No description available.

A Web Semântica tem como meta fazer com que os conteúdos disponibilizados na Web tenham significado não apenas para pessoas, mas também que possam ser processados por máquinas. Essa meta está sendo realizada com o desenvolvimento e uso de ontologias para criar dados anotados semanticamente. Entre as distintas formas de anotação semântica, a Semantic Web Rule Language (SWRL) torna possível criar anotações no formato de regras que combinam regras com conceitos definidos em ontologias, especificadas em Web Ontology Language (OWL), para representar conhecimento sobre dados por meio de afirmações condicionais. Todavia, à medida que o número dessas regras crescem, seus desenvolvedores podem enfrentar dificuldades para gerenciá-las adequadamente. Um grande conjunto de regras torna-se difícil de entender e propício a erros, principalmente quando usado e mantido de forma colaborativa. Neste trabalho é apresentado um conjunto de soluções para aprimorar o uso e gerenciamento de regras SWRL, que compreendem o desenvolvimento de novas representações visuais, técnicas de classificação de regras e ferramenta de detecção de erros. Essas soluções resultaram no SWRL Editor, uma ferramenta Web de visualização e composição de regras que roda como um plug-in para o Web Protégé. Como estudo de caso, foi utilizada a Autism Phenologue Rules, uma ontologia para caracterizar fenótipos de autismo, para exemplificar um conjunto grande e complexo de regras SWRL. A partir desse estudo, uma nova representação visual específica para as regras dessa ontologia foi elaborada, permitindo que um especialista em autismo, sem grandes conhecimentos computacionais, seja capaz de ver e editar regras sem ter de se preocupar com a sintaxe da linguagem SWRL. Os resultados obtidos indicam que o SWRL Editor é uma ferramenta clara e intuitiva, contribuindo para um melhor entendimento, criação e gerenciamento de regras SWRL. / The Semantic Web aims to make web content available not only to people but also to computers using machine-readable formats. This goal is being realized with the development and use of ontologies to create semantically annotated data. Among the different ways to annotate data, the Semantic Web Rule Language (SWRL) enables rule-based annotation that combines rules with ontology concepts, defined using the Web Ontology Language (OWL), to represent knowledge about data as conditional assertions. However, as the number of these rule-base annotations grows, developers face problems when trying to manage them. A large rule set becomes difficult to understand and prone to errors, especially when it is collaboratively maintained. This work presents solutions to improve SWRL rule use and management that include the development of new visual representations, classification techniques and error detection tools. These solutions resulted in the SWRL Editor, a webbased visualization and composition tool for SWRL rules that runs as a Web Protégé plug-in. As a case study, we used the Autism Phenologue Rules, an ontology to characterize autism phenotypes, to exemplify a large and complex SWRL rule set. From this study, a new visual representation, specific for this ontologys rules, has been developed, allowing an expert in autism, without a lot of computational knowledge, to be able to view and edit the rules without having to worry about SWRL syntax. The results obtained indicate that the SWRL Editor is a clear and intuitive tool, contributing for a better understanding and easing the creation and management of SWRL rule sets

A Web Semântica tem como meta fazer com que os conteúdos disponibilizados na Web tenham significado não apenas para pessoas, mas também que possam ser processados por máquinas. Essa meta está sendo realizada com o desenvolvimento e uso de ontologias para criar dados anotados semanticamente. Entre as distintas formas de anotação semântica, a Semantic Web Rule Language (SWRL) torna possível criar anotações no formato de regras que combinam regras com conceitos definidos em ontologias, especificadas em Web Ontology Language (OWL), para representar conhecimento sobre dados por meio de afirmações condicionais. Todavia, à medida que o número dessas regras crescem, seus desenvolvedores podem enfrentar dificuldades para gerenciá-las adequadamente. Um grande conjunto de regras torna-se difícil de entender e propício a erros, principalmente quando usado e mantido de forma colaborativa. Neste trabalho é apresentado um conjunto de soluções para aprimorar o uso e gerenciamento de regras SWRL, que compreendem o desenvolvimento de novas representações visuais, técnicas de classificação de regras e ferramenta de detecção de erros. Essas soluções resultaram no SWRL Editor, uma ferramenta Web de visualização e composição de regras que roda como um plug-in para o Web Protégé. Como estudo de caso, foi utilizada a Autism Phenologue Rules, uma ontologia para caracterizar fenótipos de autismo, para exemplificar um conjunto grande e complexo de regras SWRL. A partir desse estudo, uma nova representação visual específica para as regras dessa ontologia foi elaborada, permitindo que um especialista em autismo, sem grandes conhecimentos computacionais, seja capaz de ver e editar regras sem ter de se preocupar com a sintaxe da linguagem SWRL. Os resultados obtidos indicam que o SWRL Editor é uma ferramenta clara e intuitiva, contribuindo para um melhor entendimento, criação e gerenciamento de regras SWRL. / The Semantic Web aims to make web content available not only to people but also to computers using machine-readable formats. This goal is being realized with the development and use of ontologies to create semantically annotated data. Among the different ways to annotate data, the Semantic Web Rule Language (SWRL) enables rule-based annotation that combines rules with ontology concepts, defined using the Web Ontology Language (OWL), to represent knowledge about data as conditional assertions. However, as the number of these rule-base annotations grows, developers face problems when trying to manage them. A large rule set becomes difficult to understand and prone to errors, especially when it is collaboratively maintained. This work presents solutions to improve SWRL rule use and management that include the development of new visual representations, classification techniques and error detection tools. These solutions resulted in the SWRL Editor, a webbased visualization and composition tool for SWRL rules that runs as a Web Protégé plug-in. As a case study, we used the Autism Phenologue Rules, an ontology to characterize autism phenotypes, to exemplify a large and complex SWRL rule set. From this study, a new visual representation, specific for this ontologys rules, has been developed, allowing an expert in autism, without a lot of computational knowledge, to be able to view and edit the rules without having to worry about SWRL syntax. The results obtained indicate that the SWRL Editor is a clear and intuitive tool, contributing for a better understanding and easing the creation and management of SWRL rule sets

Dans le contexte du Web sémantique, les ontologies OWL représentent des connaissances explicites sur un domaine sur la base d'une conceptualisation des domaines d'intérêt, tandis que la connaissance correspondante sur les individus est donnée par les données RDF qui s'y réfèrent. Dans cette thèse, sur la base d'idées dérivées de l'ILP, nous visons à découvrir des motifs de connaissance cachés sous la forme de règles d'association multi-relationnelles en exploitant l'évidence provenant des assertions contenues dans les bases de connaissances ontologiques. Plus précisément, les règles découvertes sont codées en SWRL pour être facilement intégrées dans l'ontologie, enrichissant ainsi son pouvoir expressif et augmentant les connaissances sur les individus (assertions) qui en peuvent être dérivées. Deux algorithmes appliqués aux bases de connaissances ontologiques peuplées sont proposés pour trouver des règles à forte puissance inductive : (i) un algorithme de génération et test par niveaux et (ii) un algorithme évolutif. Nous avons effectué des expériences sur des ontologies accessibles au public, validant les performances de notre approche et les comparant avec les principaux systèmes de l'état de l'art. En outre, nous effectuons une comparaison des métriques asymétriques les plus répandues, proposées à l'origine pour la notation de règles d'association, comme éléments constitutifs d'une fonction de fitness pour l'algorithme évolutif afin de sélectionner les métriques qui conviennent à la sémantique des données. Afin d'améliorer les performances du système, nous avons proposé de construire un algorithme pour calculer les métriques au lieu d'interroger viaSPARQL-DL. / In the Semantic Web context, OWL ontologies represent explicit domain knowledge based on the conceptualization of domains of interest while the corresponding assertional knowledge is given by RDF data referring to them. In this thesis, based on ideas derived from ILP, we aim at discovering hidden knowledge patterns in the form of multi-relational association rules by exploiting the evidence coming from the assertional data of ontological knowledge bases. Specifically, discovered rules are coded in SWRL to be easily integrated within the ontology, thus enriching its expressive power and augmenting the assertional knowledge that can be derived. Two algorithms applied to populated ontological knowledge bases are proposed for finding rules with a high inductive power: (i) level-wise generated-and-test algorithm and (ii) evolutionary algorithm. We performed experiments on publicly available ontologies, validating the performances of our approach and comparing them with the main state-of-the-art systems. In addition, we carry out a comparison of popular asymmetric metrics, originally proposed for scoring association rules, as building blocks for a fitness function for evolutionary algorithm to select metrics that are suitable with data semantics. In order to improve the system performance, we proposed to build an algorithm to compute metrics instead of querying via SPARQL-DL.

Dans un environnement collaboratif de développement de produit, plusieurs acteurs, ayant différents points de vue et intervenant dans plusieurs phases du cycle de vie de produit, doivent communiquer et échanger des connaissances entre eux. Ces connaissances, existant sous différents formats hétérogènes, incluent potentiellement plusieurs concepts tels que l'historique de conception, la structure du produit, les features, les paramètres, les contraintes, et d'autres informations sur le produit. Les exigences industrielles de réduction du temps et du coût de production nécessitent l'amélioration de l'interopérabilité sémantique entre les différents processus de développement afin de surmonter ces problèmes d'hétérogénéité tant au niveau syntaxique, structurel, que sémantique. Dans le domaine de la CAO, la plupart des méthodes existantes pour l'échange de données d'un modèle de produit sont, effectivement, basées sur le transfert des données géométriques. Cependant, ces données ne sont pas suffisantes pour saisir la sémantique des données, telle que l'intention de conception, ainsi que l'édition des modèles après leur échange. De ce fait, nous nous sommes intéressés à l'échange des modèles " intelligents ", autrement dit, définis en termes d'historique de construction, de fonctions intelligentes de conception appelées features, y compris les paramètres et les contraintes. L'objectif de notre thèse est de concevoir des méthodes permettant d'améliorer l'interopérabilité sémantique des systèmes CAO moyennant les technologies du Web Sémantique comme les ontologies OWL DL et le langage des règles SWRL. Nous avons donc élaboré une approche d'échange basée sur une ontologie commune de features de conception, que nous avons appelée CDFO " Common Design Features Ontology ", servant d'intermédiaire entre les différents systèmes CAO. Cette approche s'appuie principalement sur deux grandes étapes. La première étape consiste en une homogénéisation des formats de représentation des modèles CAO vers un format pivot, en l'occurrence OWL DL. Cette homogénéisation sert à traiter les hétérogénéités syntaxiques entre les formats des modèles. La deuxième étape consiste à définir des règles permettant la mise en correspondance sémantique entre les ontologies d'application de CAO et notre ontologie commune. Cette méthode de mise en correspondance se base principalement, d'une part, sur la définition explicite des axiomes et des règles de correspondance permettant l'alignement des entités de différentes ontologies, et d'autre part sur la reconnaissance automatique des correspondances sémantiques supplémentaires à l'aide des capacités de raisonnement fournies par les moteurs d'inférence basés sur les logiques de description. Enfin, notre méthode de mise en correspondance est enrichie par le développement d'une méthode de calcul de similarité sémantique appropriée pour le langage OWL DL, qui repose principalement sur les composants des entités en question tels que leur description et leur contexte.

This project presents a Materials Informatics Workbench that resolves the challenges confronting materials scientists in the aspects of materials science data assimilation and dissemination. It adopts an approach that has ingeniously combined and extended the technologies of the Semantic Web, Web Service Business Process Execution Language (WSBPEL) and Open Archive Initiative Object Reuse and Exchange (OAI-ORE). These technologies enable the development of novel user interfaces and innovative algorithms and techniques behind the major components of the proposed workbench. In recent years, materials scientists have been struggling with the challenge of dealing with the ever-increasing amount of complex materials science data that are available from online sources and generated by the high-throughput laboratory instruments and data-intensive software tools, respectively. Meanwhile, the funding organizations have encouraged, and even mandated, the sponsored researchers across many domains to make the scientifically-valuable data, together with the traditional scholarly publications, available to the public. This open access requirement provides the opportunity for materials scientists who are able to exploit the available data to expedite the discovery of novel compound materials. However, it also poses challenges for them. The materials scientists raise concerns about the difficulties of precisely locating and processing diverse, but related, data from different data sources and of effectively managing laboratory information and data. In addition, they also lack the simple tools for data access and publication, and require measures for Intellectual Property protection and standards for data sharing, exchange and reuse. The following paragraphs describe how the major workbench components resolve these challenges. First, the materials science ontology, represented in the Web Ontology Language (OWL), enables, (1) the mapping between and the integration of the disparate materials science databases, (2) the modelling of experimental provenance information acquired in the physical and digital domains and, (3) the inferencing and extraction of new knowledge within the materials science domain. Next, the federated search interface based on the materials science ontology enables the materials scientists to search, retrieve, correlate and integrate diverse, but related, materials science data and information across disparate databases. Then, a workflow management system underpinning the WSBPEL engine is not only able to manage the scientific investigation process that incorporates multidisciplinary scientists distributed over a wide geographic region and self-contained computational services, but also systematically acquire the experimental data and information generated by the process. Finally, the provenance-aware scientific compound-object publishing system provides the scientists with a view of the highly complex scientific workflow at multiple-grained levels. Thus, they can easily comprehend the science of the workflow, access experimental information and keep the confidential information from unauthorised viewers. It also enables the scientists to quickly and easily author and publish a scientific compound object that, (1) incorporates not only the internal experimental data with the provenance information from the rendered view of a scientific experimental workflow, but also external digital objects with the metadata, for example, published scholarly papers discoverable via the World Wide Web (the Web), (2) is self- contained and explanatory with IP protection and, (3) is guaranteed to be disseminated widely on the Web. The prototype systems of the major workbench components have been developed. The quality of the material science ontology has been assessed, based on Gruber’s principles for the design of ontologies used for knowledge–sharing, while its applicability has been evaluated through two of the workbench components, the ontology-based federated search interface and the provenance-aware scientific compound object publishing system. Those prototype systems have been deployed within a team of fuel cell scientists working within the Australian Institute for Bioengineering and Nanotechnology (AIBN) at the University of Queensland. Following the user evaluation, the overall feedback to date has been very positive. First, the scientists were impressed with the convenience of the ontology-based federated search interface because of the easy and quick access to the integrated databases and analytical tools. Next, they felt the surge of the relief that the complex compound synthesis process could be managed by and monitored through the WSBPEL workflow management system. They were also excited because the system is able to systematically acquire huge amounts of complex experimental data produced by self-contained computational services that is no longer handled manually with paper-based laboratory notebooks. Finally, the scientific compound object publishing system inspired them to publish their data voluntarily, because it provides them with a scientific-friendly and intuitive interface that enables scientists to, (1) intuitively access experimental data and information, (2) author self-contained and explanatory scientific compound objects that incorporate experimental data and information about research outcomes, and published scholarly papers and peer-reviewed datasets to strengthen those outcomes, (3) enforce proper measures for IP protection, (4) comply those objects with the Open Archives Initiative Protocol – Object Exchange and Reuse (OAI-ORE) to maximize its dissemination over the Web and,(5) ingest those objects into a Fedora-based digital library.

This project presents a Materials Informatics Workbench that resolves the challenges confronting materials scientists in the aspects of materials science data assimilation and dissemination. It adopts an approach that has ingeniously combined and extended the technologies of the Semantic Web, Web Service Business Process Execution Language (WSBPEL) and Open Archive Initiative Object Reuse and Exchange (OAI-ORE). These technologies enable the development of novel user interfaces and innovative algorithms and techniques behind the major components of the proposed workbench. In recent years, materials scientists have been struggling with the challenge of dealing with the ever-increasing amount of complex materials science data that are available from online sources and generated by the high-throughput laboratory instruments and data-intensive software tools, respectively. Meanwhile, the funding organizations have encouraged, and even mandated, the sponsored researchers across many domains to make the scientifically-valuable data, together with the traditional scholarly publications, available to the public. This open access requirement provides the opportunity for materials scientists who are able to exploit the available data to expedite the discovery of novel compound materials. However, it also poses challenges for them. The materials scientists raise concerns about the difficulties of precisely locating and processing diverse, but related, data from different data sources and of effectively managing laboratory information and data. In addition, they also lack the simple tools for data access and publication, and require measures for Intellectual Property protection and standards for data sharing, exchange and reuse. The following paragraphs describe how the major workbench components resolve these challenges. First, the materials science ontology, represented in the Web Ontology Language (OWL), enables, (1) the mapping between and the integration of the disparate materials science databases, (2) the modelling of experimental provenance information acquired in the physical and digital domains and, (3) the inferencing and extraction of new knowledge within the materials science domain. Next, the federated search interface based on the materials science ontology enables the materials scientists to search, retrieve, correlate and integrate diverse, but related, materials science data and information across disparate databases. Then, a workflow management system underpinning the WSBPEL engine is not only able to manage the scientific investigation process that incorporates multidisciplinary scientists distributed over a wide geographic region and self-contained computational services, but also systematically acquire the experimental data and information generated by the process. Finally, the provenance-aware scientific compound-object publishing system provides the scientists with a view of the highly complex scientific workflow at multiple-grained levels. Thus, they can easily comprehend the science of the workflow, access experimental information and keep the confidential information from unauthorised viewers. It also enables the scientists to quickly and easily author and publish a scientific compound object that, (1) incorporates not only the internal experimental data with the provenance information from the rendered view of a scientific experimental workflow, but also external digital objects with the metadata, for example, published scholarly papers discoverable via the World Wide Web (the Web), (2) is self- contained and explanatory with IP protection and, (3) is guaranteed to be disseminated widely on the Web. The prototype systems of the major workbench components have been developed. The quality of the material science ontology has been assessed, based on Gruber’s principles for the design of ontologies used for knowledge–sharing, while its applicability has been evaluated through two of the workbench components, the ontology-based federated search interface and the provenance-aware scientific compound object publishing system. Those prototype systems have been deployed within a team of fuel cell scientists working within the Australian Institute for Bioengineering and Nanotechnology (AIBN) at the University of Queensland. Following the user evaluation, the overall feedback to date has been very positive. First, the scientists were impressed with the convenience of the ontology-based federated search interface because of the easy and quick access to the integrated databases and analytical tools. Next, they felt the surge of the relief that the complex compound synthesis process could be managed by and monitored through the WSBPEL workflow management system. They were also excited because the system is able to systematically acquire huge amounts of complex experimental data produced by self-contained computational services that is no longer handled manually with paper-based laboratory notebooks. Finally, the scientific compound object publishing system inspired them to publish their data voluntarily, because it provides them with a scientific-friendly and intuitive interface that enables scientists to, (1) intuitively access experimental data and information, (2) author self-contained and explanatory scientific compound objects that incorporate experimental data and information about research outcomes, and published scholarly papers and peer-reviewed datasets to strengthen those outcomes, (3) enforce proper measures for IP protection, (4) comply those objects with the Open Archives Initiative Protocol – Object Exchange and Reuse (OAI-ORE) to maximize its dissemination over the Web and,(5) ingest those objects into a Fedora-based digital library.

This thesis proposes a reference model and its computational core to support the creation of software applications within educational environments, which address Differences In Learning (DiffInL) and are applicable to both learners and instructors. This work differs from others in that the strength of this model resides on the re-usable character of the reasoning mechanism enabled by the computational environment. The starting point is the definition of agreed learning goals that the learner needs to achieve. In turn, the reference model generates personalised, best-practice teaching and learning materials, suitable for achieving the individual’s learning goals. This reference model consists of MODEL and MANAGEMENT components. The MODEL components store the domain needed to create learners and instructional models, which are required for the creation of Learning Spaces (LeS). The MANAGEMENT compo- nent also manages the semantics stored in various model components in order to carry out the configuration of an LeS. The architecture of software applications generated from the reference model is illustrated and contains: Netbeans IDE 8.0.2, JavaServer Faces framework and OWL-API library. We tested this to generate teaching practices for Learning Difficulties (LDif) student. In order to prove the feasibility of creating a software application from the reference model, an example of a particular scenario in a specific educational setting for LDif Students has been shown. This proposed model has successfully proved its ability to address the needs of LDif Students through a corresponding novel and re-usable reasoning mechanism implemented in Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) computational environments. The reference model has shown its ability to integrate with different disciplines such as psychology, sociology and human-computer interactions. The main contribution to research is the creation of a novel reference computational model which addresses the needs of people with DiffInL. The strength of this model resides on the re-usable character of the reasoning mechanism enabled by the computational environment. The whole framework allows a unified implementation which takes into account classes, constraints, matching, and inference mechanisms for the complete configuration of an LeS. The suggested approach also differs from previous work in that it is personalised, and the applied reasoning rules are dynamic. Therefore this model can be constantly “tuned” according to the questions we may ask in such environments. Overall, the proposed reference model in this research offers a promising and feasible solution that can support current educational systems and benefit both learners and instructors. It also demonstrates the applicability of the latest technologies and would allow for future technologies to be incorporated, in order to enhance the model.

No description available.

Next-generation network architectures support complex services in the data-path of routers. A key challenge is the integration of multiple policy constraints from senders, receivers, and network providers when using such services. We introduce a multi-party service specification framework based on our “service socket” API. We illustrate the operation of this approach in an IPTV scenario that uses a video transcoding service implemented on a Cisco ISR platform.