Ontology exemplification for aSPOCMS in the Semantic Web

The support of constructs in thesaurus tools from a Semantic Web perspective: Framework to assess standard conformance

The Web Ontology Language OWL has been advocated as a suitable model for semantic data integration. Data integration requires expressive means to map between heterogeneous OWL schemas. This paper introduces SWQL (Semantic Web Query Language), a strictly typed query language for OWL, and shows how it can be used for mapping between heterogeneous schemas. In contrast to existing RDF query languages which focus on selection and navigation, SWQL also supports construction and user-defined functions to allow for instantiating integrated global schemas in OWL.

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.

With the wide spread of Open Linked Data and Semantic Web technologies, a larger amount of data has been published on the Web in the RDF and OWL formats. This data can be queried using SPARQL, the Semantic Web Query Language. SPARQL cannot be understood by ordinary users and is not directly accessible to humans, and thus they will not be able to check whether the retrieved answers truly correspond to the intended information need. Driven by this challenge, natural language generation from SPARQL data has recently attracted a considerable attention. However, most existing solutions to verbalize SPARQL in natural language focused on English and Latin-based languages. Little effort has been made on the Arabic language which has different characteristics and morphology. This work aims to particularly help Arab users to perceive SPARQL queries on the Semantic Web by translating SPARQL to Arabic. It proposes an approach that gets a SPARQL query as an input and generates a query expressed in Arabic as an output. The translation process combines both morpho-syntactic analysis and language dependencies to generate a legible and understandable Arabic query. The approach was preliminary assessed with a sample query set, and results indicated that 75% of the queries were correctly translated into Arabic.

Alternatives for facilitating automatic transformation of BIM data using semantic query languages

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.

The Semantic Web is an extension of the current web in which information is\ngiven well-defined meaning. The perspective of Semantic Web is to promote the\nquality and intelligence of the current web by changing its contents into\nmachine understandable form. Therefore, semantic level information is one of\nthe cornerstones of the Semantic Web. The process of adding semantic metadata\nto web resources is called Semantic Annotation. There are many obstacles\nagainst the Semantic Annotation, such as multilinguality, scalability, and\nissues which are related to diversity and inconsistency in content of different\nweb pages. Due to the wide range of domains and the dynamic environments that\nthe Semantic Annotation systems must be performed on, the problem of automating\nannotation process is one of the significant challenges in this domain. To\novercome this problem, different machine learning approaches such as supervised\nlearning, unsupervised learning and more recent ones like, semi-supervised\nlearning and active learning have been utilized. In this paper we present an\ninclusive layered classification of Semantic Annotation challenges and discuss\nthe most important issues in this field. Also, we review and analyze machine\nlearning applications for solving semantic annotation problems. For this goal,\nthe article tries to closely study and categorize related researches for better\nunderstanding and to reach a framework that can map machine learning techniques\ninto the Semantic Annotation challenges and requirements.\n

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.

Motivation The Semantic Web is an endeavor aiming at enriching the existing Web with meta-data and data (and meta-data) processing so as to allow computer systems to actually reason with the data instead of merely rendering it. To this aim, it is necessary to be able to query and update data and meta-data. Existing Semantic Web query languages (like DQL) are special purpose, i.e. they are designed for querying and reasoning with special representations like OWL or RDF, but are not capable of processing generic Web data. On the other hand, the language Xcerpt [1] [2] presented in the poster is a general purpose language that can query any kind of XML data and at the same time, being based on logic programming, provides advanced reasoning capabilities. It could thus serve to implement a wide range of different reasoning formalisms. Likewise, the maintenance and evolution of data on the (Semantic) Web is necessary: the Web is a ”living organism” whose dynamic character requires languages for specifying its evolution. This requirement regards not only updating data from Web resources, but also the propagation of changes on the Web. These issues have not received much attention so far, existing update languages (like XML-RL Update Language [3]) and reactive languages [4] developed for XML data offer the possibility to execute just simple update operations and, moreover, important features needed for propagation of updates on the Web are still missing. The language XChange also presented in the poster builds upon the query language Xcerpt and provides advanced, Web-specific capabilities, such as propagation of changes on the Web (change) and event-based communications between Web sites (exchange).

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 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.

Semantic Web (SW) technology aims to facilitate the integration of legacy data sources spread worldwide. Despite the plethora of SW languages (e.g., RDF/S, OWL) recently proposed for supporting large-scale information interoperation, the vast majority of legacy sources still rely on relational databases (RDB) published on the Web or corporate intranets as virtual XML. In this article, we advocate a first-order logic framework for mediating high-level queries to relational and/or XML sources using community ontologies expressed in a SW language such as RDF/S. We describe the architecture and reasoning services of our SW integration middleware, termed SWIM, and we present the main design choices and techniques for supporting powerful mappings between different data models, as well as reformulation and optimization of queries expressed against mediator ontologies and views.