7 resultados para Resource Description Framework

em Universidad Politécnica de Madrid


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In this introductory chapter we put in context and give a brief outline of the work that we thoroughly present in the rest of the dissertation. We consider this work divided in two main parts. The first part is the Firenze Framework, a knowledge level description framework rich enough to express the semantics required for describing both semantic Web services and semantic Grid services. We start by defining what the Semantic Grid is and its relation with the Semantic Web; and the possibility of their convergence since both initiatives have become mainly service-oriented. We also introduce the main motivators of the creation of this framework, one is to provide a valid description framework that works at knowledge level; the other to provide a description framework that takes into account the characteristics of Grid services in order to be able to describe them properly. The other part of the dissertation is devoted to Vega, an event-driven architecture that, by means of proposed knowledge level description framework, is able to achieve high scale provisioning of knowledge-intensive services. In this introductory chapter we portrait the anatomy of a generic event-driven architecture, and we briefly enumerate their main characteristics, which are the reason that make them our choice.

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This PhD thesis contributes to the problem of resource and service discovery in the context of the composable web. In the current web, mashup technologies allow developers reusing services and contents to build new web applications. However, developers face a problem of information flood when searching for appropriate services or resources for their combination. To contribute to overcoming this problem, a framework is defined for the discovery of services and resources. In this framework, three levels are defined for performing discovery at content, discovery and agente levels. The content level involves the information available in web resources. The web follows the Representational Stateless Transfer (REST) architectural style, in which resources are returned as representations from servers to clients. These representations usually employ the HyperText Markup Language (HTML), which, along with Content Style Sheets (CSS), describes the markup employed to render representations in a web browser. Although the use of SemanticWeb standards such as Resource Description Framework (RDF) make this architecture suitable for automatic processes to use the information present in web resources, these standards are too often not employed, so automation must rely on processing HTML. This process, often referred as Screen Scraping in the literature, is the content discovery according to the proposed framework. At this level, discovery rules indicate how the different pieces of data in resources’ representations are mapped onto semantic entities. By processing discovery rules on web resources, semantically described contents can be obtained out of them. The service level involves the operations that can be performed on the web. The current web allows users to perform different tasks such as search, blogging, e-commerce, or social networking. To describe the possible services in RESTful architectures, a high-level feature-oriented service methodology is proposed at this level. This lightweight description framework allows defining service discovery rules to identify operations in interactions with REST resources. The discovery is thus performed by applying discovery rules to contents discovered in REST interactions, in a novel process called service probing. Also, service discovery can be performed by modelling services as contents, i.e., by retrieving Application Programming Interface (API) documentation and API listings in service registries such as ProgrammableWeb. For this, a unified model for composable components in Mashup-Driven Development (MDD) has been defined after the analysis of service repositories from the web. The agent level involves the orchestration of the discovery of services and contents. At this level, agent rules allow to specify behaviours for crawling and executing services, which results in the fulfilment of a high-level goal. Agent rules are plans that allow introspecting the discovered data and services from the web and the knowledge present in service and content discovery rules to anticipate the contents and services to be found on specific resources from the web. By the definition of plans, an agent can be configured to target specific resources. The discovery framework has been evaluated on different scenarios, each one covering different levels of the framework. Contenidos a la Carta project deals with the mashing-up of news from electronic newspapers, and the framework was used for the discovery and extraction of pieces of news from the web. Similarly, in Resulta and VulneraNET projects the discovery of ideas and security knowledge in the web is covered, respectively. The service level is covered in the OMELETTE project, where mashup components such as services and widgets are discovered from component repositories from the web. The agent level is applied to the crawling of services and news in these scenarios, highlighting how the semantic description of rules and extracted data can provide complex behaviours and orchestrations of tasks in the web. The main contributions of the thesis are the unified framework for discovery, which allows configuring agents to perform automated tasks. Also, a scraping ontology has been defined for the construction of mappings for scraping web resources. A novel first-order logic rule induction algorithm is defined for the automated construction and maintenance of these mappings out of the visual information in web resources. Additionally, a common unified model for the discovery of services is defined, which allows sharing service descriptions. Future work comprises the further extension of service probing, resource ranking, the extension of the Scraping Ontology, extensions of the agent model, and contructing a base of discovery rules. Resumen La presente tesis doctoral contribuye al problema de descubrimiento de servicios y recursos en el contexto de la web combinable. En la web actual, las tecnologías de combinación de aplicaciones permiten a los desarrolladores reutilizar servicios y contenidos para construir nuevas aplicaciones web. Pese a todo, los desarrolladores afrontan un problema de saturación de información a la hora de buscar servicios o recursos apropiados para su combinación. Para contribuir a la solución de este problema, se propone un marco de trabajo para el descubrimiento de servicios y recursos. En este marco, se definen tres capas sobre las que se realiza descubrimiento a nivel de contenido, servicio y agente. El nivel de contenido involucra a la información disponible en recursos web. La web sigue el estilo arquitectónico Representational Stateless Transfer (REST), en el que los recursos son devueltos como representaciones por parte de los servidores a los clientes. Estas representaciones normalmente emplean el lenguaje de marcado HyperText Markup Language (HTML), que, unido al estándar Content Style Sheets (CSS), describe el marcado empleado para mostrar representaciones en un navegador web. Aunque el uso de estándares de la web semántica como Resource Description Framework (RDF) hace apta esta arquitectura para su uso por procesos automatizados, estos estándares no son empleados en muchas ocasiones, por lo que cualquier automatización debe basarse en el procesado del marcado HTML. Este proceso, normalmente conocido como Screen Scraping en la literatura, es el descubrimiento de contenidos en el marco de trabajo propuesto. En este nivel, un conjunto de reglas de descubrimiento indican cómo los diferentes datos en las representaciones de recursos se corresponden con entidades semánticas. Al procesar estas reglas sobre recursos web, pueden obtenerse contenidos descritos semánticamente. El nivel de servicio involucra las operaciones que pueden ser llevadas a cabo en la web. Actualmente, los usuarios de la web pueden realizar diversas tareas como búsqueda, blogging, comercio electrónico o redes sociales. Para describir los posibles servicios en arquitecturas REST, se propone en este nivel una metodología de alto nivel para descubrimiento de servicios orientada a funcionalidades. Este marco de descubrimiento ligero permite definir reglas de descubrimiento de servicios para identificar operaciones en interacciones con recursos REST. Este descubrimiento es por tanto llevado a cabo al aplicar las reglas de descubrimiento sobre contenidos descubiertos en interacciones REST, en un nuevo procedimiento llamado sondeo de servicios. Además, el descubrimiento de servicios puede ser llevado a cabo mediante el modelado de servicios como contenidos. Es decir, mediante la recuperación de documentación de Application Programming Interfaces (APIs) y listas de APIs en registros de servicios como ProgrammableWeb. Para ello, se ha definido un modelo unificado de componentes combinables para Mashup-Driven Development (MDD) tras el análisis de repositorios de servicios de la web. El nivel de agente involucra la orquestación del descubrimiento de servicios y contenidos. En este nivel, las reglas de nivel de agente permiten especificar comportamientos para el rastreo y ejecución de servicios, lo que permite la consecución de metas de mayor nivel. Las reglas de los agentes son planes que permiten la introspección sobre los datos y servicios descubiertos, así como sobre el conocimiento presente en las reglas de descubrimiento de servicios y contenidos para anticipar contenidos y servicios por encontrar en recursos específicos de la web. Mediante la definición de planes, un agente puede ser configurado para descubrir recursos específicos. El marco de descubrimiento ha sido evaluado sobre diferentes escenarios, cada uno cubriendo distintos niveles del marco. El proyecto Contenidos a la Carta trata de la combinación de noticias de periódicos digitales, y en él el framework se ha empleado para el descubrimiento y extracción de noticias de la web. De manera análoga, en los proyectos Resulta y VulneraNET se ha llevado a cabo un descubrimiento de ideas y de conocimientos de seguridad, respectivamente. El nivel de servicio se cubre en el proyecto OMELETTE, en el que componentes combinables como servicios y widgets se descubren en repositorios de componentes de la web. El nivel de agente se aplica al rastreo de servicios y noticias en estos escenarios, mostrando cómo la descripción semántica de reglas y datos extraídos permiten proporcionar comportamientos complejos y orquestaciones de tareas en la web. Las principales contribuciones de la tesis son el marco de trabajo unificado para descubrimiento, que permite configurar agentes para realizar tareas automatizadas. Además, una ontología de extracción ha sido definida para la construcción de correspondencias y extraer información de recursos web. Asimismo, un algoritmo para la inducción de reglas de lógica de primer orden se ha definido para la construcción y el mantenimiento de estas correspondencias a partir de la información visual de recursos web. Adicionalmente, se ha definido un modelo común y unificado para el descubrimiento de servicios que permite la compartición de descripciones de servicios. Como trabajos futuros se considera la extensión del sondeo de servicios, clasificación de recursos, extensión de la ontología de extracción y la construcción de una base de reglas de descubrimiento.

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The use of semantic and Linked Data technologies for Enterprise Application Integration (EAI) is increasing in recent years. Linked Data and Semantic Web technologies such as the Resource Description Framework (RDF) data model provide several key advantages over the current de-facto Web Service and XML based integration approaches. The flexibility provided by representing the data in a more versatile RDF model using ontologies enables avoiding complex schema transformations and makes data more accessible using Web standards, preventing the formation of data silos. These three benefits represent an edge for Linked Data-based EAI. However, work still has to be performed so that these technologies can cope with the particularities of the EAI scenarios in different terms, such as data control, ownership, consistency, or accuracy. The first part of the paper provides an introduction to Enterprise Application Integration using Linked Data and the requirements imposed by EAI to Linked Data technologies focusing on one of the problems that arise in this scenario, the coreference problem, and presents a coreference service that supports the use of Linked Data in EAI systems. The proposed solution introduces the use of a context that aggregates a set of related identities and mappings from the identities to different resources that reside in distinct applications and provide different views or aspects of the same entity. A detailed architecture of the Coreference Service is presented explaining how it can be used to manage the contexts, identities, resources, and applications which they relate to. The paper shows how the proposed service can be utilized in an EAI scenario using an example involving a dashboard that integrates data from different systems and the proposed workflow for registering and resolving identities. As most enterprise applications are driven by business processes and involve legacy data, the proposed approach can be easily incorporated into enterprise applications.

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This paper presents a Focused Crawler in order to Get Semantic Web Resources (CSR). Structured data web are available in formats such as Extensible Markup Language (XML), Resource Description Framework (RDF) and Ontology Web Language (OWL) that can be used for processing. One of the main challenges for performing a manual search and download semantic web resources is that this task consumes a lot of time. Our research work propose a focused crawler which allow to download these resources automatically and store them on disk in order to have a collection that will be used for data processing. CRS consists of three layers: (a) The User Interface Layer, (b) The Focus Crawler Layer and (c) The Base Crawler Layer. CSR uses as a selection policie the Shark-Search method. CSR was conducted with two experiments. The first one starts on December 15 2012 at 7:11 am and ends on December 16 2012 at 4:01 were obtained 448,123,537 bytes of data. The CSR ends by itself after to analyze 80,4375 seeds with an unlimited depth. CSR got 16,576 semantic resources files where the 89 % was RDF, the 10 % was XML and the 1% was OWL. The second one was based on the Web Data Commons work of the Research Group Data and Web Science at the University of Mannheim and the Institute AIFB at the Karlsruhe Institute of Technology. This began at 4:46 am of June 2 2013 and 1:37 am June 9 2013. After 162.51 hours of execution the result was 285,279 semantic resources where predominated the XML resources with 99 % and OWL and RDF with 1 % each one.

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El Análisis de Consumo de Recursos o Análisis de Coste trata de aproximar el coste de ejecutar un programa como una función dependiente de sus datos de entrada. A pesar de que existen trabajos previos a esta tesis doctoral que desarrollan potentes marcos para el análisis de coste de programas orientados a objetos, algunos aspectos avanzados, como la eficiencia, la precisión y la fiabilidad de los resultados, todavía deben ser estudiados en profundidad. Esta tesis aborda estos aspectos desde cuatro perspectivas diferentes: (1) Las estructuras de datos compartidas en la memoria del programa son una pesadilla para el análisis estático de programas. Trabajos recientes proponen una serie de condiciones de localidad para poder mantener de forma consistente información sobre los atributos de los objetos almacenados en memoria compartida, reemplazando éstos por variables locales no almacenadas en la memoria compartida. En esta tesis presentamos dos extensiones a estos trabajos: la primera es considerar, no sólo los accesos a los atributos, sino también los accesos a los elementos almacenados en arrays; la segunda se centra en los casos en los que las condiciones de localidad no se cumplen de forma incondicional, para lo cual, proponemos una técnica para encontrar las precondiciones necesarias para garantizar la consistencia de la información acerca de los datos almacenados en memoria. (2) El objetivo del análisis incremental es, dado un programa, los resultados de su análisis y una serie de cambios sobre el programa, obtener los nuevos resultados del análisis de la forma más eficiente posible, evitando reanalizar aquellos fragmentos de código que no se hayan visto afectados por los cambios. Los analizadores actuales todavía leen y analizan el programa completo de forma no incremental. Esta tesis presenta un análisis de coste incremental, que, dado un cambio en el programa, reconstruye la información sobre el coste del programa de todos los métodos afectados por el cambio de forma incremental. Para esto, proponemos (i) un algoritmo multi-dominio y de punto fijo que puede ser utilizado en todos los análisis globales necesarios para inferir el coste, y (ii) una novedosa forma de almacenar las expresiones de coste que nos permite reconstruir de forma incremental únicamente las funciones de coste de aquellos componentes afectados por el cambio. (3) Las garantías de coste obtenidas de forma automática por herramientas de análisis estático no son consideradas totalmente fiables salvo que la implementación de la herramienta o los resultados obtenidos sean verificados formalmente. Llevar a cabo el análisis de estas herramientas es una tarea titánica, ya que se trata de herramientas de gran tamaño y complejidad. En esta tesis nos centramos en el desarrollo de un marco formal para la verificación de las garantías de coste obtenidas por los analizadores en lugar de analizar las herramientas. Hemos implementado esta idea mediante la herramienta COSTA, un analizador de coste para programas Java y KeY, una herramienta de verificación de programas Java. De esta forma, COSTA genera las garantías de coste, mientras que KeY prueba la validez formal de los resultados obtenidos, generando de esta forma garantías de coste verificadas. (4) Hoy en día la concurrencia y los programas distribuidos son clave en el desarrollo de software. Los objetos concurrentes son un modelo de concurrencia asentado para el desarrollo de sistemas concurrentes. En este modelo, los objetos son las unidades de concurrencia y se comunican entre ellos mediante llamadas asíncronas a sus métodos. La distribución de las tareas sugiere que el análisis de coste debe inferir el coste de los diferentes componentes distribuidos por separado. En esta tesis proponemos un análisis de coste sensible a objetos que, utilizando los resultados obtenidos mediante un análisis de apunta-a, mantiene el coste de los diferentes componentes de forma independiente. Abstract Resource Analysis (a.k.a. Cost Analysis) tries to approximate the cost of executing programs as functions on their input data sizes and without actually having to execute the programs. While a powerful resource analysis framework on object-oriented programs existed before this thesis, advanced aspects to improve the efficiency, the accuracy and the reliability of the results of the analysis still need to be further investigated. This thesis tackles this need from the following four different perspectives. (1) Shared mutable data structures are the bane of formal reasoning and static analysis. Analyses which keep track of heap-allocated data are referred to as heap-sensitive. Recent work proposes locality conditions for soundly tracking field accesses by means of ghost non-heap allocated variables. In this thesis we present two extensions to this approach: the first extension is to consider arrays accesses (in addition to object fields), while the second extension focuses on handling cases for which the locality conditions cannot be proven unconditionally by finding aliasing preconditions under which tracking such heap locations is feasible. (2) The aim of incremental analysis is, given a program, its analysis results and a series of changes to the program, to obtain the new analysis results as efficiently as possible and, ideally, without having to (re-)analyze fragments of code that are not affected by the changes. During software development, programs are permanently modified but most analyzers still read and analyze the entire program at once in a non-incremental way. This thesis presents an incremental resource usage analysis which, after a change in the program is made, is able to reconstruct the upper-bounds of all affected methods in an incremental way. To this purpose, we propose (i) a multi-domain incremental fixed-point algorithm which can be used by all global analyses required to infer the cost, and (ii) a novel form of cost summaries that allows us to incrementally reconstruct only those components of cost functions affected by the change. (3) Resource guarantees that are automatically inferred by static analysis tools are generally not considered completely trustworthy, unless the tool implementation or the results are formally verified. Performing full-blown verification of such tools is a daunting task, since they are large and complex. In this thesis we focus on the development of a formal framework for the verification of the resource guarantees obtained by the analyzers, instead of verifying the tools. We have implemented this idea using COSTA, a state-of-the-art cost analyzer for Java programs and KeY, a state-of-the-art verification tool for Java source code. COSTA is able to derive upper-bounds of Java programs while KeY proves the validity of these bounds and provides a certificate. The main contribution of our work is to show that the proposed tools cooperation can be used for automatically producing verified resource guarantees. (4) Distribution and concurrency are today mainstream. Concurrent objects form a well established model for distributed concurrent systems. In this model, objects are the concurrency units that communicate via asynchronous method calls. Distribution suggests that analysis must infer the cost of the diverse distributed components separately. In this thesis we propose a novel object-sensitive cost analysis which, by using the results gathered by a points-to analysis, can keep the cost of the diverse distributed components separate.

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We describe the datos.bne.es library dataset. The dataset makes available the authority and bibliography catalogue from the Biblioteca Nacional de España (BNE, National Library of Spain) as Linked Data. The catalogue contains around 7 million authority and bibliographic records. The records in MARC 21 format were transformed to RDF and modelled using IFLA (International Federation of Library Associations) ontologies and other well-established vocabularies such as RDA (Resource Description and Access) or the Dublin Core Metadata Element Set. A tool named MARiMbA automatized the RDF generation process and the data linkage to DBpedia and other library linked data resources such as VIAF (Virtual International Authority File) or GND (Gemeinsame Normdatei, the authority dataset from the German National Library).

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Growing scarcity, increasing demand and bad management of water resources are causing weighty competition for water and consequently managers are facing more and more pressure in an attempt to satisfy users? requirement. In many regions agriculture is one of the most important users at river basin scale since it concentrates high volumes of water consumption during relatively short periods (irrigation season), with a significant economic, social and environmental impact. The interdisciplinary characteristics of related water resources problems require, as established in the Water Framework Directive 2000/60/EC, an integrated and participative approach to water management and assigns an essential role to economic analysis as a decision support tool. For this reason, a methodology is developed to analyse the economic and environmental implications of water resource management under different scenarios, with a focus on the agricultural sector. This research integrates both economic and hydrologic components in modelling, defining scenarios of water resource management with the goal of preventing critical situations, such as droughts. The model follows the Positive Mathematical Programming (PMP) approach, an innovative methodology successfully used for agricultural policy analysis in the last decade and also applied in several analyses regarding water use in agriculture. This approach has, among others, the very important capability of perfectly calibrating the baseline scenario using a very limited database. However one important disadvantage is its limited capacity to simulate activities non-observed during the reference period but which could be adopted if the scenario changed. To overcome this problem the classical methodology is extended in order to simulate a more realistic farmers? response to new agricultural policies or modified water availability. In this way an economic model has been developed to reproduce the farmers? behaviour within two irrigation districts in the Tiber High Valley. This economic model is then integrated with SIMBAT, an hydrologic model developed for the Tiber basin which allows to simulate the balance between the water volumes available at the Montedoglio dam and the water volumes required by the various irrigation users.