Semantic Web Rule Language

Background: Semantic Web technology can considerably catalyze translational genetics and genomics research in medicine, where the interchange of information between basic research and clinical levels becomes crucial. This exchange involves mapping abstract phenotype descriptions from research resources, such as knowledge databases and catalogs, to unstructured datasets produced through experimental methods and clinical practice. This is especially true for the construction of mutation databases. This paper presents a way of harmonizing abstract phenotype descriptions with patient data from clinical practice, and querying this dataset about relationships between phenotypes and genetic variants, at different levels of abstraction. Methods: Due to the current availability of ontological and terminological resources that have already reached some consensus in biomedicine, a reuse-based ontology engineering approach was followed. The proposed approach uses the Ontology Web Language (OWL) to represent the phenotype ontology and the patient model, the Semantic Web Rule Language (SWRL) to bridge the gap between phenotype descriptions and clinical data, and the Semantic Query Web Rule Language (SQWRL) to query relevant phenotype-genotype bidirectional relationships. The work tests the use of semantic web technology in the biomedical research domain named cerebrotendinous xanthomatosis (CTX), using a real dataset and ontologies. Results: A framework to query relevant phenotype-genotype bidirectional relationships is provided. Phenotype descriptions and patient data were harmonized by defining 28 Horn-like rules in terms of the OWL concepts. In total, 24 patterns of SWQRL queries were designed following the initial list of competency questions. As the approach is based on OWL, the semantic of the framework adapts the standard logical model of an open world assumption. Conclusions: This work demonstrates how semantic web technologies can be used to support flexible representation and computational inference mechanisms required to query patient datasets at different levels of abstraction. The open world assumption is especially good for describing only partially known phenotype-genotype relationships, in a way that is easily extensible. In future, this type of approach could offer researchers a valuable resource to infer new data from patient data for statistical analysis in translational research. In conclusion, phenotype description formalization and mapping to clinical data are two key elements for interchanging knowledge between basic and clinical research.

This book constitutes the refereed proceedings of the 7th International Semantic Web Conference, ISWC 2008, held in Karlsruhe, Germany, during October 26-30, 2008. The volume contains 43 revised full research papers selected from a total of 261 submissions, of which an additional 3 papers were referred to the semantic Web in-use track; 11 papers out of 26 submissions to the semantic Web in-use track, and 7 papers and 12 posters accepted out of 39 submissions to the doctorial consortium. The topics covered in the research track ...

Ontologies implemented in RDF(S)‚ DAML+OIL‚ and OWL should be evaluated from the point of view of knowledge representation before using them in Semantic Web applications. Several language-dependent ontology validation tools and ontology platforms‚ such as OilEd with FaCT‚ can be used in order to evaluate RDF(S)‚ DAML+OIL and OWL ontologies. This paper offers two main contributions. The first of these exams whether previous ontology tools detect knowledge representation problems in RDF(S)‚ DAML+OIL‚ and OWL concept taxonomies. Indeed‚ such tools do not focus on detecting inconsistencies and redundancies in concept taxonomies. The second contribution is ODEval‚ a language-dependent tool for evaluating‚ from the point of view of knowledge representation‚ concept taxonomies in ontologies implemented in such languages. ODEval complements previous ontology tools when we want to evaluate RDF(S)‚ DAML+OIL‚ and OWL concept taxonomies.

As the Semantic Web and the Language Resources research fields become closer, the need for standard representation formats and languages gets clearer, specially taking into account the increasing need for cooperation and interoperability between both fields that is being set forth. The purpose of this paper is to present how this process of standardisation and integration is being achieved in ContentWeb by means of OntoTag, a multi-level (also multipurpose and possibly multi-language) hybrid (ontologic and linguistic) platform for Semantic Web annotation, designed according to EAGLES standards and implemented with last generation Semantic Web languages (XML/ RDF(S)/OWL).

Semantic Web Services are considered to be the next step in the evolution of Web Services. In addition to Web Services, Semantic Web Services allows software agents to discover, select, call, compose, invoke, and execute automatically a Web services without ...

In this paper we propose the Fire system, a prototype rule engine for reasoning with SWRL (Semantic Web Rules Language) rules and OWL (Ontology Web Language) ontologies. This system is intended as an extension to the reasoning services of the RACER system . For ease of implementation, support is currently provided for SWRL rules that are restricted as follows: (i) Rules must be atomic (single atom in the rule consequent); (ii) Rules must have tree-shaped antecedents; (iii) Rules must be 'strictly Horn' (predicates of rule atoms may only be 'name' of property or class); (iv) SWRL built-ins, sameAs, differentFrom or OWL DatatypeProperty may not be used for predicates in rule atoms. The Fire system is implemented in Java in the following way; Rules defined in the ontology are extracted using Protégé's SWRL API . Facts asserted in and entailed by the ontology are obtained from RACER. The RETE algorithm [1, 2] is implemented for 'pattern matching' these facts with patterns in rule antecedents. Materialization of rules for which instantiations/bindings are provided by the pattern matcher, is done by synchronizing with RACER's inferences. Simple 'random selection' strategy is applied in resolving the conflict when more than one 'new' rule instantiation is provided at the same time. The reasoning process terminates when no 'new' inference is found compared to the already 'known' facts (asserted, entailed or new inferences from rules materialized earlier). Reasoning is offered in two modes, based on the number of rule instantiations considered during materialization for a given state of the knowledge base; (i) One-at-a-time mode: 'one' rule instantiation for an applicable rule at a time, and (ii) Batch mode: 'all' rule instantiations for all applicable rules at once in a batch. Our initial results of Fire's performance over example SWRL ontologies have been very encouraging. We are currently working on several open issues to optimize Fire's performance and extend its services: (i) Extend support for use of OWLDatatypeProperty, sameAs and different-From predicates in rules; (ii) Optimize construction of the RETE pattern network by exploiting the common predicates generally existing among different rules; (iii) Use the publish-subscribe mechanism from RACER to efficiently learn about the changes (newly asserted/inferred instantiations) made to any concept in the ontology that is relevant for rule reasoning; (iv) Provide Fire as a plug-in support for Protégé's SWRL Tab; (v) Integrate an optimized version of Fire as a rule engine for nRQL (new Racer Query Language) rules [4] into the RACER system.

The Semantic Web renewed a growing interest in rule based software systems and their development. Semantic Web Rule Language (SWRL) is a rule language that enables Horn-like rules to be combined with Web Ontology Language (OWL) knowledge bases to provide even more expressivity. However, as rule based web system mature, the number of rules they use grows making them difficult to manage. Developers face problems when trying to understand and control the big rule sets they create. In order to address this problem, techniques and tools are necessary to organize, view and create new rules as part of a large rule set. This work presents strategies and techniques developed in order to improve SWRL tools based upon a survey of rule tools, a study of the state of the art and the analysis of representative rule sets.

SQOWL2 is a compiler which allows an RDBMS to support sound reasoning of SROIQ(D) description logics, by implementing ontologies expressed in the OWL 2 DL language as a combination of tables and triggers in the RDBMS. The reasoning process is divided into two phases of classification of the T-Box and type inference of the A-Box. SQOWL2 establishes a relational schema based on classification completed using the Pellet reasoner, and performs type inference by using SQL triggers. SQOWL2 supports type inference over all OWL 2 DL constructs, and supports a more conventional relational schemas, rather than naively mapping OWL classes and properties to relational tables with one and two columns. Moreover, SQOWL2 is a transactional reasoning system (with full ACID properties), since the results of reasoning are available within the same transaction as that in which the base data of the reasoning was inserted.

In this report we describe a method to perform type inference over data stored in an RDBMS, where rules over the data are specified using OWL-DL. Since OWL-DL is an implementation of the Description Logic (DL) SHOIN (D), we are in effect implementing a method for SHOIN (D) reasoning in relational databases. Reasoning make be broken down into two processes of classification and type inference. Classification may be performed efficiently by a number of existing reasoners, and since classification alters the schema, it need only be performed once for any given relational schema as a preprocessor of the schema before creation of a database schema. However, type inference needs to be performed for each data value added to the database, and hence needs to be more tightly coupled with the database system. Previously, no technique has been proposed that implements SHOIN (D) type inference within an RDBMS. We propose such a technique, involving the use of triggers to perform reasoning over the data values as they inserted into the database. We demonstrate the soundness and performance of our approach by comparing an implementation of our technique against other existing approaches for less powerful reasoning over data in an RDBMS. The results show we provide the fastest query processing of any technique, despite having a more powerful reasoner.

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Most healthcare data are available in XML format, which mainly focuses on the structure level and lacks support for data representation. Therefore, a variety of medical applications and medical semantic search engines have difficulty understanding and integrating healthcare data in a highly heterogeneous environment. OWL (Web Ontology Language) and Semantic Web technologies provide an infrastructure that can solve these problems. The aim of our study is to present a mechanism to ease the interpretation and automate the semantic transformation of XML healthcare data into the OWL ontology (S-Trans), which allows an easier and better semantic communication among hospital information systems. On the basis of the XML schemas (XSD or DTD), we extract the document structure and add more descriptions for XML elements. Moreover, to classify the semantic level of duplicate elements in an XML schema, we propose novel metrics to measure the similarity between them. Experimental results show that the proposed method reliably predicts semantic similarity of duplicates and produces a better-quality OWL ontology.

The purpose of the present paper is to research a rule-based approach for transforming X3D (eXtensible 3D) models to RDF (Resource Description Framework). The transformation is performed by using the RDF Mapping Language (RML). Its advantages are summarized, which are mainly due to the fact that the rules created build a knowledge base. By applying SPARQL (SPARQL Protocol and RDF Query Language) queries to it, the possibility of explore in order to validate and improve the defined RML rules themselves, is pointed out. An approach for reversing from the RDF triples to the original X3D in a unique way is considered, and the types of SPARQL queries needed for its implementation are systematized. Rules are formulated for all elements defined in the X3D schema, their attributes and properties are described. Their accessibility is ensured. The conversion of X3D models to RDF is confirmed to be consistent with guidelines and best practices for creating accessible, understandable, and reusable ontologies on the Web. The systematized SPARQL query types for reversing from RDF triples to the original X3D are checked for specific elements and sample data, and the obtained results establish their correctness. The prerequisites and limitations of the represented approach are explained. The proposed approach allows building a comprehensive knowledge base that includes the RML rules, the transformed X3D models and the domain-specific ontology and its use to analyzing data and semantic reasoning. The electronic libraries that include 3D content could take advantage from the benefits and possible future applications of the solutions discussed in this study.

Personalized access and content syndication involving diverse conceptual representations of information resources are two of the key challenges of real-scale Semantic Web (SW) applications, such as e-Commerce, e-Learning or e-Science portals. RDF/S represents nowadays the core SW language for creating and exchanging resource descriptions worldwide. Unfortunately, full-fledged view definition languages for the RDF/S data model are still missing. We propose RVL, a view definition language capable of creating not only virtual resource descriptions, but also virtual RDF/S schemas from (meta)classes, properties, as well as, resource descriptions available on the Semantic Web. RVL exploits the functional nature and type system of the RQL query language in order to navigate, filter and restructure complex RDF/S schema and resource description graphs.

In this paper, we propose to bring together the semantic web experience and statistical natural language semantic parsing modeling. The idea is that, the process for populating knowledgebases by semantically parsing structured web pages may provide very valuable implicit annotation for language understanding tasks. We mine search queries hitting to these web pages in order to semantically annotate them for building statistical unsupervised slot filling models, without even a need for a semantic annotation guideline. We present promising results demonstrating this idea for building an unsupervised slot filling model for the movies domain with some representative slots. Furthermore, we also employ unsupervised model adaptation for cases when there are some in-domain unannotated sentences available. Another key contribution of this work is using implicitly annotated natural-language-like queries for testing the performance of the models, in a totally unsupervised fashion. We believe, such an approach also ensures consistent semantic representation between the semantic parser and the backend knowledge-base.

The domain module within Intelligent Tutoring Systems is used to describe the course topics including the knowledge units and competencies. Ontology is a good solution for knowledge management as it can provide a standardized way and a reasoning engine for the related knowledge management tasks. In this paper, we analyze the functionality of the usual OWL-based ontology construction and set the main requirements to enhance the usability of the ontology knowledge modelling language. Based on these shortcomings, we set the main requirements against an efficient ITS domain ontology description language. This language should be based on simplified Manchester syntax and it should contain additional structural elements too.

In this paper the Web Ontology Language (OWL) is examined to instantiate expert system knowledge bases intended for semantic Web applications. In particular, OWL is analyzed for expressing Unified Modeling Language (UML) representations that have been augmented with propositional logic asserted as inter-link constraints. The motivation is ultimately to provide declarative propositional logic constraints that can be represented in UML and declaratively implemented using OWL and other constructs to realize semantic Web knowledge base repositories and databases to facilitate expert system applications. The results of this paper show that OWL is sufficient for capturing most inter-link constraints asserted on generalization=specialization instances; however, OWL alone is inadequate for representing some inter-link constraints asserted on associations. We propose enhancements to OWL via RDF extensions for the reification of associations into classes. These extensions mitigate all concerns that were identified in OWL as part of this study. The result is increased support of declarative constraint representations, which can be expressed in knowledge bases in the context of the semantic Web.

The I/O model of computation measures the efficiency of an algorithm by counting how many disk reads and writes it needs. It is widely applicable to the database environment, since most data is stored on disks and disk access typically dominates CPU time.

Visualization is the graphical or semi-graphical representation of information that aids human comprehension of and reasoning about that information. Visualization tools are critically important for creating, querying, visualizing and validating Semantic Web Data. Semantic Web, an efficient infrastructure that enhances visibility of knowledge on the web, is often used more specifically to refer to the formats and technologies that enable it. These technologies include RDF, RDFS and OWL. However, lack of robust and efficient tools to visualize, analyze and represent these technologies within time and space constraint remains a big challenge. In this study, semantic web technologies and their visualization tools were reviewed. RROVT (RDF, RDFS, OWL Visualization Tool), a tool to evaluate and represent formal description of concepts, terms and relationships of data models within a given knowledge domain as well as manage time and space complexities for publishing contents of the semantic web more efficiently is developed and proposed. Performance of RROVT was investigated on samples of semantic web documents implementing RDF, RDFS and OWL technologies. The proposed tool showed remarkable improvement over the existing tools as it aids a better comprehension of the syntax and semantics of semantic web technologies investigated in this study.

Abstract. Intelligent text information retrieval systems need the capability to deal with the semantics of the content of their text bases. In order to satisfy this requisite it is necessary to extract semantic information from the documents and to be able to make inferences about ...

The COntext INterchange (COIN) strategy is an approach to solving the problem of interoperability of semantically heterogeneous data sources through context mediation. COIN has used its own notation and syntax for representing ontologies. More recently, the OWL Web Ontology Language is becoming established as the W3C recommended ontology language. We propose the use of the COIN strategy to solve context disparity and ontology interoperability problems in the emerging Semantic Webboth at the ontology level and at the data level. In conjunction with this, we propose a version of the COIN ontology model that uses OWL and the emerging rules interchange language, RuleML.

Background: The Unified Medical Language System is a formal ontology of the biomedical and health domain. Its goal is to offer a vocabulary that would facilitate the exchange of information between informatics systems. The semantics and basic facts of the UMLS are contained in the Semantic Network of Metathesaurus. The objective of this research is to translate their content into a OWL 2 Ontology that can be interrogated and inferenced through a SPARQL Endpoint. Methods: The translated model of the UMLS towards the UMLS-OWL was done through the classification of the conceptual entities, the atoms and the relationships of the UMLS into entities of the description logic T-BOX, R-BOX, and A-BOX. Results: The experimentation will validate the interoperability of the transformation by using tools of the semantic web to consult the UMLS-OWL.

Ontology as a knowledge base can provide different reasoning tasks, e.g. to check consistency of the ontology or to check whether a resource is instance of a concept or not. In this paper we want to focus on retrieval problem. There already exist systems resolving this problem, but they are not effective within large datasets. Our idea is to transform ontology into a relational database. We present particular algorithms of this transformation both on the scheme level and SQL level with special handling of functional roles and definitions. This enables to query such database by usual tools of SQL, i.e. to solve the retrieval problem.

The Semantic Web Rule Language (SWRL) is a direct extension of OWL 2 DL with a subset of RuleML, and it is designed to be the rule language of the Semantic Web. This paper explores the stateof-the-art of SWRL's expressiveness extensions proposed over time. As a motivation, the effectiveness of the SWRL/OWL combination in modeling domain facts is discussed while some of the common expressive limitations of the combination are also highlighted. The paper then classifies and presents the relevant language extensions of the SWRL and their added expressive powers to the original SWRL definition. Furthermore, it provides a comparative analysis of the syntax and semantics of the proposed extensions. In conclusion, the decidability requirement and usability of each expressiveness extension are evaluated towards an efficient inclusion into the OWL ontologies.

This paper presents the use of first-order logic to improve upon currently employed engineering design knowledge management techniques. Specifically, this work uses description logic in unison with Horn logic, to not only guide the knowledge acquisition process but also to offer much needed support in decision making during the engineering design process in a distributed environment. The knowledge management methods introduced are highlighted by the ability to identify modeling knowledge inconsistencies through the recognition of model characteristic limitations, such as those imposed by model idealizations. The adopted implementation languages include the Semantic Web Rule Language, which enables Horn-like rules to be applied to an ontological knowledge base and the Semantic Web's native Web Ontology Language. As part of this work, an ontological tool, OPTEAM, was developed to capture key aspects of the design process through a set of design-related ontologies and to serve as a...

In this recent technological world, it is necessary that we get accustomed to all types of advanced technological techniques. In the process, we are becoming more aware about database and information system. But what is database system information? The Database Management System which works through the storing of data can be used any time. The importance of database and information Systems in modern business is inevitable. In this chapter, we define Information Systems by its categories of Information System, type and the usefulness for efficient Information System. Then, we will proceed to explaining the management of information systems by taking a short look at its history and list some of its domains of application. After that, we define the relation between Information Systems and database. Finally, we will explore the problem of storage and some issues related to information systems and databases.

An important issue is to know whether Web ontology languages, meet the expected requirements of expressiveness and reasoning. This paper aims at contributing to this question in evaluating and comparing several languages. After describing the needs of a Semantic Web in medicine, it analyses Protégé and DAML+OIL primitives on a concrete medical ontology, the brain cortex anatomy ontology. It draws conclusions about the requirements that a Web ontology language should meet for the representation of medical taxonomy and axioms. The expressiveness of DAML+OIL or OWL DL seems suited to describe the complex taxonomic knowledge. But rules are required for representing the deductive knowledge (dependencies between relations) and to support several tasks (ontology construction, maintenance, verification, query of heterogeneous distributed information sources). Finally, the paper evaluates the features of the next standard OWL and of an hybrid language CARIN-ALN with respect to these requirements.

Abstract—Access to Web data has become an integral part of many applications and services. In the past, such data has usually been accessed through human-tailored HTML interfaces. Nowadays, rich client interfaces in desktop applications or, increasingly, in browser-based clients ease data access and allow more complex client processing based on XML or RDF data retrieved through Web service interfaces. Convenient speci cations of the data processing on the client and exible, expressive service interfaces for data access ...

Current efforts in the biomedical ontology community focus on establishing interoperability and data integration. In covering human diseases, one of the major international standards in clinical practice is the International Classification for Diseases (ICD), maintained by the World Health Organization (WHO). Several countryand language-specific adaptations exist which share the general structure of the WHO version but differ in certain details. This complicates the exchange of patient records and hampers data integration across language borders. We present our approach for modeling the hierarchy of the ICD-10 using the Web Ontology Language (OWL). Our model captures the hierarchical information of the ICD-10 as well as comprehensive class labels for English and German. Specialties such as “Exclusion” statements, which make statements about the disjointness of certain ICD-10 categories, are modeled in a formal way. For properties which exceed the expressivity of OWL-DL, we provide a...

The modelling of agriculture with ontologies has been of interest to many authors in the past years. However, no research, currently, has focused on building a knowledge base ontology for the Climate Smart Agriculture (CSA) domain. This study attempts to fill this gap through the development of a Climate Smart Agriculture Ontology (OntoCSA). Information was gathered from secondary sources including websites, published research articles and reports as well as related ontologies, to formalize the OntoCSA ontology in Description Logics (DLs). The OntoCSA ontology was developed in Web Ontology Language (OWL) with Protégé. Furthermore, the OntoCSA ontology was successfully validated with the HermiT reasoner within Protégé. The resulting OntoCSA ontology is a machine-readable model of CSA that can be leveraged in web-based applications for the storage, open and automated access and sharing of CSA information/data, for research and dissemination of best practices

An increasing part of research in the Semantic Web has been directed at making data become the main concept of the web. Plenty of languages and specifications support this transition and work by inserting additional (semantic) markup into web documents. Yet, little attention is being paid to the possibility of expressing the actual structures of the documents in a form suitable for the semantic web. EARMARK is a model for explicitly expressing structural assertions of markup and documents, allowing a straightforward integration of the semantics of the markup and the semantics of the content. The well-formedness of a hierarchy, for instance, becomes an explicit assertion and similarly the analysis of the validity of markup structures become matter for further semantic analysis. This paper describes EARMARK and shows a framework for using OWL ontologies, that implement particular markup properties, to demonstrate the compliance of EARMARK documents with those properties.

Multimedia service providers on the web need their services to be well protected and easily accessible worldwide. This has initiated several lines of research to provide semantically rich policy-aware web services. However, the existence of various technologies to define and protect services has made the communication of services questionable. Currently, it is ambiguous how a broker agent looking for a special object would communicate to an online service provider, with different policy and service definition languages, to obtain the appropriate object. Here, we propose a solution to such problems by introducing an interchange framework to transform business rules and policies between different enterprises using REWERSE Rule Markup Language.

The interest in the use of ontologies for creating more intelligent and effective enterprise information systems has increased considerably in recent years. The most critical aspects during the development of these systems are: (1) to identify the ontology concepts and (2) to make explicit the business rules by means of the ontology axioms. In order to address these issues, mappings of business rules expressions to ontology statements based on different languages were proposed. Despite the efforts made in this area, some work remain to be done. This work presents a set of ontology design patterns providing a way to obtain an OWL/SWRL ontology by applying metamodel transformation rules over the SBVR specification of a business domain. Patterns are rooted in the structural specification of the standards, providing a set of mappings readily usable for business people or developers concerned with the implementation of a mapping tool. Moreover, translations from SBVR to SWRL language are presented in order to fill the gap in the expressive power of SBVR and OWL. The theoretical expressions of patterns are illustrated by means of an example depicting the core structure of a fictitious company.

A common approach to represent semantics on Semantic Web area is to use an ontology. However, there is an emerging approach that combines an ontology with its context definition. So, the misunderstanding can be avoided if the context is explicitly defined. The resulting structure is called contextual ontology. To process a contextual ontology at run time, it has to be expressed in a machine processable language. However, for the analysis and design phase of a Web domain, a more appropriate ontology modeling language is needed. To this aim, this chapter presents a metamodel for modeling explicit and formal contextual ontologies that assists Web domain designers in modeling contextual ontologies. Furthermore, the relationship between XML specifications and ontologies in order to add formal and explicit semantics to Web domain designs is analyzed.

This paper presents an ontology-based conceptual mapping framework that translates a formal and visually rich business process modeling (BPM) language, Fundamental Business Process Modelling Language (FBPML) to a Semantic Web-based language, the Web Services Ontology (OWL-S). The translation aims to narrow the gap between Enterprise Modelling methods and Semantic Web services, thus bringing the two communities closer. Another significant contribution of the translation is that it allows more mature technologies such as BPM methods to be utilised within emerging fields that are constantly evolving, such as the Semantic Web. The framework is divided into a data model translation and a process model translation. An implementation and an evaluation of the process model translation are demonstrated and discussed.

Due to their powerful knowledge representation formalism and associated inference mechanisms, ontology-based approaches have been increasingly adopted to formally represent domain knowledge. We propose the use of ontologies to advance knowledge-sharing on underutilized crops and propose how to integrate those ontologies with rules for added expressiveness. We first present a survey on the use of ontologies in the field of life-sciences with emphasis on crop-related ontologies, and justify why we need a new formalism. We then present the UC-ONTO (an Underutilized Crops Ontology) as a case study showing the integration of OWL (Web Ontology Language) ontologies with Semantic Web Rule Language (SWRL) rules for added expressiveness.

Geospatial ontologies have a key role to play in the development of the geospatial-Semantic Web, with regard to facilitating the search for geographical information and resources. They normally hold large volumes of geographic information and undergo a continuous process of revision and update. Limitations of the OWL ontology representation language for supporting geospatial domains are discussed and an integrated rule and ontology language is recognized as needed to support the representation and reasoning requirements in this domain. A survey of the current approaches to integrating ontologies and rules is presented and a new framework is proposed that is based on and extends Description Logic Programs. A hybrid representational approach is adopted where the logical component of the framework is used to represent geographical concepts and spatial rules and an external computational geometry processor is used for storing and manipulating the associated geometric data. A sample application is used to demonstrate the proposed language and engine and how they address the identified challenges.

Geospatial ontologies have a key role to play in the development of the geospatial-Semantic Web, with regard to facilitating the search for geographical information and resources. They normally hold large volumes of geographic information and undergo a continuous process of revision and update. Limitations of the OWL ontology representation language for supporting geospatial domains are discussed and an integrated rule and ontology language is recognized as needed to support the representation and reasoning requirements in this domain. A survey of the current approaches to integrating ontologies and rules is presented and a new framework is proposed that is based on and extends Description Logic Programs. A hybrid representational approach is adopted where the logical component of the framework is used to represent geographical concepts and spatial rules and an external computational geometry processor is used for storing and manipulating the associated geometric data. A sample application is used to demonstrate the proposed language and engine and how they address the identified challenges.

Development of agent systems is without question a complex task when autonomous, reactive and proactive characteristics of agents are considered. Furthermore, internal agent behavior model and interaction within the agent organizations become even more complex and hard to implement when new requirements and interactions for new agent environments such as the Semantic Web are taken into account. We believe that the use of both domain specific modeling and a Domain-specific Modeling Language (DSML) may provide the required abstraction and support a more fruitful methodology for the development of Multi-agent Systems (MASs) especially when they are working on the Semantic Web environment. Although syntax definition based on a metamodel is an essential part of a modeling language, an additional and required part would be the determination and implementation of DSML constraints that constitute the (formal) semantics which cannot be defined solely with a metamodel. Hence, in this paper, f...

Semantic Web services integrate the meaningful content of the Semantic Web with the business logic of Web services and thus enable industries and individuals to access these services. But as the number of available Web services increase, there is a growing demand for a mechanism for effective retrieval of required services. We propose an improved Semantic Web service discovery method for finding OWLS (Web Ontology Language for Services) services by combining functional similarity matching (using bipartite graph) and textual similarity matching. However, discovering relevant Semantic Web service is a heavyweight task. Performance of service discovery is significantly reduced when the number of services increases. To overcome this issue, a lightweight filtering stage is also introduced before the discovery mechanism. Filtering is performed by semantic-based SPARQL (Simple Protocol and RDF Query Language) query. It will significantly reduce the input for the discovery process. Thus the search space and the time required to find the relevant services will be reduced. The proposed techniques are applied to a sample test collection and experimental results are presented, which demonstrate the effectiveness of the idea.

This paper addresses a major weakness of current technologies for the Semantic Web, namely the lack of a principled means to represent and reason about uncertainty. This not only hinders the realization of the original vision for the Semantic Web, but also creates a barrier to the development of new, powerful features for general knowledge applications that require proper treatment of uncertain phenomena. We propose to extend OWL, the ontology language recommended by the World Wide Web Consortium (W3C), to provide the ability to express probabilistic knowledge. The new language, PR-OWL, will allow legacy ontologies to interoperate with newly developed probabilistic ontologies. PR-OWL will move beyond the current limitations of deterministic classical logic to a full first-order probabilistic logic. By providing a principled means of modeling uncertainty in ontologies, PR-OWL will serve as a supporting tool for many applications that can benefit from probabilistic inference within an ontology language, thus representing an important step toward the W3C's vision for the Semantic Web. Uncertainty is ubiquitous. If the Semantic Web vision [1] is to be realized, a sound and principled means of representing and reasoning with uncertainty will be required. Existing Semantic Web technologies lack this capability. Our broad objective is to address this shortcoming by developing a Bayesian framework for probabilistic ontologies and plausible reasoning services. As an initial step toward our objective, we introduce PR-OWL, a probabilistic extension to the Web ontology language OWL. Although our research is focused in the Semantic Web, we are tackling a problem that long predates the WWW: the quest for more efficient data exchange. Clearly, solving that problem requires precise semantics and flexible ways to convey information. While the WWW provides a new presentation medium, and technologies such as XML present new data exchange formats, neither addresses the semantics of data

In this paper, we propose a method of detecting and classifying web application attacks. In contrast to current signature-based security methods, our solution is an ontology based technique. It specifies web application attacks by using semantic rules, the context of consequence and the specifications of application protocols. The system is capable of detecting sophisticated attacks effectively and efficiently by analyzing the specified portion of a user request where attacks are possible. Semantic rules help to capture the context of the application, possible attacks and the protocol that was used. These rules also allow inference to run over the ontological models in order to detect, the often complex polymorphic variations of web application attacks. The ontological model was developed using Description Logic that was based on the Web Ontology Language (OWL). The inference rules are Horn Logic statements and are implemented using the Apache JENA framework. The system is therefore platform and technology independent. Prior to the evaluation of the system the knowledge model was validated by using Ont-oClean to remove inconsistency, incompleteness and redundancy in the specification of ontological concepts. The experimental results show that the detection capability and performance of our system is significantly better than existing state of the art solutions. The system successfully detects web application attacks whilst generating few false positives. The examples that are presented demonstrate that a semantic approach can be used to effectively detect zero day and more sophisticated attacks in a real-world environment.

Su-Field analysis, as one of the inventive problem solving tools, can be used to analyse and improve the efficacy of the technical system. Generally, the process of using Su-Field model to solve a specific inventive problem includes: building a Problem Model, mapping to a Generic Problem Model, finding a Generic Solution Model based on the corresponding inventive standard, and finally establishing and instantiating a Solution Model. As one of the most important phases of Su-Field analysis, the last step is normally implemented manually with the help of physical effects, which link generic technical functions with specific applications and systems. The physical effects compatible with the context of the specific problem should be chosen to assist the users to instantiate the Solution Model. However, the physical effects and the specific problems are built at different levels of abstraction, and it is difficult for the users to choose, that is, given a certain function, too many physical effects are chosen while with the detailed context of the problem, no physical effect is returned. This paper firstly proposes a new way of representing physical effects using the change of two states, that is, the couple of two states before and after applying physical effects. Then, the knowledge about using physical effects is formalized in OWL (Ontology Web Language)-an ontology language for semantic web, and the constraint knowledge, such as the condition to use each kind of physical effect, is formalized in SWRL (Semantic Web Rule Language)-a rule language. Finally, the reasoning process of using physical effects is performed with the support of JESS (Java Expert System Shell) rule engine.

Probabilistic OWL (PR-OWL) improves the Web Ontology Language (OWL) with the ability to treat uncertainty using Multi-Entity Bayesian Networks (MEBN). PROWL 2 presents a better integration with OWL and its underlying logic, allowing the creation of ontologies with probabilistic and deterministic parts. However, there are scalability problems since PROWL 2 is built upon OWL 2 DL which is a version of OWL based on description logic SROIQ(D) and with high complexity. To address this issue, this paper proposes PROWL 2 RL, a scalable version of PROWL based on OWL 2 RL profile and triplestores (databases based on RDF triples). OWL 2 RL allows reasoning in polynomial time for the main reasoning tasks. This paper also presents First-Order expressions accepted by this new language and analyzes its expressive power. A comparison with the previous language presents which kinds of problems are more suitable for each version of PROWL .

An abstract architecture for semantic web services is requisite to present a conceptual model to assist in the principled design and implementation of semantic web service applications. The architectural structure we portray stands on the shoulders of two promising technical conceptions: Web Services and the Semantic Web. Automatic discovery is acknowledged as a key task and semantic description is the foundation for automatic service discovery. We portray a novel approach for automatic discovery of semantic Web services which utilize LDA to match a user request, articulated in service discovery language, with a semantic Web service description. Our approach to semantic based web service discovery entails semantic-based service categorization and semantic enhancement of the service request. We intend a solution for accomplishing functional level service categorization based on an ontology framework. Furthermore, we exploit clustering for precisely categorizing the web services based...