWL and RDF. When attacking non-trivial problems such as the creation and maintenance of large-scale knowledge bases in RDF, it becomes evident that RDF lacks a central feature, namely the capability of restricting the truth value of a statement to a context, with far-reaching consequences which we will hint at in this paper. We propose a solution approach to this problem: the extension of RDF knowledge bases with context features. We will present theoretical background, envisioned experiments as well as a comparative study based on two technically different approaches, and illustrate the applications and benefits of contextual Knowledge Representation in the Semantic Web.
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.
Abstract: In so-called Virtual Information Environments (VIEs), which consist of meta-information about vast document collections, the exchange and integration of hierarchical classification schemas are important issues in terms of semantic interoperability. We see schema exchange between agents and the resulting integration process as a context switch. Thus we present an approach for semantic schema integration based on formal logics of context, by exploiting the contextualization features of an existing schema matching algorithm and storing the elicited semantics of the schema in a VIE for later use by semantic-based community processes.
Abstract: Large-scale knowledge representation (KR) with RDF unveils shortcomings which become obvious when facts have to be further qualified with contextual aspects to represent anything else but simplistic binary predicates. Motivated by requirements in the VIKEF project, in which we are required to store a large amount of information extracted from a heterogeneous set of documents and encoded in RDF triples, we are proposing an architecture for modelling context in RDF knowledge bases. Our approach â based on well-researched theories of context in KR â avoids issues that other approaches face, by preserving standard RDF within a context and adding context semantics and relations between contexts around the standard. In this paper we will present our approach, including formal definitions of our extensions and an illustration of further works.
Abstract: Software development in globally distributed projects is becoming increasingly popular due to a number of reasons. This paper will provide an insight into arising challenges and possible solutions. It concludes that - regarding culture and communication - there is still work to be done in some fields so that the successful realization of globally distributed projects becomes normality.
