975 resultados para Web Semantico semantic open data geoSPARQL
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The open provenance architecture (OPA) approach to the challenge was distinct in several regards. In particular, it is based on an open, well-defined data model and architecture, allowing different components of the challenge workflow to independently record documentation, and for the workflow to be executed in any environment. Another noticeable feature is that we distinguish between the data recorded about what has occurred, emphprocess documentation, and the emphprovenance of a data item, which is all that caused the data item to be as it is and is obtained as the result of a query over process documentation. This distinction allows us to tailor the system to separately best address the requirements of recording and querying documentation. Other notable features include the explicit recording of causal relationships between both events and data items, an interaction-based world model, intensional definition of data items in queries rather than relying on explicit naming mechanisms, and emphstyling of documentation to support non-functional application requirements such as reducing storage costs or ensuring privacy of data. In this paper we describe how each of these features aid us in answering the challenge provenance queries.
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HydroShare is an online, collaborative system being developed for open sharing of hydrologic data and models. The goal of HydroShare is to enable scientists to easily discover and access hydrologic data and models, retrieve them to their desktop or perform analyses in a distributed computing environment that may include grid, cloud or high performance computing model instances as necessary. Scientists may also publish outcomes (data, results or models) into HydroShare, using the system as a collaboration platform for sharing data, models and analyses. HydroShare is expanding the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated, creating new capability to share models and model components, and taking advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. One of the fundamental concepts in HydroShare is that of a Resource. All content is represented using a Resource Data Model that separates system and science metadata and has elements common to all resources as well as elements specific to the types of resources HydroShare will support. These will include different data types used in the hydrology community and models and workflows that require metadata on execution functionality. The HydroShare web interface and social media functions are being developed using the Drupal content management system. A geospatial visualization and analysis component enables searching, visualizing, and analyzing geographic datasets. The integrated Rule-Oriented Data System (iRODS) is being used to manage federated data content and perform rule-based background actions on data and model resources, including parsing to generate metadata catalog information and the execution of models and workflows. This presentation will introduce the HydroShare functionality developed to date, describe key elements of the Resource Data Model and outline the roadmap for future development.
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Observational data encodes values of properties associated with a feature of interest, estimated by a specified procedure. For water the properties are physical parameters like level, volume, flow and pressure, and concentrations and counts of chemicals, substances and organisms. Water property vocabularies have been assembled at project, agency and jurisdictional level. Organizations such as EPA, USGS, CEH, GA and BoM maintain vocabularies for internal use, and may make them available externally as text files. BODC and MMI have harvested many water vocabularies alongside others of interest in their domain, formalized the content using SKOS, and published them through web interfaces. Scope is highly variable both within and between vocabularies. Individual items may conflate multiple concerns (e.g. property, instrument, statistical procedure, units). There is significant duplication between vocabularies. Semantic web technologies provide the opportunity both to publish vocabularies more effectively, and achieve harmonization to support greater interoperability between datasets. - Models for vocabulary items (property, substance/taxon, process, unit-of-measure, etc) may be formalized OWL ontologies, supporting semantic relations between items in related vocabularies; - By specializing the ontology elements from SKOS concepts and properties, diverse vocabularies may be published through a common interface; - Properties from standard vocabularies (e.g. OWL, SKOS, PROV-O and VAEM) support mappings between vocabularies having a similar scope - Existing items from various sources may be assembled into new virtual vocabularies However, there are a number of challenges: - use of standard properties such as sameAs/exactMatch/equivalentClass require reasoning support; - items have been conceptualised as both classes and individuals, complicating the mapping mechanics; - re-use of items across vocabularies may conflict with expectations concerning URI patterns; - versioning complicates cross-references and re-use. This presentation will discuss ways to harness semantic web technologies to publish harmonized vocabularies, and will summarise how many of the challenges may be addressed.
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A key to maintain Enterprises competitiveness is the ability to describe, standardize, and adapt the way it reacts to certain types of business events, and how it interacts with suppliers, partners, competitors, and customers. In this context the field of organization modeling has emerged with the aim to create models that help to create a state of self-awareness in the organization. This project's context is the use of Semantic Web in the Organizational modeling area. The Semantic Web technology advantages can be used to improve the way of modeling organizations. This was accomplished using a Semantic wiki to model organizations. Our research and implementation had two main purposes: formalization of textual content in semantic wiki pages; and automatic generation of diagrams from organization data stored in the semantic wiki pages.
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Recently the focus given to Web Services and Semantic Web technologies has provided the development of several research projects in different ways to addressing the Web services composition issue. Meanwhile, the challenge of creating an environment that provides the specification of an abstract business process and that it is automatically implemented by a composite service in a dynamic way is considered a currently open problem. WSDL and BPEL provided by industry support only manual service composition because they lack needed semantics so that Web services are discovered, selected and combined by software agents. Services ontology provided by Semantic Web enriches the syntactic descriptions of Web services to facilitate the automation of tasks, such as discovery and composition. This work presents an environment for specifying and ad-hoc executing Web services-based business processes, named WebFlowAH. The WebFlowAH employs common domain ontology to describe both Web services and business processes. It allows processes specification in terms of users goals or desires that are expressed based on the concepts of such common domain ontology. This approach allows processes to be specified in an abstract high level way, unburdening the user from the underline details needed to effectively run the process workflow
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Pós-graduação em Ciência da Informação - FFC
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Pós-graduação em Ciência da Informação - FFC
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Este artigo apresenta um estudo experimental de técnicas de identificação paramétrica aplicadas à modelagem dinâmica de um servidor web Apache. Foi desenvolvido um arranjo experimental para simular variações de carga no servidor. O arranjo é composto por dois computadores PC, sendo um deles utilizado para executar o servidor Apache e o outro utilizado como um gerador de carga, solicitando requisições de serviço ao servidor Apache. Foram estimados modelos paramétricos auto-regressivos (AR) para diferentes pontos de operação e de condição de carga. Cada ponto de operação foi definido em termos dos valores médios para o parâmetro de entrada MaxClients (parâmetro utilizado para definir o número máximo de processos ativos) e a saída percentual de consumo de CPU (Central Processing Unit) do servidor Apache. Para cada ponto de operação foram coletadas 600 amostras, com um intervalo de amostragem de 5 segundos. Metade do conjunto de amostras coletadas em cada ponto de operação foi utilizada para estimação do modelo, enquanto que a outra metade foi utilizada para validação. Um estudo da ordem mais adequada do modelo mostrou que, para um ponto de operação com valor reduzido de MaxClients, um modelo AR de 7a ordem pode ser satisfatório. Para valores mais elevados de MaxClients, os resultados mostraram que são necessários modelos de ordem mais elevada, devido às não-linearidades inerentes ao sistema.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)