SEMANTIC WEB TECHNOLOGY

Software reuse is defined as the use of any artifact, or partthereof, created before, on a new Project. This practice has significant benefits in reducing costs and increasing quality and productivity in software development. Numerous approaches have been proposed aimed mostly at the source code reuse, but this type of reuse has its limitations because development platforms and technologies are constantly changing. Then, it is necessary to apply reuse over software artifacts created at higher levels of software life cycle such as requirements specification. This paper presents a tool for the reuse of use case diagrams by storing their information in OWL ontology and the use of Semantic Web technologies.

The number of applications designed around Linked Open Data (LOD) has expanded rapidly in recent years. However, these applications typically do not make use of the vast amounts of LOD datasets, but only provide access to predefined, domain-specific subsets. Exceptions that do allow for more flexible exploration of LOD are not targeted at end users, which excludes users who have limited experience with Semantic Web technologies from realizing the potential of the so-called LOD cloud. This paper introduces a Mashup Platform that models, manages , reuses, and interconnects LOD web applications, thereby encouraging initiative and creativity of potential users. Figuratively, our approach allows developers to implement building blocks whereas the platform provides the cement so that end users can build houses by themselves.

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.

Litteratus Calculus is a proposal to help Semantic Web enjoy the good properties which made the success of the original Web, i.e. natural language, navigation, simple search, freedom of formats, without sacrificing the structural and normative qualities of semantics. This poster outlines the underlying formalism of Litteratus Calculus, explains how it relates to Semantic Web standards, and describes some promising experiments. It is an invitation to a shared reflection on these points.

Topics in education are changing with an ever faster pace. Especially in the field of life-long learning the aspects that need to be taught by information providers must keep up to date with emerging topics. The courseware watchdog is a comprehensive module which allows users to focus on existing subfields of a discipline, but thereby be aware of important drifts and tendencies in the field.

Topics in education are changing with an ever faster pace. Especially in the field of life-long learning the aspects that need to be taught by information providers must keep up to date with emerging topics. The courseware watchdog is a comprehensive module which allows users to focus on existing subfields of a discipline, but thereby be aware of important drifts and tendencies in the field.

Topics in education are changing with an ever faster pace. E-Learning resources tend to be more and more decentralised. Users need increasingly to be able to use the resources of the web. For this, they should have tools for finding and organizing information in a decentral way. In this, paper, we show how an ontology-based tool suite allows to make

In the Linked Open Data cloud one of the largest data sets, comprising of 2.5 billion triples, is derived from the Life Science domain. Yet this represents a small fraction of the total number of publicly available data sources on the Web. We briefly describe past attempts to transform specific Life Science sources from a plethora of open as well as proprietary formats into RDF data. In particular, we identify and tackle two bottlenecks in current practice: Acquiring ontologies to formally describe these data and creating "RDFizer" programs to convert data from legacy formats into RDF. We propose an unsupervised method, based on transformation rules, for performing these two key tasks, which makes use of our previous work on unsupervised wrapper induction for extracting labelled data from complete Life Science Web sites. We apply our approach to 13 real-world online Life Science databases. The learned ontologies are evaluated by domain experts as well as against gold standard ontologies. Furthermore, we compare the learned ontologies against ontologies that are "lifted" directly from the underlying relational schema using an existing unsupervised approach. Finally, we apply our approach to three online databases to extract RDF data. Our results indicate that this approach can be used to bootstrap and speed up the migration of life science data into the Linked Open Data cloud.

Peer-to-Peer systems are a new paradigm for information sharing and some systems have successfully been deployed. It has been argued that current Peer-to-Peer systems suffer from the lack of semantics. The SWAP project (Semantic Web and Peer-to-Peer) aims at overcoming this problem by combining the Peer-to-Peer paradigm with Semantic Web technologies. In the course of our investigations it turned out that the nature of Peer-to-Peer systems requires some compromises with respect to the use of semantic knowledge models. In particular, the notion of ontology does not really apply as we often do not find a shared understanding of the domain. In this paper, we propose a data model for encoding semantic information that combines features of ontology (concept hierarchies, relational structures) with a flexible description and rating model that allows us to handle heterogeneous and even contradictory views on the domain of interest. We discuss the role of this model in the SWAP environment and describe the model as well as its creation and access.

Knowledge and information spanning multiple information sources, multiple media, multiple versions and multiple communities challenge the capabilities of existing knowledge and information management infrastructures by far -primarily in terms of intellectually exploiting the stored knowledge and information. In this paper we present some semantic web technologies of the EU integrated project X-Media that build bridges between the various information sources, the different media, the stations of knowledge management and the different communities. Core to this endeavour is the combination of information extraction with formal ontologies as well as with semantically lightweight folksonomies.

The Semantic Web is intended as a web of machine readable data where every data source can be the data provider for different kinds of applications. However, due to a lack of support it is still cumbersome to work with RDF data in modern, object-oriented programming languages, in particular if the data source is only available through a SPARQL endpoint without further documentation or published schema information. In this setting, it is desirable to have an integrated tool-chain that helps to understand the data source during development and supports the developer in the creation of persistent data objects. To tackle these issues, we introduce LITEQ, a paradigm for integrating RDF data sources into programming languages and strongly typing the data. Additionally, we report on two use cases and show that compared to existing approaches LITEQ performs competitively according to the Halstead metric.

Semantic Annotation is a basic technology for intelligent content and is beneficial in a wide range of contentoriented intelligent applications. In this paper we present our work in ontology-based semantic annotation, which is embedded in a scenario of a knowledge portal application. Starting with seemingly good and bad manual semantic annotation, we describe our experiences made within the KA -initiative. The experiences gave us the starting point for developing an ergonomic and knowledge base-supported annotation tool. Furthermore, the annotation tool described are currently extended with mechanisms for semi-automatic information-extraction based annotation. Supporting the evolving nature of semantic content we additionally describe our idea of evolving ontologies supporting semantic annotation.

Peer-to-Peer systems are a new paradigm for information sharing and some systems have successfully been deployed. It has been argued that current Peer-to-Peer systems suffer from the lack of semantics. The SWAP project (Semantic Web and Peer-to-Peer) aims at overcoming this problem by combining the Peer-to-Peer paradigm with Semantic Web technologies. In the course of our investigations it turned out that the nature of Peer-to-Peer systems requires some compromises with respect to the use of semantic knowledge models. In particular, the notion of ontology does not really apply as we often do not find a shared understanding of the domain. In this paper, we propose a data model for encoding semantic information that combines features of ontology (concept hierarchies, relational structures) with a flexible description and rating model that allows us to handle heterogeneous and even contradictory views on the domain of interest. We discuss the role of this model in the SWAP environment and describe the model as well as its creation and access.

The Semantic Web Service Challenge is one of the major initiative dedicated to work on Semantic Web Service (SWS) discovery and selection. It represents an effective manner for evaluating the functionality of SWS technologies. In this paper, we provide a new SWS-Challenge scenario proposal with new interesting problems to be solved on the basis of an analysis of a real world shipment scenario in the logistic operators domain. In the discussion a number of aspects concerning the discovery and selection processes are emphasized. In particular, we focus on the problem of considering the heterogeneity between the provider and the requester perspectives, and on the differences between functional and non functional specifications both on the requester and provider side.

Abstract. Many Web applications have offered personalization and adaptation as their features in order to provide personalized services to their users. The user profiles are gathered independently by these applications often through an explicit dialogue with the user. As a result, the users have to go through a similar elicitation process multiple times, that is, providing similar information that is used to build the user profiles to different applications. In the springtime of mashup applications, we observe the importance of ...

This article presents the semantic portal MUSEUMFINLAND for publishing heterogeneous museum collections on the Semantic Web. It is shown how museums with their semantically rich and interrelated collection content can create a large, consolidated semantic collection portal together on the web. By sharing a set of ontologies, it is possible to make collections semantically interoperable, and provide the museum visitors with intelligent content-based search and browsing services to the global collection base. The ...

This document is the final report of the CoMMA project. It gives an overview of the different search activities that have been achieved through the project. First, a description of the general requirements is proposed through the definition of two scenarios. Then it shows the different technical aspects of the projects and the solution that has been proposed and implemented.

Semantic information is assuming more and more importance both for the development of knowledge-based applications and for supporting the interoperability among different applications. This paper presents a software framework that tries to simplify the development of such kinds of applications by providing the possibility of working on models for representing such semantic information and implementations of such models that can be easily used by software developers without any knowledge about semantic models and languages. This software library allows to represent a domain model through Java interfaces and annotations and then to use such a representation for automatically generating a Java implementation of such a domain model. Moreover, it provides the interoperability with other applications both automatically mapping the Java domain representation in an OWL ontology, and providing an automatic translation of each object obtained from the domain model representation in an OWL string representation.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Public Domain

Ontology evaluation is an important issue that must be addressed during the lifecycle of an ontology because it assures that the ontology reflects the desired requirements during selection, design, population, evolution, usage, or other processes of the ontology lifecycle. Ontology evaluation aims at assessing the quality and the adequacy of an ontology from the point of view of a particular predefined criterion, for use in a specific context, for a specific purpose. Here, we demonstrate that evaluation is an important issue for ontology evolution. To capture the different nature of evaluation and evolution criteria, we use a tool (S-OntoEval) aiming at assessing ontology quality by implementing existing quality metrics that draw upon semiotic theory. An evaluation of the SWIntO ontology of the SmartWeb project shows its controlled evolution by quality measurement and improvement.

To integrate access to musicology's heterogeneous data sources so that they can be explored effectively and efficiently via one interface service.  To deliver an optimally interactive approach to support this exploration.  To develop a better understanding of how musicologists use the musicSpace interface, so that it can be optimised to support the process of discovery and aid the attainment of new knowledge.

This paper introduces the Protégé plugin uDecide. With the help of uDecide it is possible to solve multi-attribute decision making problems encoded in a straight forward extension of standard Description Logics. The formalism allows to specify background knowledge in terms of an ontology, while each attribute is represented as a weighted class expression. On top of such an approach one can compute the best choice (or the best k-choices) taking background knowledge into account in the appropriate way. We show how to implement the approach on top of existing semantic web technologies and demonstrate its benefits with the help of an interesting use case that illustrates how to convert an existing web resource into an expert system with the help of uDecide.

Triple Space Computing (TSC) has been proposed as communication and coordination paradigm based on the convergence of spacebased computing and the Semantic Web. It acts as a global virtual shared space like middleware to enable communication and coordination of semantic data based on the principle of publish and read. This paper presents an overview of the work in progress under Austrian FIT-IT funded TSC project (http:==tsc.deri.at). It presents the evolution of the TSC framework, overall architecture and its usage by Semantic Web Services.

Currently available toolsets for the development of embedded systems adopt traditional architectural styles and do not cover the whole requirements of the development process, with extensibility being the major drawback. In this paper, a service-oriented architectural framework that exploits semantic web is defined. Features required in the development process are defined as web services and published into the public domain, so as to be used on demand by developers to construct their projects' specific integrated development environments (IDEs). The infrastructure required to build a web service-based IDE is presented. Specific web services are defined and the way these services affect the development process is discussed. Special focus is given on the device model and the means that such a modelling can significantly improve the development process. A prototype implementation demonstrates the applicability and usefulness of the proposed demand-led development process in the industrial automation domain.

Large heterogeneous online repositories of scientific information have the potential to change the way science is done today. In order for this potential to be realized, numerous challenges must be addressed concerning access to and interoperability of the online scientific data. In our work, we are using semantic web technologies to improve access and interoperability by providing a framework for collaboration and a basis for building and distributing advanced data simulation tools. Our initial scientific focus area is the solar terrestrial physics community. In this paper, we will present our work on the Virtual Solar Terrestrial Observatory (VSTO). We will present the emerging trend of the virtual observatory -a virtual integrated evolving scientific data repository -and describe the general use case and our semantically-enabled architecture. We will also present our specific implementation and describe the benefits of the semantic web in this setting. Further, we speculate on the future of the growing adoption of semantic technologies in this important application area of scientific cyberinfrastructure and semantically enabled scientific data repositories.

Large heterogeneous online repositories of scientific information have the potential to change the way science is done today. In order for this potential to be realized, numerous challenges must be addressed concerning access to and interoperability of the online scientific data. In our work, we are using semantic web technologies to improve access and interoperability by providing a framework for collaboration and a basis for building and distributing advanced data simulation tools. Our initial scientific focus area is the solar terrestrial physics community. In this paper, we will present our work on the Virtual Solar Terrestrial Observatory (VSTO). We will present the emerging trend of the virtual observatory -a virtual integrated evolving scientific data repository -and describe the general use case and our semantically-enabled architecture. We will also present our specific implementation and describe the benefits of the semantic web in this setting. Further, we speculate on the future of the growing adoption of semantic technologies in this important application area of scientific cyberinfrastructure and semantically enabled scientific data repositories.

Abstract. The Virtual Solar-Terrestrial Observatory (VSTO) is a distributed, scalable education and research environment for searching, integrating, and analyzing observational, experimental and model databases in fields of solar, solar-terrestrial and space physics. Our work on VSTO required us to create a formal, machine understandable representation for concepts, relations and attributes of physical quantities, including concepts to represent scientific instruments and their operating modes, parameters ...

Personalization efforts to date have centred on presenting web users with novel items by predicting what they may find relevant. This approach has utility where the user is unsure of exactly what they are looking for, but not where they have a particular information need to satisfy or a particular item to locate. Furthermore, by operating purely on a predefined database of users and items, systems using this approach represent closed worlds and offer poor scalability to new data sets. To address these limitations we propose a technique for personalizing relevance in information seeking activities, based on an understanding of how people seek information and recommendations from their social network. We then describe technical work in progress, based on Semantic Web technologies, that aims to realize this perspective.

Formal ontologies have made significant impact in bioscience over the last ten years. Among them, the Foundational Model of Anatomy Ontology (FMA) is the most comprehensive model for the spatio-structural representation of human anatomy. In the research project ME-DICO we use the FMA as our main source of background knowledge about human anatomy. Our ultimate goals are to use spatial knowledge from the FMA (1) to improve automatic parsing algorithms for 3D volume data sets generated by Computed Tomography and Magnetic Resonance Imaging and ( ) to generate semantic annotations using the concepts from the FMA to allow semantic search on medical image repositories. We argue that in this context more spatial relation instances are needed than those currently available in the FMA. In this publication we present a technique for the automatic inductive acquisition of spatial relation instances by generalizing from expert-annotated volume datasets.

TRIPLE was designed as a practical rule language for data manipulation applications. Over the last couple of years the language has been deployed in various applications and use case studies. In this paper we first introduce the design principles of TRIPLE and then present some of the applications for which this language has been used.

Formal ontologies have made significant impact in bioscience over the last ten years. Among them, the Foundational Model of Anatomy Ontology (FMA) is the most comprehensive model for the spatio-structural representation of human anatomy. In the research project ME-DICO we use the FMA as our main source of background knowledge about human anatomy. Our ultimate goals are to use spatial knowledge from the FMA (1) to improve automatic parsing algorithms for 3D volume data sets generated by Computed Tomography and Magnetic Resonance Imaging and ( ) to generate semantic annotations using the concepts from the FMA to allow semantic search on medical image repositories. We argue that in this context more spatial relation instances are needed than those currently available in the FMA. In this publication we present a technique for the automatic inductive acquisition of spatial relation instances by generalizing from expert-annotated volume datasets.

In this paper we show how personalization techniques from the area of adaptive hypermedia can be achieved in the semantic web. Our approach is based on rule-based reasoning enabled by semantic web technologies. The personalization techniques are formalized as reasoning rules. The rules are able to reason over distributed information resources annotated with semantic web metadata formats. This leads towards the realization of an adaptive semantic web idea which provides personalized, adaptive access to information, services, or other, distributed resources.

Traditional adaptive hypermedia systems have focused on providing adaptation functionality on a closed corpus, while Web search interfaces have delivered non-personalized information to users. In this paper, we show how we integrate closed corpus adaptation and global context provision in a Personal Reader environment. The local context consists of individually optimized recommendations to learning materials within the given corpus; the global context provides individually optimized recommendations to resources found on the Web, e. g., FAQs, student exercises, simulations, etc. The adaptive local context of a learning resource is generated by applying methods from adaptive educational hypermedia in a semantic web setting. The adaptive global context is generated by constructing appropriate queries, enrich them based on available user profile information, and, if necessary, relax them during the querying process according to available metadata.

Personalized support for learners becomes even more important, when e-Learning takes place in open and dynamic learning and information networks. This paper shows how to realize personalized learning support in distributed learning environments based on Semantic Web technologies. Our approach fills the existing gap between current adaptive educational systems with well-established personalization functionality, and open, dynamic learning repository networks. We propose a service-based architecture for establishing personalized e-Learning, where personalization functionality is provided by various web-services. A Personal Learning Assistant integrates personalization services and other supporting services, and provides the personalized access to learning resources in an e-Learning network.

In the current Information Society, being informed is a basic necessity. As one of the main news bussiness actors, news agencies are required to provide fresh, relevant, high-quality information to their customers. Dealing with this requirement is not an easy task, but, as partners of the NEWS (News Engine Web Services) project, we believe that the usage of Semantic Web technologies could help news agencies in achieving that objective. In this paper we will describe the aims and main achievements of the NEWS project, that was just completed. The NEWS Consortium is composed of news agencies Agencia EFE S.A.

E-Learning is an important support mechanism for educational systems to increase the efficiency of the education process including students and teachers. The current e-learning systems typically lack the level of metacognitive awareness, adaptive tutoring, and time management skills and have not always met the expectations of the learners as required. In this study, we introduce a novel ontological model for the learning process in the e-learning domain. In the framework, we have built a domain ontology that represents knowledge of the learning, the outcome domain ontology covers the whole learning process. We focused on the learning process ontology model conceptualizing knowledge constructions, such as learning courses, and we present the created course and learning process ontology in detail. In this work, we considered three layers of learning process. The top layer defines a general framework of learning process, conceptual model layer, defines the framework of the actual process of the learning process and course ontology model contains the knowledge unit of the learning process. The prototype ontology is constructed in protégé and managed by Java web ontology language-application programming interface (OWL-API). As a result, our model can solve the problems of current e-tutor systems. Also, it can be used for different domain in e-tutor systems. It can reach the characteristics of standardization, reusability, flexibility, and open knowledge. By applying this model, we can avoid applying isolated databases. The constructed ontology can be used in the future to control adaptive intelligent e-tutor frameworks.

In the field of technology-enhanced learning environment, while some researchers have been working on the learner modelling thematic for decades, the last few years have been marked by the multiplication of challenges related to the representation and selection of relevant information on the learner. Among the significant issues that arise when setting up a learning system is the question of how to present relevant learning content that meets learner's needs, and that also takes into account the learning context information. This present work aims to provide a context-aware learner modelling approach based on ontology. The proposed model incorporates the relevant characteristics of learners plus specific information about their learning context. In this paper, we also analyzed the prevalent approaches and provided a comparative analysis of our model with the most important works in literary.  In conclusion, we showed different use cases that place in evidence the integration of ...

Abstract: There is a long tradition of the use of metadata stores in the educational setting. These stores usually present a mismatch problem between the structure of the metadata, usually some form of XML, and the structure of the repository itself, for example relational databases, or document-oriented stores. These mismatches lead to reduced functionality of the metadata store. This work presents a different alternative, using RDF as the internal representation of educational repositories. The architecture and actual implementation of ...

In this paper the architecture of a learner-centered e-Learning system, which aims to qualify and recommend learning material using semantic web technologies, is presented. In the proposed approach, the learner has a central role in the decision-making process of the distribution of learning material. The main idea relies on gathering appropriate reputation metadata from the learning material consumers. As a result of a proper material ranking, a better matching to future searches of learners having similar profile is anticipated. An experimental implementation of the presented architecture provided interesting results that better depict the applicability and usefulness of the proposals.

A key point in modern automated data processing is meta-data semantics representation. Employing Semantic Web existing fea-tures -ontologies -is a promising option. Ontologies open a novel ap-proach to knowledge representation. The paper presents a GIS (Geographic Information System) domain ap-plication illustrating ontological approach to data integration and data processing automation in the specific system. This VirGIS system is an integration system that works with spatio-temporal data. We start our study with developing the data representation based on common Seman-tic Web techniques and build a VirGIS ontology.

Nowadays the web can serve as a perfect technological environment for personalized learning which is suggested by educators and based on interactive learning objects. While a range of technological solutions for the development of integrated e-learning environments already exists, the most appropriate solutions require further improvement of the implementation of novel learning objects, unification of standardization and integration of learning environments, based on semantic web services that are still in the early stages of development. The aim of the research is to create a model for the development of semantic learning objects, connect it with the architecture of the educational system for semantic learning object design and to present the experimental part of the model's impact on the course design process. The paper presents the research with the main question on how to improve the e-learning course with semantic learning objects by exploring the application of learning object design approaches, usability, performing modern training facilities and the learning object design model based on semantic web technologies.

To date, adding semantic capabilities to web content usually requires considerable server-side reengineering, thus only a tiny fraction of all web content currently has semantic annotations. Recently, we announced Reflect (), a free service that takes a more practical approach: Reflect uses augmented browsing to allow end-users to add systematic semantic annotations to any web-page in real-time, typically within seconds. In this paper we describe the tagging process in detail and show how further entity types can be added to Reflect; we also describe how publishers and content providers can access Reflect programmatically using SOAP, REST (HTTP post), and JavaScript. Usage of Reflect has grown rapidly within the life sciences, and while currently only genes, protein and small molecule names are tagged, we plan to soon expand the scope to include a much broader range of terms (e.g., Wikipedia entries). The popularity of Reflect demonstrates the use and feasibility of letting end-users decide how and when to add semantic annotations. Ultimately, 'semantics is in the eye of the end-user', hence we believe end-user approaches such as Reflect will become increasingly important in semantic web technologies.

The NUbots are the current world champions in the Sony Four-Legged League of RoboCup using the AIBO ERS-7 robots. The present paper describes the team, and how its strategy and approach evolved from RoboCup 2002. The paper also addresses associated research projects and relevant aspects of the study and research environment of the NUbots' host institution, the University of Newcastle in Australia.