Showing papers on "Semantic Web published in 2009"

Linked Data - the story so far

Abstract: The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

BioPortal: ontologies and integrated data resources at the click of a mouse

Abstract: Biomedical ontologies provide essential domain knowledge to drive data integration, information retrieval, data annotation, natural-language processing and decision support. BioPortal (http://bioportal.bioontology.org) is an open repository of biomedical ontologies that provides access via Web services and Web browsers to ontologies developed in OWL, RDF, OBO format and Protege frames. BioPortal functionality includes the ability to browse, search and visualize ontologies. The Web interface also facilitates community-based participation in the evaluation and evolution of ontology content by providing features to add notes to ontology terms, mappings between terms and ontology reviews based on criteria such as usability, domain coverage, quality of content, and documentation and support. BioPortal also enables integrated search of biomedical data resources such as the Gene Expression Omnibus (GEO), ClinicalTrials.gov, and ArrayExpress, through the annotation and indexing of these resources with ontologies in BioPortal. Thus, BioPortal not only provides investigators, clinicians, and developers ‘one-stop shopping’ to programmatically access biomedical ontologies, but also provides support to integrate data from a variety of biomedical resources.

SKOS Simple Knowledge Organization System Reference

Abstract: This document defines the Simple Knowledge Organization System (SKOS), a common data model for sharing and linking knowledge organization systems via the Web.Many knowledge organization systems, such as thesauri, taxonomies, classification schemes and subject heading systems, share a similar structure, and are used in similar applications. SKOS captures much of this similarity and makes it explicit, to enable data and technology sharing across diverse applications.The SKOS data model provides a standard, low-cost migration path for porting existing knowledge organization systems to the Semantic Web. SKOS also provides a lightweight, intuitive language for developing and sharing new knowledge organization systems. It may be used on its own, or in combination with formal knowledge representation languages such as the Web Ontology language (OWL).This document is the normative specification of the Simple Knowledge Organization System. It is intended for readers who are involved in the design and implementation of information systems, and who already have a good understanding of Semantic Web technology, especially RDF and OWL.For an informative guide to using SKOS, see the [SKOS-PRIMER].

Foundations of Semantic Web Technologies

Abstract: With more substantial funding from research organizations and industry, numerous large-scale applications, and recently developed technologies, the Semantic Web is quickly emerging as a well-recognized and important area of computer science. While Semantic Web technologies are still rapidly evolving, Foundations of Semantic Web Technologies focuses on the established foundations in this area that have become relatively stable over time. It thoroughly covers basic introductions and intuitions, technical details, and formal foundations.The book concentrates on Semantic Web technologies standardized by the World Wide Web Consortium: RDF and SPARQL enable data exchange and querying, RDFS and OWL provide expressive ontology modeling, and RIF supports rule-based modeling. The text also describes methods for specifying, querying, and reasoning with ontological information. In addition, it explores topics that are clearly beyond foundations, such as tools, applications, and engineering aspects.Written by highly respected researchers with a deep understanding of the material, this text centers on the formal specifications of the subject and supplies many pointers that are useful for employing Semantic Web technologies in practice.Updates, errata, slides for teaching, and links to further resources are available at http://semantic-web-book.org/

Resource Description Framework

Abstract: This chapter introduces Resource Description Framework (RDF), the W3C recommendation for semantic annotations in the Semantic Web It will cover the syntax and semantics of RDF, as well as its relation with the W3C OWL Web Ontology Language To address the mismatch between RDF and OWL-DL, the most expressive decidable fragment of the OWL standard, we introduce a novel variant of RDF(S), called RDFS-FA, which provides a solid semantic foundation for many of the latest Description Logic-based SW ontology languages, such as OWL-DL and OWL2-DL

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.

Silk - A Link Discovery Framework for the Web of Data

Abstract: Web of Data is built upon two simple ideas: Employ the RDF data model to publish structured data on the Web and to set explicit RDF links between entities within different data sources. This paper presents the Silk - Link Discovery Framework, a tool for finding relationships between entities within different data sources. Data publishers can use Silk to set RDF links from their data sources to other data sources on the Web. Silk features a declarative language for specifying which types of RDF links should be discovered between data sources as well as which conditions entities must fulfill in order to be interlinked. Link conditions may be based on various similarity metrics and can take the graph around entities into account, which is addressed using a path-based selector language. Silk accesses data sources over the SPARQL protocol and can thus be used without having to replicate datasets locally.

Description Logics

Abstract: Description Logics (DLs) are a well-investigated family of logic-based knowledge representation formalisms, which can be used to represent the conceptual knowledge of an application domain in a structured and formally well-understood way. They are employed in various application domains, such as natural language processing, configuration, and databases, but their most notable success so far is the adoption of the DL-based language OWL as standard ontology language for the semantic web. This article concentrates on the problem of designing reasoning procedures for DLs. After a short introduction and a brief overview of the research in this area of the last 20 years, it will on the one hand present approaches for reasoning in expressive DLs, which are the foundation for reasoning in the Web ontology language OWL DL. On the other hand, it will consider tractable reasoning in the more light-weight DL $\mathcal{EL}$, which is employed in bio-medical ontologies, and which is the foundation for the OWL 2 profile OWL 2 EL.

Trust Management for Semantic Web

Abstract: The contemporary Web is heading towards its next stage of evolution From a clump of unorganized information spaces, the Web is becoming more focused on the meaning of information that is a Semantic Web Trust is an integral component in semantic web, allowing people to act under uncertainty and with the risk of negative consequences In this paper we discussed trust management and its connection to the semantic web We first discussed aspects of semantic web and trust management including defining trust and describing trust negotiations and then relationship of them After that we explored how mechanisms of XML access control are used to protect the confidentiality, integrity and availability of ontologies in trust management

SW-Store: a vertically partitioned DBMS for Semantic Web data management

Abstract: Efficient management of RDF data is an important prerequisite for realizing the Semantic Web vision. Performance and scalability issues are becoming increasingly pressing as Semantic Web technology is applied to real-world applications. In this paper, we examine the reasons why current data management solutions for RDF data scale poorly, and explore the fundamental scalability limitations of these approaches. We review the state of the art for improving performance of RDF databases and consider a recent suggestion, "property tables". We then discuss practically and empirically why this solution has undesirable features. As an improvement, we propose an alternative solution: vertically partitioning the RDF data. We compare the performance of vertical partitioning with prior art on queries generated by a Web-based RDF browser over a large-scale (more than 50 million triples) catalog of library data. Our results show that a vertically partitioned schema achieves similar performance to the property table technique while being much simpler to design. Further, if a column-oriented DBMS (a database architected specially for the vertically partitioned case) is used instead of a row-oriented DBMS, another order of magnitude performance improvement is observed, with query times dropping from minutes to several seconds. Encouraged by these results, we describe the architecture of SW-Store, a new DBMS we are actively building that implements these techniques to achieve high performance RDF data management.

World Wide Web Consortium (W3C)

Abstract: The World Wide Web Consortium (W3C) is the organization that leads the development of standards for the Web. Sir Tim Berners-Lee, the founder and current director of the W3C, envisions a linked network of information resources that guides Web standards development and points the way towards the creation of a Semantic Web. This entry describes the pioneering role of Berners-Lee in the development of the Web, the accomplishments and vision of the W3C, and the development of the Semantic Web

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.

Discovering and Maintaining Links on the Web of Data

Abstract: The Web of Data is built upon two simple ideas: Employ the RDF data model to publish structured data on the Web and to create explicit data links between entities within different data sources. This paper presents the Silk --- Linking Framework, a toolkit for discovering and maintaining data links between Web data sources. Silk consists of three components: 1. A link discovery engine, which computes links between data sources based on a declarative specification of the conditions that entities must fulfill in order to be interlinked; 2. A tool for evaluating the generated data links in order to fine-tune the linking specification; 3. A protocol for maintaining data links between continuously changing data sources. The protocol allows data sources to exchange both linksets as well as detailed change information and enables continuous link recomputation. The interplay of all the components is demonstrated within a life science use case.

The Semantic Web - ISWC 2009

Abstract: Research Track.- Queries to Hybrid MKNF Knowledge Bases through Oracular Tabling.- Automatically Constructing Semantic Web Services from Online Sources.- Exploiting User Feedback to Improve Semantic Web Service Discovery.- A Generic Approach for Large-Scale Ontological Reasoning in the Presence of Access Restrictions to the Ontology's Axioms.- OntoCase-Automatic Ontology Enrichment Based on Ontology Design Patterns.- Graph-Based Ontology Construction from Heterogenous Evidences.- DOGMA: A Disk-Oriented Graph Matching Algorithm for RDF Databases.- Semantically-Aided Business Process Modeling.- Task Oriented Evaluation of Module Extraction Techniques.- A Decomposition-Based Approach to Optimizing Conjunctive Query Answering in OWL DL.- Goal-Directed Module Extraction for Explaining OWL DL Entailments.- Analysis of a Real Online Social Network Using Semantic Web Frameworks.- Coloring RDF Triples to Capture Provenance.- TripleRank: Ranking Semantic Web Data by Tensor Decomposition.- What Four Million Mappings Can Tell You about Two Hundred Ontologies.- Modeling and Query Patterns for Process Retrieval in OWL.- Context and Domain Knowledge Enhanced Entity Spotting in Informal Text.- Using Naming Authority to Rank Data and Ontologies for Web Search.- Executing SPARQL Queries over the Web of Linked Data.- Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes.- Decidable Order-Sorted Logic Programming for Ontologies and Rules with Argument Restructuring.- Semantic Web Service Composition in Social Environments.- XLWrap - Querying and Integrating Arbitrary Spreadsheets with SPARQL.- Optimizing QoS-Aware Semantic Web Service Composition.- Synthesizing Semantic Web Service Compositions with jMosel and Golog.- A Practical Approach for Scalable Conjunctive Query Answering on Acyclic Knowledge Base.- Learning Semantic Query Suggestions.- Investigating the Semantic Gap through Query Log Analysis.- Towards Lightweight and Robust Large Scale Emergent Knowledge Processing.- On Detecting High-Level Changes in RDF/S KBs.- Efficient Query Answering for OWL 2.- Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data.- A Conflict-Based Operator for Mapping Revision.- Functions over RDF Language Elements.- Policy-Aware Content Reuse on the Web.- Exploiting Partial Information in Taxonomy Construction.- Actively Learning Ontology Matching via User Interaction.- Optimizing Web Service Composition While Enforcing Regulations.- A Weighted Approach to Partial Matching for Mobile Reasoning.- Scalable Distributed Reasoning Using MapReduce.- Discovering and Maintaining Links on the Web of Data.- Concept and Role Forgetting in Ontologies.- Parallel Materialization of the Finite RDFS Closure for Hundreds of Millions of Triples.- Semantic Web In Use.- Live Social Semantics.- RAPID: Enabling Scalable Ad-Hoc Analytics on the Semantic Web.- LinkedGeoData: Adding a Spatial Dimension to the Web of Data.- Enrichment and Ranking of the YouTube Tag Space and Integration with the Linked Data Cloud.- Produce and Consume Linked Data with Drupal!.- Extracting Enterprise Vocabularies Using Linked Open Data.- Reasoning about Resources and Hierarchical Tasks Using OWL and SWRL.- Using Hybrid Search and Query for E-discovery Identification.- Bridging the Gap between Linked Data and the Semantic Desktop.- Vocabulary Matching for Book Indexing Suggestion in Linked Libraries - A Prototype Implementation and Evaluation.- Semantic Web Technologies for the Integration of Learning Tools and Context-Aware Educational Services.- Semantic Enhancement for Enterprise Data Management.- Lifting Events in RDF from Interactions with Annotated Web Pages.- A Case Study in Integrating Multiple E-commerce Standards via Semantic Web Technology.- Supporting Multi-view User Ontology to Understand Company Value Chains.- Doctoral Consortium.- EXPRESS: EXPressing REstful Semantic Services Using Domain Ontologies.- A Lexical-Ontological Resource for Consumer Heathcare.- Semantic Web for Search.- Towards Agile Ontology Maintenance.- Ontologies for User Interface Integration.- Semantic Usage Policies for Web Services.- Ontology-Driven Generalization of Cartographic Representations by Aggregation and Dimensional Collapse.- Invited Talks.- Populating the Semantic Web by Macro-reading Internet Text.- Search 3.0: Present, Personal, Precise.

Evaluating similarity measures for emergent semantics of social tagging

Abstract: Social bookmarking systems are becoming increasingly important data sources for bootstrapping and maintaining Semantic Web applications. Their emergent information structures have become known as folksonomies. A key question for harvesting semantics from these systems is how to extend and adapt traditional notions of similarity to folksonomies, and which measures are best suited for applications such as community detection, navigation support, semantic search, user profiling and ontology learning. Here we build an evaluation framework to compare various general folksonomy-based similarity measures, which are derived from several established information-theoretic, statistical, and practical measures. Our framework deals generally and symmetrically with users, tags, and resources. For evaluation purposes we focus on similarity between tags and between resources and consider different methods to aggregate annotations across users. After comparing the ability of several tag similarity measures to predict user-created tag relations, we provide an external grounding by user-validated semantic proxies based on WordNet and the Open Directory Project. We also investigate the issue of scalability. We find that mutual information with distributional micro-aggregation across users yields the highest accuracy, but is not scalable; per-user projection with collaborative aggregation provides the best scalable approach via incremental computations. The results are consistent across resource and tag similarity.

Triplify: light-weight linked data publication from relational databases

Abstract: In this paper we present Triplify - a simplistic but effective approach to publish Linked Data from relational databases. Triplify is based on mapping HTTP-URI requests onto relational database queries. Triplify transforms the resulting relations into RDF statements and publishes the data on the Web in various RDF serializations, in particular as Linked Data. The rationale for developing Triplify is that the largest part of information on the Web is already stored in structured form, often as data contained in relational databases, but usually published by Web applications only as HTML mixing structure, layout and content. In order to reveal the pure structured information behind the current Web, we have implemented Triplify as a light-weight software component, which can be easily integrated into and deployed by the numerous, widely installed Web applications. Our approach includes a method for publishing update logs to enable incremental crawling of linked data sources. Triplify is complemented by a library of configurations for common relational schemata and a REST-enabled data source registry. Triplify configurations containing mappings are provided for many popular Web applications, including osCommerce, WordPress, Drupal, Gallery, and phpBB. We will show that despite its light-weight architecture Triplify is usable to publish very large datasets, such as 160GB of geo data from the OpenStreetMap project.

Media Meets Semantic Web --- How the BBC Uses DBpedia and Linked Data to Make Connections

Abstract: In this paper, we describe how the BBC is working to integrate data and linking documents across BBC domains by using Semantic Web technology, in particular Linked Data, MusicBrainz and DBpedia. We cover the work of BBC Programmes and BBC Music building Linked Data sites for all music and programmes related brands, and we describe existing projects, ongoing development, and further research we are doing in a joint collaboration between the BBC, Freie Universitat Berlin and Rattle Research in order to use DBpedia as the controlled vocabulary and semantic backbone for the whole BBC.

The Emerging Web of Linked Data

Abstract: The paper discusses the semantic Web and Linked Data. The classic World Wide Web is built upon the idea of setting hyperlinks between Web documents. These hyperlinks are the basis for navigating and crawling the Web.Technologically, the core idea of Linked Data is to use HTTP URLs not only to identify Web documents, but also to identify arbitrary real world entities.Data about these entities is represented using the Resource Description Framework (RDF). Whenever a Web client resolves one of these URLs, the corresponding Web server provides an RDF/ XML or RDFa description of the identified entity. These descriptions can contain links to entities described by other data sources.The Web of Linked Data can be seen as an additional layer that is tightly interwoven with the classic document Web. The author mentions the application of Linked Data in media, publications, life sciences, geographic data, user-generated content, and cross-domain data sources. The paper concludes by stating that the Web has succeeded as a single global information space that has dramatically changed the way we use information, disrupted business models, and led to profound societal change.

TripleRank: Ranking Semantic Web Data by Tensor Decomposition

Abstract: The Semantic Web fosters novel applications targeting a more efficient and satisfying exploitation of the data available on the web, e.g. faceted browsing of linked open data. Large amounts and high diversity of knowledge in the Semantic Web pose the challenging question of appropriate relevance ranking for producing fine-grained and rich descriptions of the available data, e.g. to guide the user along most promising knowledge aspects. Existing methods for graph-based authority ranking lack support for fine-grained latent coherence between resources and predicates (i.e. support for link semantics in the linked data model). In this paper, we present TripleRank, a novel approach for faceted authority ranking in the context of RDF knowledge bases. TripleRank captures the additional latent semantics of Semantic Web data by means of statistical methods in order to produce richer descriptions of the available data. We model the Semantic Web by a 3-dimensional tensor that enables the seamless representation of arbitrary semantic links. For the analysis of that model, we apply the PARAFAC decomposition, which can be seen as a multi-modal counterpart to Web authority ranking with HITS. The result are groupings of resources and predicates that characterize their authority and navigational (hub) properties with respect to identified topics. We have applied TripleRank to multiple data sets from the linked open data community and gathered encouraging feedback in a user evaluation where TripleRank results have been exploited in a faceted browsing scenario.

Model Driven Engineering and Ontology Development

Abstract: Defining a formal domain ontology is generally considered a useful, not to say necessary step in almost every software project. This is because software deals with ideas rather than with self-evident physical artefacts. However, this development step is hardly ever done, as ontologies rely on well-defined and semantically powerful AI concepts such as description logics or rule-based systems, and most software engineers are largely unfamiliar with these. Gaevic and his co-authors try to fill this gap by covering the subject of MDA application for ontology development on the Semantic Web. Part I of their book describes existing technologies, tools, and standards like XML, RDF, OWL, MDA, and UML. Part II presents the first detailed description of OMGs new ODM (Ontology Definition Metamodel) initiative, a specification which is expected to be in the form of an OMG language like UML. Finally, Part III is dedicated to applications and practical aspects of developing ontologies using MDA-based languages. The book is supported by a website showing many ontologies, UML and other MDA-based models, and the transformations between them. "The book is equally suited to those who merely want to be informed of the relevant technological landscape, to practitioners dealing with concrete problems, and to researchers seeking pointers to potentially fruitful areas of research. The writing is technical yet clear and accessible, illustrated throughout with useful and easily digestible examples." from the Foreword by Bran Selic, IBM Rational Software, Canada. "I do not know another book that offers such a high quality insight into UML and ontologies." Steffen Staab, U Koblenz, Germany

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.

Semantic Web Programming

Abstract: The next major advance in the Web?Web 3.0?will be built on semantic Web technologies, which will allow data to be shared and reused across application, enterprise, and community boundaries. Written by a team of highly experienced Web developers, this book explains examines how this powerful new technology can unify and fully leverage the ever-growing data, information, and services that are available on the Internet. Helpful examples demonstrate how to use the semantic Web to solve practical, real-world problems while you take a look at the set of design principles, collaborative working groups, and technologies that form the semantic Web. The companion Web site features full code, as well as a reference section, a FAQ section, a discussion forum, and a semantic blog.

SemSOS: Semantic sensor Observation Service

Abstract: Sensor Observation Service (SOS) is a Web service specification defined by the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) group in order to standardize the way sensors and sensor data are discovered and accessed on the Web. This standard goes a long way in providing interoperability between repositories of heterogeneous sensor data and applications that use this data. Many of these applications, however, are ill equipped at handling raw sensor data as provided by SOS and require actionable knowledge of the environment in order to be practically useful. There are two approaches to deal with this obstacle, make the applications smarter or make the data smarter. We propose the latter option and accomplish this by leveraging semantic technologies in order to provide and apply more meaningful representation of sensor data. More specifically, we are modeling the domain of sensors and sensor observations in a suite of ontologies, adding semantic annotations to the sensor data, using the ontology models to reason over sensor observations, and extending an open source SOS implementation with our semantic knowledge base. This semantically enabled SOS, or SemSOS, provides the ability to query high-level knowledge of the environment as well as low-level raw sensor data.

Ontology based personalized route planning system using a multi-criteria decision making approach

Abstract: This study presents a generic ontology-based architecture using a multi-criteria decision making technique to design a personalized route planning system. The real world has become too complex to implement entirely within an information system such as geographic information system (GIS). A route planning technique is an essential geo-related decision support tool, especially in intelligent transportation systems (ITS). In ubiquitous GIS environments, personalization can be accomplished through a user's preferences stored on mobile appliances. In this manner, personalized and user-centric route planning services using semantic technologies and ontologies perceive user and context models to satisfy user demands and predict their requirements. In the past few years, several studies have been carried out regarding personalized services. However, the existing route finding algorithms suffer from a number of major difficulties, mainly owing to insufficient criteria modeling for a personalized system. Thus, the present study investigates how a user-centric route planning system can be implemented. In order to address this research issue, an ontology-based knowledge modelling technique using an analytic hierarchical process (AHP) is proposed. This technique can facilitate determination of the choice of criteria used for applying an impedance function in the route finding algorithm. From another perspective, AHP explicitly deals with a hierarchy structure and is essentially a theory of measurement and decision making methodology used for combining or synthesizing quantitative as well as qualitative criteria. User-centric results on real data illustrate the strengths of the present approach. It is anticipated that this new technique can be applied to develop new graph algorithms based on semantic web technology and can be used with new semantic graph structures.

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.

Reusing ontologies on the Semantic Web: A feasibility study

Abstract: Technologies for the efficient and effective reuse of ontological knowledge are one of the key success factors for the Semantic Web. Putting aside matters of cost or quality, being reusable is an intrinsic property of ontologies, originally conceived of as a means to enable and enhance the interoperability between computing applications. This article gives an account, based on empirical evidence and real-world findings, of the methodologies, methods and tools currently used to perform ontology-reuse processes. We study the most prominent case studies on ontology reuse, published in the knowledge-/ontology-engineering literature from the early nineties. This overview is complemented by two self-conducted case studies in the areas of eHealth and eRecruitment in which we developed Semantic Web ontologies for different scopes and purposes by resorting to existing ontological knowledge on the Web. Based on the analysis of the case studies, we are able to identify a series of research and development challenges which should be addressed to ensure reuse becomes a feasible alternative to other ontology-engineering strategies such as development from scratch. In particular, we emphasize the need for a context- and task-sensitive treatment of ontologies, both from an engineering and a usage perspective, and identify the typical phases of reuse processes which could profit considerably from such an approach. Further on, we argue for the need for ontology-reuse methodologies which optimally exploit human and computational intelligence to effectively operationalize reuse processes.

A semantic web based framework for social network access control

Abstract: The existence of on-line social networks that include person specific information creates interesting opportunities for various applications ranging from marketing to community organization. On the other hand, security and privacy concerns need to be addressed for creating such applications. Improving social network access control systems appears as the first step toward addressing the existing security and privacy concerns related to on-line social networks. To address some of the current limitations, we propose an extensible fine grained access control model based on semantic web tools. In addition, we propose authorization, admin and filtering policies that depend on trust relationships among various users, and are modeled using OWL and SWRL. Besides describing the model, we present the architecture of the framework in its support.