Showing papers on "Semantic Web Rule Language published in 2009"

Resource Description Framework (RDF)

Abstract: The Resource Description Framework (RDF) is the standard knowledge representation language for the Semantic Web, an evolution of the World Wide Web that aims to provide a well-founded infrastructure for publishing, sharing and querying structured data. This article provides an introduction to RDF and its related vocabulary definition language RDF Schema, and explains its relationship with the OWL Web Ontology Language. Finally, it provides an overview of the historical development of RDF and related languages for Web metadata.

OWL 2 Web Ontology Language: Profiles

Abstract: The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, OWL 2 Web Ontology LanguageProfiles W3C Working Draft 21 April 2009 Page 1 of 53 http://www.w3.org/TR/2009/WD-owl2-profiles-20090421/ and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. This document provides a specification of several profiles of OWL 2 which can be more simply and/or efficiently implemented. In logic, profiles are often called fragments. Most profiles are defined by placing restrictions on the structure of OWL 2 ontologies. These restrictions have been specified by modifying the productions of the functional-style syntax. Status of this Document

OWL 2 Web Ontology Language

Abstract: The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. The Manchester syntax is a user-friendly compact syntax for OWL 2 ontologies; it is frame-based, as opposed to the axiom-based other syntaxes for OWL 2. The Manchester Syntax is used in the OWL 2 Primer, and this document provides the language used there. It is expected that tools will extend the Manchester Syntax for their own purposes, and tool builders may collaboratively extend the common language.

Web ontology language: Owl

Abstract: In order to extend the limited expressiveness of RDF Schema, a more expressive Web Ontology Language (OWL) has been defined by the World Wide Web Consortium (W3C). In this chapter we analyse the limitations of RDF Schema and derive requirements for a richer Web Ontology Language. We then describe the three-layered architecture of the OWL language, and we describe all of the language constructs of OWL in some detail. The chapter concludes with two extensive examples of OWL ontologies.

SQWRL: a query language for OWL

Abstract: The ability to extract information from OWL ontologies is a basic requirement. While SPARQL and its extensions are being used as an OWL query language in many applications, their understanding of OWL's semantics is at best incomplete. There is a pressing need for a concise, readable, and semantically robust query language for OWL. We describe a query language called SQWRL that we believe provides such a language. SQWRL is based on the SWRL rule language and uses SWRL's strong semantic foundation as its formal underpinning. The resulting language provides a small but powerful array of operators that allows users to construct queries on OWL ontologies. SQWRL also contains novel set operators that can be used to perform closure operations to allow limited forms of negation as failure, counting, and aggregation.

The OWL API: a Java API for working with OWL 2 ontologies

Abstract: This paper presents the OWL API a high level Application Programming Interface (API) for working with OWL 2 ontologies. The API is closely aligned with the OWL 2 structural specification. It supports parsing and rendering in the syntaxes defined in the W3C specification, namely, the Functional Syntax, RDF/XML, OWL/XML and the Manchester OWL Syntax. Finally, the reference implementation of the API, which is written in Java, includes validators for the various OWL 2 profiles - OWL 2 QL, OWL 2 EL and OWL 2 RL.

Web 3.0 Emerging

Abstract: While Web 3.0 technologies are difficult to define precisely, the outline of emerging applications has become clear over the past year. We can thus essentially view Web 3.0 as semantic Web technologies integrated into, or powering, large-scale Web applications. The base of Web 3.0 applications resides in the resource description framework (RDF) for providing a means to link data from multiple Web sites or databases. With the SPARQL query language, a SQL-like standard for querying RDF data, applications can use native graph-based RDF stores and extract RDF data from traditional databases.

DL-Learner: Learning Concepts in Description Logics

Abstract: In this paper, we introduce DL-Learner, a framework for learning in description logics and OWL. OWL is the official W3C standard ontology language for the Semantic Web. Concepts in this language can be learned for constructing and maintaining OWL ontologies or for solving problems similar to those in Inductive Logic Programming. DL-Learner includes several learning algorithms, support for different OWL formats, reasoner interfaces, and learning problems. It is a cross-platform framework implemented in Java. The framework allows easy programmatic access and provides a command line interface, a graphical interface as well as a WSDL-based web service.

OWL 2 Web Ontology Language Direct Semantics

Abstract: The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. This document provides the direct model-theoretic semantics for OWL 2, which is compatible with the description logic SROIQ. Furthermore, this document defines the most common inference problems for OWL 2.

Rapid prototyping of semantic mash-ups through semantic web pipes

Abstract: The use of RDF data published on the Web for applications is still a cumbersome and resource-intensive task due to the limited software support and the lack of standard programming paradigms to deal with everyday problems such as combination of RDF data from dierent sources, object identifier consolidation, ontology alignment and mediation, or plain querying and filtering tasks. In this paper we present a framework, Semantic Web Pipes, that supports fast implementation of Semantic data mash-ups while preserving desirable properties such as abstraction, encapsulation, component-orientation, code re-usability and maintainability which are common and well supported in other application areas.

Programming the Semantic Web

Abstract: With this book, the promise of the Semantic Web -- in which machines can find, share, and combine data on the Web -- is not just a technical possibility, but a practical reality Programming the Semantic Web demonstrates several ways to implement semantic web applications, using current and emerging standards and technologies. You'll learn how to incorporate existing data sources into semantically aware applications and publish rich semantic data. Each chapter walks you through a single piece of semantic technology and explains how you can use it to solve real problems. Whether you're writing a simple mashup or maintaining a high-performance enterprise solution,Programming the Semantic Web provides a standard, flexible approach for integrating and future-proofing systems and data. This book will help you: Learn how the Semantic Web allows new and unexpected uses of data to emerge Understand how semantic technologies promote data portability with a simple, abstract model for knowledge representation Become familiar with semantic standards, such as the Resource Description Framework (RDF) and the Web Ontology Language (OWL) Make use of semantic programming techniques to both enrich and simplify current web applications

OWL 2 Web Ontology Language RDF-Based Semantics

Abstract: The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. This document defines the RDF-compatible model-theoretic semantics of OWL 2.

OWL 2 Web Ontology Language New Features and Rationale

Abstract: The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. This document is a simple introduction to the new features of the OWL 2 Web Ontology Language, including an explanation of the differences between the initial version of OWL and OWL 2. The document also presents the requirements that have motivated the design of the main new features, and their rationale from a theoretical and implementation perspective.

Language Models Based on Semantic Composition

Abstract: In this paper we propose a novel statistical language model to capture long-range semantic dependencies Specifically, we apply the concept of semantic composition to the problem of constructing predictive history representations for upcoming words We also examine the influence of the underlying semantic space on the composition task by comparing spatial semantic representations against topic-based ones The composition models yield reductions in perplexity when combined with a standard n-gram language model over the n-gram model alone We also obtain perplexity reductions when integrating our models with a structured language model

Ontology-based curriculum content sequencing system with semantic rules

Abstract: Curriculum content sequencing involves managing a learning route to help users achieve learning goals. A conventional learning route consists of ordered content and is primarily based on a single course material. In an e-learning system, amount of similar course contents are available. These contents are expected to mutually substitute for one another in creating flexible learning routes. Owing to inconsistency in materials editing and cataloging, composing contents based on multiple sources leads to sequencing complexity. Most significantly, most e-learning systems lack a sequencing mechanism for dominating content composition. This study utilizes a knowledge-intensive approach to create a general sequencing knowledge base. This approach includes two components: (1) ontology is used to represent abstract views of content sequencing and course materials and (2) added semantic rules are used to represent relationships between individuals. Following knowledge base creation, both practical curriculum sequences and course materials can be inserted as factual knowledge. A reliable knowledge base can be established using inference power. An example involving mathematics course in elementary school education is designed using Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL). Experimental lessons demonstrate that semantic rules in conjunction with ontologies not only solve sequencing problems but also achieve a durable knowledge base and a reliable system.

A Semantic Similarity Measure for Expressive Description Logics

Abstract: A totally semantic measure is presented which is able to calculate a similarity value between concept descriptions and also between concept description and individual or between individuals expressed in an expressive description logic. It is applicable on symbolic descriptions although it uses a numeric approach for the calculus. Considering that Description Logics stand as the theoretic framework for the ontological knowledge representation and reasoning, the proposed measure can be effectively used for agglomerative and divisional clustering task applied to the semantic web domain.

OWL 2 Web Ontology Language Mapping to RDF Graphs

Abstract: The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. This document defines the mapping of OWL 2 ontologies into RDF graphs, and vice versa.

Scalable Authoritative OWL Reasoning for the Web

Abstract: In this article the authors discuss the challenges of performing reasoning on large scale RDF datasets from the Web. Using ter-Horst’s pD* fragment of OWL as a base, the authors compose a rule-based framework for application to web data: they argue their decisions using observations of undesirable examples taken directly from the Web. The authors further temper their OWL fragment through consideration of “authoritative sources†which counter-acts an observed behaviour which they term “ontology hijacking†: new ontologies published on the Web re-defining the semantics of existing entities resident in other ontologies. They then present their system for performing rule-based forward-chaining reasoning which they call SAOR: Scalable Authoritative OWL Reasoner. Based upon observed characteristics of web data and reasoning in general, they design their system to scale: the system is based upon a separation of terminological data from assertional data and comprises of a lightweight in-memory index, on-disk sorts and file-scans. The authors evaluate their methods on a dataset in the order of a hundred million statements collected from real-world Web sources and present scale-up experiments on a dataset in the order of a billion statements collected from the Web.

Semantic rules for context-aware geographical information retrieval

Abstract: Geographical information retrieval (GIR) can benefit from context information to adapt the results to a user's current situation and personal preferences. In this respect, semantics-based GIR is especially challenging because context information - such as collected from sensors - is often provided through numeric values, which need to be mapped to ontological representations based on nominal symbols. The Web Ontology Language (OWL) lacks mathematical processing capabilities that require free variables, so that even basic comparisons and distance calculations are not possible. Therefore, the context information cannot be interpreted with respect to the task and the current user's preferences. In this paper, we introduce an approach based on semantic rules that adds these processing capabilities to OWL ontologies. The task of recommending personalized surf spots based on user location and preferences serves as a case study to evaluate the capabilities of semantic rules for context-aware geographical information retrieval. We demonstrate how the Semantic Web Rule Language (SWRL) can be utilized to model user preferences and how execution of the rules successfully retrieves surf spots that match these preferences. While SWRL itself enables free variables, mathematical functions are added via built-ins - external libraries that are dynamically loaded during rule execution. Utilizing the same mechanism, we demonstrate how SWRL built-ins can query the Semantic Sensor Web to enable the consideration of real-time measurements and thus make geographical information retrieval truly context-aware.

Semantic matchmaker with precondition and effect matching using SWRL

Abstract: Service oriented architectures provide more effective and dynamic applications. Using semantic Web Services in service oriented architectures improves interoperability and scalability. A very important aspect of using semantic Web Services is the matchmaking process. Semantic matchmaking is used during discovery and composition of semantic Web Services to find valuable service candidates. Among these candidates, best ones are chosen to build up the composition, or for substitution in the case of an execution failure. Our proposed matchmaker architecture performs semantic matching of Web Services on the basis of input and output descriptions of semantic Web Services as well as precondition and effect matching. We present a novel approach for assigning matchmaking scores to condition expressions in OWL-S documents written in SWRL during matchmaking.

Optimizing QoS-Aware Semantic Web Service Composition

Abstract: Ranking and optimization of web service compositions are some of the most interesting challenges at present. Since web services can be enhanced with formal semantic descriptions, forming the "semantic web services", it becomes conceivable to exploit the quality of semantic links between services (of any composition) as one of the optimization criteria. For this we propose to use the semantic similarities between output and input parameters of web services. Coupling this with other criteria such as quality of service (QoS) allow us to rank and optimize compositions achieving the same goal. Here we suggest an innovative and extensible optimization model designed to balance semantic fit (or functional quality) with non-functional QoS metrics. To allow the use of this model in the context of a large number of services as foreseen by the strategic EC-funded project SOA4All we propose and test the use of Genetic Algorithms.

Cross ontology query answering on the semantic web: an initial evaluation

Abstract: PowerAqua is a Question Answering system, which takes as input a natural language query and is able to return answers drawn from relevant semantic resources found anywhere on the Semantic Web. In this paper we provide two novel contributions: First, we detail a new component of the system, the Triple Similarity Service, which is able to match queries effectively to triples found in different ontologies on the Semantic Web. Second, we provide a first evaluation of the system, which in addition to providing data about PowerAqua's competence, also gives us important insights into the issues related to using the Semantic Web as the target answer set in Question Answering. In particular, we show that, despite the problems related to the noisy and incomplete conceptualizations, which can be found on the Semantic Web, good results can already be obtained.

An weighted ontology-based semantic similarity algorithm for web service

Abstract: A critical step in the process of reusing existing WSDL-specified services for building web-based applications is the discovery of potentially relevant services. However, the category-based service discovery, such as UDDI, is clearly insufficient. Semantic web services, augmenting web service descriptions using semantic web technology, were introduced to facilitate the publication, discovery, and execution of web services at the semantic level. Semantic matchmaker enhances the capability of UDDI service registries in the semantic web services architecture by applying some matching algorithms between advertisements and requests described in OWL-S to recognize various degrees of matching for web services. Based on semantic web service framework, semantic matchmaker and probabilistic matching approach, this paper proposes a weighted ontology-based semantic similarity algorithm for web service to support a more automated and veracious service discovery and rank process in the semantic web service framework.

An OWL Ontology for Fuzzy OWL 2

Abstract: The need to deal with vague information in Semantic Web languages is rising in importance and, thus, calls for a standard way to represent such information. We may address this issue by either extending current Semantic Web languages to cope with vagueness, or by providing an ontology describing how to represent such information within Semantic Web languages. In this work, we follow the latter approach and propose and discuss an OWL ontology to represent important features of fuzzy OWL 2 statements.

Efficient Linked-List RDF Indexing in Parliament

Abstract: As the number and scale of Semantic Web applications in use increases, so does the need to efficiently store and retrieve RDF data. Current published schemes for RDF data management either fail to embrace the schema flexibility inherent in RDF or make restrictive assumptions about application usage models. This paper describes a storage and indexing scheme based on linked lists and memory-mapped files, and presents theoretical and empirical analysis of its strengths and weaknesses versus other techniques. This scheme is currently used in Parliament (formerly DAML DB), a triple store with rule support that has recently been released as open source.

A syntax for rules in OWL 2

Abstract: Being able to extend an OWL ontology with some form of rules is a feature that many ontology developers consider as very important. Nevertheless, working with rules in practice can be difficult since the tool support is not as good as for handling standard ontologies. Furthermore, the existing rule syntaxes are not very well aligned with the new OWL 2 standard. We propose, therefore, an extension to OWL 2 for representing rules, which is directly inspired by (DL Safe) SWRL rules, but uses and extends the succinct and human-readable functional-style syntax of OWL 2. We also propose an OWL/XML version of the syntax for easy XML serialization. Support for parsing such rules has been added to the new OWL API 3.0 and reasoning support is available in the two OWL 2 reasoners Pellet and HermiT. In HermiT, these rules can also be used in conjunction with description graphs.