RDFS(FA): Connecting RDF(S) and OWL DL

An article tries to see a group of semantic web representation and communication means like description logics, semantic networks, RDF model and language, OWL language, RDF CFL etc. taking a part at the development of formal ontologies from a slightly higher (meta) level. A focus has been oriented towards properties that semantic web language ought to have to fulfill according to a semantic web idea. Consequently the article tries to draw by the help of the means above the trip towards a proper semantic-web ontology language fulfilling the main demands of expressivity and also easy-to-use conditions. Even if the development of a semantic web language was until now much more complicated with a taking part of a lot of people or companies the authors of the article try to contribute to an analyzing of the actual state by drawing it as a cloud of demands, streams, events or condition’s fulfilling that at the end would have brought into the world an easy-to-usable semantic web ontology language having all the demands fulfilled. The article moreover shows that a language RDF CFL belongs nowadays to the semantic web family as a unique well usable tool of reasoning within semantic web knowledge bases.

In this paper we give details about the role of ontologies in Semantic Web and tools required for constructing Semantic Web applications. The Protégé tool for ontology development and knowledge acquisition can be adapted for editing models in different Semantic Web languages. In recent experiments to prototype the Semantic Web, members of different communities with different backgrounds have created a multitudinous of languages for representing ontologies and instance data on the Web. Typically, a Semantic Web language for describing ontologies and instance data contains a hierarchical description of important conceptual thing in a domain. Individuals in the domain are instances of these classes, and properties of each classes describes the various features and attributes of the concept. Logical statements describe relations among concepts. Protégé adopt the new world of the Semantic Web reusing its user interface, internal representation, and framework also it is useful in conceptual modeling with the new Semantic Web languages.

Web Ontology Language (OWL), Semantic Web Rule Language (SWRL) and Model-Driven Engineering (MDE) are technologies being developed in parallel, but by different communities. They have common points and issues and can be brought closer together. Many authors have so far stressed this problem and have proposed several solutions. The result of these efforts is the recent OMG’s initiative for defining an ontology development platform. However, the problem of transformation between Semantic Web ontology and rule languages and MDE-based languages has been solved using rather partial and ad hoc solutions, most often by XSLT. In this paper, we relations between the Semantic Web languages and MDE-compliant languages as separate technical spaces. In order to achieve a synergy between these technical spaces, we present ontology and rule languages in terms of MDE standards, recognize relations between the OWL and SWRL langauges and MDE-based ontology languages, and propose mapping techniques. In order to illustrate the approach, we use an MDE-defined architecture that includes the ontology and rule metamodels and ontology UML Profile. We also show how MDE techniques, such as model transformations, can be used to enable sharing rules and ontologies by using REWERSE Rule Markup Language (R2ML), a proposal for a general rule language. The main benefit of this approach is that it keeps the focus on the language concepts (i.e., languages’ abstract syntax - metamodels) rather than on technical issues caused by different concrete syntax. Yet, we also provide transformations that bridge between both languages’ concrete (XML) and abstract (MOF) syntax.

The automation of software development processes is a desirable goal of current software companies which would lead to a cost reduction in software production. This automation is the backbone of approaches such as Model Driven Architecture (MDA) or Software Factories. This paper proposes the use of standard Business Rules (using Rules Interchange Format, RIF) to specify application functionality along with a platform to produce automatic implementations for them. The novelty of this proposal is to introduce Business Rules at all levels of MDA architecture in a software development process, providing a supporting tool where production Business Rules are considered at every abstraction level. Production Business Rules are represented through standard languages, rule engine vendor independence is assured via automatic transformation between rule languages, and Business Rules reuse is made possible. The objective is to get the development of production Business Rules closer to non-technical people involved in the software development process through the use of natural language processing approaches, automatic transformations among models and semantic web languages such as Ontology Web Language (OWL).

Explicit modeling of administrative workflow processes and their enactment in workflow systems have proved to be valuable in increasing the efficiency of work in organizations on the basis of distributed information for different parties. The Semantic Web is the provision to provide distributed information with well-defined meaning and understandability for different parties such as machine as well as human. “An Agent-based Semantic Web for Paperless Office Content Management System” (aSPOCMS) intends to provide paperless environment for administrative offices of universities and institutes. In this paper, we discuss the ontologies framework with their suitable exemplification for aSPOCMS in paperless environment with the emergence of the Semantic Web perspective and show that how the Semantic Web resource description formats and language can be utilized for paperless office content management system of hypertext structures from distributed metadata. The resources of aSPOCMS are domain, user and observation, which are reconnoitered from ontologies and metadata. We consider a logic-based approach for administrative workflow services using TRIPLE, which facilitate the rule and query language for Semantic Web.

Recently, there has been an increasing interest in formalisms for representing uncertain information on the Semantic Web. This interest is triggered by the observation that knowledge on the web is not always crisp and we have to be able to deal with incomplete, inconsistent and vague information. The treatment of this kind of information requires new approaches for knowledge representation and reasoning on the web as existing Semantic Web languages are based on classical logic which is known to be inadequate for representing uncertainty in many cases. While different general approaches for extending Semantic Web languages with the ability to represent uncertainty are explored, we focus our attention on probabilistic approaches. We survey existing proposals for extending semantic web languages or formalisms underlying Semantic Web languages in terms of their expressive power, reasoning capabilities as well as their suitability for supporting typical tasks associated with the Semantic Web.

The current architecture for the Semantic Web, with its emphasis on RDF syntactic and semantic compatability, has severe problems when expressive Semantic Web languages are incorporated. An architecture less tied to RDF is proposed. In this architecture different Semantic Web languages can have different syntaxes but must use the same models. This revised architecture provides significant advantages over the currrent Semantic Web architecture while still remaining true to the vision of the Semantic Web.

Semantic web reasoners and languages enable the semantic web to function. Some of the latest reasoning models developed in the last few years are: DLP, FaCT, RACER, Pellet, MSPASS, CEL, Cerebra Engine, QuOnto, KAON2, HermiT and others. Some software tools such as Protege, Jena and others also have been developed, which provide inferencing as well as ontology development and management environments. These reasoners usually differ in their inference procedures, supporting logic, completeness of reasoning, expressiveness and implementation languages. Various semantic web languages with increasing expressive power continue to be developed for describing web services. We survey the some of the more recent languages like OWL-S (Ontology Web Language-Schema), WSML (Web Service Modeling Language), SWRL (Semantic Web Rule Language) and others that have been tested in early use. We also survey semantic web reasoners and their relationship to these languages.

Ontologies will play a central role in the development of the Semantic Web. It is unrealistic to assume that such ontologies will be developed from scratch. Rather, we assume that existing resources such as thesauri and lexical data bases will be reused in the development of ontologies for the Semantic Web. In this paper we describe a method for converting existing source material to a representation that is compatible with Semantic Web languages such as RDF(S) and OWL. The method is illustrated with three case studies: converting WordNet, AAT and MeSH to RDF(S) and OWL.KeywordsHierarchical RelationSyntactic TransformationPort ResourceSubclass RelationDescriptor RecordThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Though many kinds of multi-agent systems based on argumentation have been proposed where only rule-based knowledge is taken into account, they have been unable to handle the ontological knowledge so far. In our daily life, however, there are a lot of human argumentation where both ontological and rule knowledges are used. For example, in e-commerce, a seller and a buyer usually use ontologies about products along with their respective strategic rules for buying and selling. Recent progress of the Semantic Web technology provides expressive ontology languages. In this paper, we demonstrate integration of the Semantic Web reasoning and argument-based reasoning. We have implemented the integrated system such that Logic of Multiple-valued Argumentation-based agent system (specialized to two values {f, t }) can be accessible to the Semantic Web reasoning established as the description logic reasoning system, given ontologies expressed by OWL DL or its notational variant the DL SHOIN(D). An interesting argumentation result using both ontologies and rules about the university curriculum is shown as an example executed by our system.

Question-Answering (QA) system is improved version of search engines or can be stated as specific Search engines because search engines deliver data in the form of URLs whereas Question-Answering system produces direct answer to the query asked. That's why more focus has been put on developing better Question Answering systems that could respond to large variety of user query. Semantic Web Technology has aided to the development of such systems from past many years because it could add meaning to the query being asked. Such systems are more efficient than the systems developed in other languages. In this paper, we have proposed a QA system of JAVA Programming Language, where knowledge will be represented in the form of Ontology and based on relations derived from domain knowledge to obtained final answer. Information present in Ontology is represented in the form of tables to feed in knowledge base. It combines the techniques of Natural Language Processing and Semantic Web.

The Semantic Web offers significant capabilities that transform the current Web into a global knowledge base including various cross-linked multimedia content with formal descriptions of its semantics understandable to humans and processable by computers. Content on the Semantic Web can be subject to reasoning and queries with standardized languages, methods and tools, which opens new opportunities for collaborative creation, use and exploration of web repositories. However, these opportunities have not been exploited so far by the available 3D formats and modeling tools, which limits the possibilities of search and reuse of 3D content as part of the Semantic Web. This work contributes a semantic development pipeline of the X3D Ontology, with corresponding conversion of X3D models into triple forms suitable for formal query. The ontology design reflects experience accompanying the development of the Extensible 3D (X3D) Graphics International Standard, in particular, the X3D Unified Object Model (X3DUOM). This approach combines semantic and syntactic elements of X3D models and metadata to support integration with the Semantic Web. The pipeline enables automatic generation of the X3D Ontology, thereby providing an up-to-date 3D representation with semantics during X3D specification development. By extending commonplace model conversions from other formats to X3D, the ontology presents the potential to enable integration of most forms of 3D content with the Semantic Web.

The Resource Description Framework and the Resource Description Framework Schema Specification are supposed to be the foundations of the Semantic Web, in that all other Semantic Web languages are to be layered on top of them. It turns out that such a layering cannot be achieved in a straightforward way. This paper describes the problem with the straightforward layering and lays out several alternative layering possibilities. The benefits and drawbacks of each of these possibilities are presented and analyzed.

Clinical practice guideline is an evolving reference document that contains recommendations and knowledge which aims to assist professionals to master a medical domain. In our work, we are interested in using these documents in order to assist doctors to make decisions about appropriate health care for patients who are at risk of cardiovascular disease. More precisely, our paper proposes an automatic approach that parses and transforms text (clinical practice guideline) into OWL DL (Ontology Language Web Description Logic) axioms and SWRL (Semantic Web Rule Language) rules. To parse the text, we have used an existing ontology of cardiovascular domain and natural language processing tools (NLP). Our work is original in that studies the mapping between text and SWRL rules while the related works are focused only on mapping text on OWL lightweight axioms.

In this paper we explore some of the opportunities and challenges for machine learning on the Semantic Web. The Semantic Web provides standardized formats for the representation of both data and ontological background knowledge. Semantic Web standards are used to describe meta data but also have great potential as a general data format for data communication and data integration. Within a broad range of possible applications machine learning will play an increasingly important role: Machine learning solutions have been developed to support the management of ontologies, for the semi-automatic annotation of unstructured data, and to integrate semantic information into web mining. Machine learning will increasingly be employed to analyze distributed data sources described in Semantic Web formats and to support approximate Semantic Web reasoning and querying. In this paper we discuss existing and future applications of machine learning on the Semantic Web with a strong focus on learning algorithms that are suitable for the relational character of the Semantic Web's data structure. We discuss some of the particular aspects of learning that we expect will be of relevance for the Semantic Web such as scalability, missing and contradicting data, and the potential to integrate ontological background knowledge. In addition we review some of the work on the learning of ontologies and on the population of ontologies, mostly in the context of textual data.