7 research outputs found

    The SSN ontology of the W3C semantic sensor network incubator group

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    The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations ? the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects

    Aplicación de algoritmos genéticos a la clasificación de imágenes de satélite en el marco de los servicios grid inteligentes estado del arte

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    During many years, the web services have been interested about the syntactic interoperability problem among applications, but forgetting semantics. With the great amount of available information in the Web, and the emergence of news paradigms as Computing Grid, it is necessary to improve the web services by including the semantic component in order to achieve a better benefit from these resources and from necessary elements to be used in a grid environment. In the Web intelligence field, have been proposed several projects, among them, the application of soft computing techniques, such as, evolutionary computation. In this paper we will carry out a review about the Grid current development and other related topics, such as, Semantic Web and Web Services, as well as, the different approaches about the genetic algorithms application in satellite image classification problem.Los servicios Web han atendido durante muchos años el problema de la interoperabilidad sintáctica entre aplicaciones, dejando a un lado la semántica. Con el gran volumen de información disponible en la Web, y la aparición de nuevos paradigmas como la Computación Grid, ha surgido la necesidad de mejorar los servicios Web mediante la inclusión del componente semántico para lograr un mayor aprovechamiento de estos recursos y de los elementos necesarios para que dichos servicios puedan ser utilizados dentro de un ambiente Grid. En el campo de la inteligencia Web se han hecho varias propuestas, entre ellas la aplicación de técnicas de computación flexible como la computación evolucionaria. En este documento se realizará una revisión sobre el desarrollo actual de la Grid y otrostemas relacionados como la Web semántica y los servicios Web, además de los diferentes enfoques acerca de la aplicación de los Algoritmos Genéticos al problema de la clasificación de imágenes de satélite

    Semantically-Enabled Sensor Plug & Play for the Sensor Web

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    Environmental sensors have continuously improved by becoming smaller, cheaper, and more intelligent over the past years. As consequence of these technological advancements, sensors are increasingly deployed to monitor our environment. The large variety of available sensor types with often incompatible protocols complicates the integration of sensors into observing systems. The standardized Web service interfaces and data encodings defined within OGC’s Sensor Web Enablement (SWE) framework make sensors available over the Web and hide the heterogeneous sensor protocols from applications. So far, the SWE framework does not describe how to integrate sensors on-the-fly with minimal human intervention. The driver software which enables access to sensors has to be implemented and the measured sensor data has to be manually mapped to the SWE models. In this article we introduce a Sensor Plug & Play infrastructure for the Sensor Web by combining (1) semantic matchmaking functionality, (2) a publish/subscribe mechanism underlying the SensorWeb, as well as (3) a model for the declarative description of sensor interfaces which serves as a generic driver mechanism. We implement and evaluate our approach by applying it to an oil spill scenario. The matchmaking is realized using existing ontologies and reasoning engines and provides a strong case for the semantic integration capabilities provided by Semantic Web research

    An extensible semantic catalogue for geospatial web services

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    Searching for web services is a challenging task due to the diversity of existing discovery tools. Varying standards for service descriptions require different tools to query their content. These standards exist for good reasons. Web services are used in different application environments and special solutions are required for their integration. We suggest an architecture for web service catalogues, which takes this diversity of standards into account. Its extensibility allows for a complete separation between service discovery and service description. Using ontologies for the storage of service descriptions enables the support of different description standards without loosing their specific advantages. The discussion and implementation focuses on geospatial web services. Due to the heterogeneity of spatially referenced data, different specifications exist for them, making the problem of different standards for service discovery and service description most evident here

    Geospatial Semantics: Why, of What, and How?

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    Abstract. Why are notions like semantics and ontologies suddenly getting so much attention, within and outside geospatial information communities? The main reason lies in the componentization of Geographic Information Systems (GIS) into services, which are supposed to interoperate within and across these communities. Consequently, I look at geospatial semantics in the context of semantic interoperability. The paper clarifies the relevant notion of semantics and shows what parts of geospatial information need to receive semantic speci-fications in order to achieve interoperability. No attempt at a survey of ap-proaches to provide semantics is made, but a framework for solving interopera-bility problems is proposed in the form of semantic reference systems. Particular emphasis is put on the need and possible ways to ground geospatial semantics in physical processes and measurements. 1. Introduction: Wh

    GEOINTERPRET: AN ONTOLOGICAL ENGINEERING METHODOLOGY FOR AUTOMATED INTERPRETATION OF GEOSPATIAL QUERIES

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    Despite advances in GIS technology, solving geospatial problems using current GIS platforms involves complex tasks requiring specialized skills and knowledge that are attainable through formal training and experience in implementing GIS projects. These requisite skills and knowledge include: understanding domain-specific geospatial problems; understanding GIS representation of real-world objects, concepts, and activities; knowing how to identify, locate, retrieve, and integrate geospatial data sets into GIS projects; knowing specific geoprocessing capabilities available on specific GIS platforms; and skills in utilizing geoprocessing tools in GIS with appropriate data sets to solve problems effectively and efficiently. Users interested in solving application-domain problems often lack such skills and knowledge and resort to GIS experts (this is especially true for applications dealing with diverse geospatial data sets and complex problems). Therefore, there is a gap between users' knowledge about geoprocessing and GIS tools and the GIS knowledge and skills needed to solve geospatial problems. To fill this gap, a new approach that automates the tasks involved in geospatial problem solving is needed. Of these tasks, the most important is geospatial query (usually expressed in application-specific concepts and terminologies) interpretation and mapping to geoprocessing operations implementable by GIS. The goal of this research is to develop an ontological engineering methodology, called GeoInterpret, to automate the task of geospatial query interpretation and mapping. This methodology encompasses: a conceptualization of geospatial queries; a multiple-ontology approach for representing knowledge needed to solve geospatial queries; a set of techniques for mapping elements between different ontologies; and a set of algorithms for geospatial query interpretation, mapping, and geoprocessing workflow composition. A proof of concept was developed to demonstrate the working of GeoInterpret

    Value- and debt-aware selection and composition in cloud-based service-oriented architectures using real options

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    This thesis presents a novel model for service selection and composition in Cloud-based Service-Oriented Architectures (CB-SOA), which is called CloudMTD, using real options, Dependency Structure Matrix (DSM) and propagation-cost metrics. CB-SOA architectures are composed of web services, which are leased or bought off the cloud marketplace. CB-SOA can improve its utility and add value to its composition by substituting its constituent services. The substitution decisions may introduce technical debt, which needs to be managed. The thesis defines the concept of technical debt for CB-SOA and reports on the available technical debt definitions and approaches in the literature. The formulation of service substitution problem and its technical debt valuation is based on options, which exploits Binomial Options Analysis. This thesis looks at different option types under uncertainty. This thesis is concerned with some scenarios that may lead to technical debt, which are related to web service selection and composition that has been driven by either a technical or a business objective. In each scenario, we are interested in three decisions (1) keep, (2) substitute or (3) abandon the current service. Each scenario takes into consideration either one or more QoS attribute dimension (e.g. Availability). We address these scenarios from an option-based perspective. Each scenario is linked to a suitable option type. A specific option type depends on the nature of the application, problem to be investigated, and the decision to be taken. In addition, we use Dependency Structure Matrix (DSM) in order to represent dependencies among web services in CB-SOA. We introduce time and complexity sensitive propagation-cost metrics to DSM to solve the problem. In addition, CloudMTD model informs the time-value of the decisions under uncertainty based on behavioral and structural aspects of CB-SOA
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