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Description Logics (DLs) are gaining more popularity as the foundation of ontology languages for the Semantic Web. On the other hand, uncertainty is a form of deficiency or imperfection commonly found in the real-world information/data. In recent years, there has been an increasing interest in extending the expressive power of DLs to support uncertainty, for which a number of frameworks have been proposed. In this paper, we introduce an extension of DL (ALC) that unifies and/or generalizes a number of existing approaches for DLs with uncertainty. We first provide a classification of the components of existing frameworks for DLs with uncertainty in a generic way. Using this as a basis, we then discuss ways to extend these components with uncertainty, which includes the description language, the knowledge base, and the reasoning services. Detailed explanations and examples are included to describe the proposed completion rules. [ABSTRACT FROM AUTHOR]

With the increasing number of applications of description logics (DLs), unsatisfiable concepts and inconsistent terminologies become quite common, especially when the knowledge bases are large and complex. Even for an experienced knowledge engineer, it can be extremely difficult to identify and resolve the origins of these unsatisfiabilities and inconsistencies. Thus it is crucial to provide services to explain how and why a result is derived. Motivated by the possibilities of applying resolution technique in first-order logic to construct explanations for description logics, we extend our previous work and present an algorithm that generates explanations for unsatisfiability and inconsistency reasoning in the description language ALC. The main advantage of our approach is that it is independent of any specific DL reasoners. [ABSTRACT FROM AUTHOR]

Combining ontologies with rules has become a central topic in the Semantic Web. Bridging the discrepancy between these two knowledge representations, this paper introduces DatalogDL as a family of hybrid languages, where Datalog rules are parameterized by various DL (description logic) languages ranging from ALC to SHI Q. Making DatalogDL a decidable system with complexity of EXPTIME, we propose independent properties in the DL body as the restriction to hybrid rules, and weaken the safeness condition to balance the trade-off between expressivity and reasoning power. Building on existing well-developed techniques, we present a principled approach to enrich (RuleML) rules with information from (OWL) ontologies, and develop a prototype system integrating a rule engine (OO jDREW) with a DL reasoner (RACER). [ABSTRACT FROM AUTHOR]

Recognizing the complexity of the Description Logic-based query of 0WL-DL ontologies for the non-specialist, we introduce a query tool called Ontoligent Interactive Query (OntoIQ). This tool provides a well-organized user interface for a variety of users, from the beginner to the professional. Users can browse ontologies and build queries using query patterns and ontology content. OntoIQ translates queries automatically into the new RACER Query language (nRQL) syntax and presents them to description logic automated reasoner RACER which returns the query results. The tool includes import and export functions so that queries can be stored, shared, and re-imported by other users. Users are not required to learn the nRQL syntax. OntoIQ software is available for download at The FungalWeb website. [ABSTRACT FROM AUTHOR]

Learning objects are the currency for Educational Information Systems which support learning on the Educational Semantic Web. As such, proper metadata infrastructure must be set up around learning objects so that they are described in a way that agents can understand and also in a way that allows reuse. There are numerous problems with the LOM specification to date, but many research attempts advocate the use of various ontologies in alleviating some of the problems faced with the learning object metadata standards. However, there is a lack of practical examples describing exactly how these ontologies can be attached to a learning object. In light of this, our paper describes a practical approach that makes use of the IEEE LOM standard and which allows multiple ontologies to be included in the markup of learning objects. [ABSTRACT FROM AUTHOR]

Integration of ontologies of information sources and consumers is important for achieving web-based interoperability and thus for the success of the Semantic Web as a whole. The present work describes an approach for eliminating semantic conflicts with the purpose of integrating ontologies of heterogeneous information sources. The paper is focused on elimination of homonymy and finding synonymy in ontologies of learning objects (namely course outlines) and identification of (in)compatibilities between course descriptions. As a proof of concept, ontologies are implemented using the XML-based Rule Markup Language (RuleML), which has been combined with the Web Ontology Language (OWL), a W3C standard, to form the Semantic Web Rule Language (SWRL). This representation in RuleML allows the ontology to be executable, flexibly extensible and platform-independent. The RuleML source representation can also easily be converted to other XML-based languages (such as RDF, OWL and SWRL) as well as incorporated into existing XML-based repositories (such as IEEE LOM and CanLOM) using XSL Transformations (XSLT). The facts and rules of the RuleML-based ontology are used by the OO jDREW reasoning engine to identify semantic homonymy and synonymy between components of course descriptions. [ABSTRACT FROM AUTHOR]

The growth of interest in Semantic Web has increased the number of ontologies. Necessity of dealing with different ontologies at the same time has enhanced the research on ontology integration. This paper is focused on integrating ontologies covering the same domain. In particular, a novel approach of semantically parsing multiword elements (SPME) is presented in this paper. What is more, paper exemplifies the approach on ontology examples from e-learning domain and confirms the approach with existing ontologies. In addition, paper shows that it produces results with respect to information retrieval techniques. [ABSTRACT FROM AUTHOR]

An approach for managing knowledge in an organisation in the new infrastructure of Semantic Web consists of building a Corporate Semantic Web (CSW). The main components of a CSW are (i) evolving resources distributed over an intranet and indexed using (ii) semantic annotations expressed with the vocabulary provided by (iii) shared ontology. However, changes in the operating environment may lead to some inconsistencies in the system and they result in need of modifications of the CSW components. These changes need to be evolved and well managed. In this paper we present a rule-based approach allowing to detect and correct semantic annotation inconsistencies. This rule-based approach is implemented in the CoSWEM system enabling to manage the evolution of such a CSW, especially to address the evolution of semantic annotations when its underlying ontologies change. [ABSTRACT FROM AUTHOR]

The realization of Semantic Web vision is based on the creation and use of semantic web content which needs software tools both for semantic web developers and end users. Over the past few years, semantic web software tools like ontology editors and triple storage systems have emerged and are growing in maturity with time. While working on a large triple dataset during the course of a research aiming at a lifelong "semantic" repository of personal information, besides other semantic web tools, we used several RDF browsing and visualization tools for analyzing our data. This analysis included ensuring the correctness of the data, conformance of instance data to the ontology, finding patterns and trails in the data, cross-checking and evaluating inferred data, etc. We found that many of the features needed by a metadata creator and analyst are missing from these tools. This paper presents an investigation of the tools that are used for browsing and visualizing the datasets. It first identifies the browsing and visualization features required by a semantic web developer and a metadata creator and analyst and then based on these features evaluates the most common RDF browsing and visualization tools available till date. We conclude this paper with recommendations for requirements to be fulfilled for future semantic web browsing and visualization. [ABSTRACT FROM AUTHOR]

Bioinformaticians are accustomed to going through analysis steps, in which they employ several data sources, like protein sequence and protein interaction databases, to carry out their study. However, the ever-growing size and the dynamic nature of the biological databases make it almost impossible to use the biological data without a sophisticated data-providing infrastructure. In this paper, we introduce a distributed data providing agent system that answers biological queries according to its ontology of biological entities. [ABSTRACT FROM AUTHOR]

In the context of the Semantic Web, it may be beneficial for a user (consumer) to receive ratings from other users (advisors) regarding the reliability of an information source (provider). We offer a method for building more effective social networks of trust by critiquing the ratings provided by the advisors. Our approach models the consumer's private reputations of advisors based on ratings for providers whom the consumer has had experience with. It models public reputations of the advisors according to all ratings from these advisors for providers, including those that are unknown to the consumer. Our approach then combines private and public reputations by assigning weights for each of them. Experimental results demonstrate that our approach is robust even when there are large numbers of advisors providing large numbers of unfair ratings. As such, we present a framework for sharing ratings of possibly unreliable sources, of value as users on the Semantic Web attempt to critique the trustworthiness of the information they seek. [ABSTRACT FROM AUTHOR]

Social networks let the people find and know other people and benefit form their information. Semantic Web standard ontologies support social network sites for making use of other social networks information and hence help their expansion and unification, making them a huge social network. As social networks are public virtual social places much information may exist in them that may not be trustworthy to all. A mechanism in needed to rate coming news, reviews and opinions about a definite subject from users, according to each user preference. There should be a feature for users to specify how much they trust a friend and a mechanism to infer the trust from one user to another that is not directly a friend of the user so that a recommender site can benefit from these trust ratings for showing trustworthy information to each user from her or his point of view from not only her or his directly trusted friends but also the other indirectly trusted users. This work suggests using fuzzy linguistic terms to specify trust to other users and proposes an algorithm for inferring trust from a person to another person that may be not directly connected in the trust graph of a social network. The algorithm is implemented and compared to an algorithm that let the users to specify their trust with a number in a definite range. While according to the imprecise nature of the trust concept writing and reading a linguistic expression for trust is much more natural than a number for users, the results show that the algorithm offers more precise information than the previously used algorithm especially when contradictory beliefs should be composed and also when a more precise inference is potentially possible in searching deeper paths. As the trust graphs and inference are viewed abstractly, they can be well employed in other multi agent systems. [ABSTRACT FROM AUTHOR]

Heterogeneity is an inherent characteristic of open and distributed environments like the Internet that can hamper Web resources and Web services from successful interoperation. Mediation can be used to resolve these issues, which are critical problems in the Semantic Web. Appropriate technologies for mediation need to cover two aspects: first, techniques for handling the different kinds of heterogeneity that can occur between Web resources, and secondly logical components that connect resources and apply required mediation technique along with invocation and execution facilities. This paper presents an integrated model for mediation on the Semantic Web with special attention to Semantic Web services that is developed around the Web Service Modeling Ontology WSMO. Covering both dimensions, we explain the techniques developed for handling different types of heterogeneity as well as the components and architecture for establishing interoperability on the Semantic Web if not given a priori. [ABSTRACT FROM AUTHOR]