1,801 research outputs found

    A Geospatial Service Model and Catalog for Discovery and Orchestration

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    The goal of this research is to provide a supporting Web services architecture, consisting of a service model and catalog, to allow discovery and automatic orchestration of geospatial Web services. First, a methodology for supporting geospatial Web services with existing orchestration tools is presented. Geospatial services are automatically translated into SOAP/WSDL services by a portable service wrapper. Their data layers are exposed as atomic functions while WSDL extensions provide syntactic metadata. Compliant services are modeled using the descriptive logic capabilities of the Ontology Language for the Web (OWL). The resulting geospatial service model has a number of functions. It provides a basic taxonomy of geospatial Web services that is useful for templating service compositions. It also contains the necessary annotations to allow discovery of services. Importantly, the model defines a number of logical relationships between its internal concepts which allow inconsistency detection for the model as a whole and for individual service instances as they are added to the catalog. These logical relationships have the additional benefit of supporting automatic classification of geospatial services individuals when they are added to the service catalog. The geospatial service catalog is backed by the descriptive logic model. It supports queries which are more complex that those available using standard relational data models, such as the capability to query using concept hierarchies. An example orchestration system demonstrates the use of the geospatial service catalog for query evaluation in an automatic orchestration system (both fully and semi-automatic orchestration). Computational complexity analysis and experimental performance analysis identify potential performance problems in the geospatial service catalog. Solutions to these performance issues are presented in the form of partitioning service instance realization, low cost pre-filtering of service instances, and pre-processing realization. The resulting model and catalog provide an architecture to support automatic orchestration capable of complementing the multiple service composition algorithms that currently exist. Importantly, the geospatial service model and catalog go beyond simply supporting orchestration systems. By providing a general solution to the modeling and discovery of geospatial Web services they are useful in any geospastial Web service enterprise

    Web Service Discovery in the FUSION Semantic Registry

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    The UDDI specification was developed as an attempt to address the key challenge of effective Web service discovery and has become a widely adopted standard. However, the text-based indexing and search mechanism that UDDI registries offer does not suffice for expressing unambiguous and semantically rich representations of service capabilities, and cannot support the logic-based inference capacity required for facilitating automated service matchmaking. This paper provides an overview of the approach put forward in the FUSION project for overcoming this important limitation. Our solution combines SAWSDL-based service descriptions with service capability profiling based on OWL-DL, and automated matchmaking through DL reasoning in a semantically extended UDDI registry

    Estimating Fire Weather Indices via Semantic Reasoning over Wireless Sensor Network Data Streams

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    Wildfires are frequent, devastating events in Australia that regularly cause significant loss of life and widespread property damage. Fire weather indices are a widely-adopted method for measuring fire danger and they play a significant role in issuing bushfire warnings and in anticipating demand for bushfire management resources. Existing systems that calculate fire weather indices are limited due to low spatial and temporal resolution. Localized wireless sensor networks, on the other hand, gather continuous sensor data measuring variables such as air temperature, relative humidity, rainfall and wind speed at high resolutions. However, using wireless sensor networks to estimate fire weather indices is a challenge due to data quality issues, lack of standard data formats and lack of agreement on thresholds and methods for calculating fire weather indices. Within the scope of this paper, we propose a standardized approach to calculating Fire Weather Indices (a.k.a. fire danger ratings) and overcome a number of the challenges by applying Semantic Web Technologies to the processing of data streams from a wireless sensor network deployed in the Springbrook region of South East Queensland. This paper describes the underlying ontologies, the semantic reasoning and the Semantic Fire Weather Index (SFWI) system that we have developed to enable domain experts to specify and adapt rules for calculating Fire Weather Indices. We also describe the Web-based mapping interface that we have developed, that enables users to improve their understanding of how fire weather indices vary over time within a particular region.Finally, we discuss our evaluation results that indicate that the proposed system outperforms state-of-the-art techniques in terms of accuracy, precision and query performance.Comment: 20pages, 12 figure

    A MULTI-FUNCTIONAL PROVENANCE ARCHITECTURE: CHALLENGES AND SOLUTIONS

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    In service-oriented environments, services are put together in the form of a workflow with the aim of distributed problem solving. Capturing the execution details of the services' transformations is a significant advantage of using workflows. These execution details, referred to as provenance information, are usually traced automatically and stored in provenance stores. Provenance data contains the data recorded by a workflow engine during a workflow execution. It identifies what data is passed between services, which services are involved, and how results are eventually generated for particular sets of input values. Provenance information is of great importance and has found its way through areas in computer science such as: Bioinformatics, database, social, sensor networks, etc. Current exploitation and application of provenance data is very limited as provenance systems started being developed for specific applications. Thus, applying learning and knowledge discovery methods to provenance data can provide rich and useful information on workflows and services. Therefore, in this work, the challenges with workflows and services are studied to discover the possibilities and benefits of providing solutions by using provenance data. A multifunctional architecture is presented which addresses the workflow and service issues by exploiting provenance data. These challenges include workflow composition, abstract workflow selection, refinement, evaluation, and graph model extraction. The specific contribution of the proposed architecture is its novelty in providing a basis for taking advantage of the previous execution details of services and workflows along with artificial intelligence and knowledge management techniques to resolve the major challenges regarding workflows. The presented architecture is application-independent and could be deployed in any area. The requirements for such an architecture along with its building components are discussed. Furthermore, the responsibility of the components, related works and the implementation details of the architecture along with each component are presented

    Semantic Driven Approach for Rapid Application Development in Industrial Internet of Things

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    The evolution of IoT has revolutionized industrial automation. Industrial devices at every level such as field devices, control devices, enterprise level devices etc., are connected to the Internet, where they can be accessed easily. It has significantly changed the way applications are developed on the industrial automation systems. It led to the paradigm shift where novel IoT application development tools such as Node-RED can be used to develop complex industrial applications as IoT orchestrations. However, in the current state, these applications are bound strictly to devices from specific vendors and ecosystems. They cannot be re-used with devices from other vendors and platforms, since the applications are not semantically interoperable. For this purpose, it is desirable to use platform-independent, vendor-neutral application templates for common automation tasks. However, in the current state in Node-RED such reusable and interoperable application templates cannot be developed. The interoperability problem at the data level can be addressed in IoT, using Semantic Web (SW) technologies. However, for an industrial engineer or an IoT application developer, SW technologies are not very easy to use. In order to enable efficient use of SW technologies to create interoperable IoT applications, novel IoT tools are required. For this purpose, in this paper we propose a novel semantic extension to the widely used Node-RED tool by introducing semantic definitions such as iot.schema.org semantic models into Node-RED. The tool guides a non-expert in semantic technologies such as a device vendor, a machine builder to configure the semantics of a device consistently. Moreover, it also enables an engineer, IoT application developer to design and develop semantically interoperable IoT applications with minimal effort. Our approach accelerates the application development process by introducing novel semantic application templates called Recipes in Node-RED. Using Recipes, complex application development tasks such as skill matching between Recipes and existing things can be automated.We will present the approach to perform automated skill matching on the Cloud or on the Edge of an automation system. We performed quantitative and qualitative evaluation of our approach to test the feasibility and scalability of the approach in real world scenarios. The results of the evaluation are presented and discussed in the paper.Die Entwicklung des Internet der Dinge (IoT) hat die industrielle Automatisierung revolutioniert. Industrielle Geräte auf allen Ebenen wie Feldgeräte, Steuergeräte, Geräte auf Unternehmensebene usw. sind mit dem Internet verbunden, wodurch problemlos auf sie zugegriffen werden kann. Es hat die Art und Weise, wie Anwendungen auf industriellen Automatisierungssystemen entwickelt werden, deutlich verändert. Es führte zum Paradigmenwechsel, wo neuartige IoT Anwendungsentwicklungstools, wie Node-RED, verwendet werden können, um komplexe industrielle Anwendungen als IoT-Orchestrierungen zu entwickeln. Aktuell sind diese Anwendungen jedoch ausschließlich an Geräte bestimmter Anbieter und Ökosysteme gebunden. Sie können nicht mit Geräten anderer Anbieter und Plattformen verbunden werden, da die Anwendungen nicht semantisch interoperabel sind. Daher ist es wünschenswert, plattformunabhängige, herstellerneutrale Anwendungsvorlagen für allgemeine Automatisierungsaufgaben zu verwenden. Im aktuellen Status von Node-RED können solche wiederverwendbaren und interoperablen Anwendungsvorlagen jedoch nicht entwickelt werden. Diese Interoperabilitätsprobleme auf Datenebene können im IoT mithilfe von Semantic Web (SW) -Technologien behoben werden. Für Ingenieure oder Entwickler von IoT-Anwendungen sind SW-Technologien nicht sehr einfach zu verwenden. Zur Erstellung interoperabler IoT-Anwendungen sind daher neuartige IoT-Tools erforderlich. Zu diesem Zweck schlagen wir eine neuartige semantische Erweiterung des weit verbreiteten Node-RED-Tools vor, indem wir semantische Definitionen wie iot.schema.org in die semantischen Modelle von NODE-Red einführen. Das Tool leitet einen Gerätehersteller oder Maschinebauer, die keine Experten in semantische Technologien sind, an um die Semantik eines Geräts konsistent zu konfigurieren. Darüber hinaus ermöglicht es auch einem Ingenieur oder IoT-Anwendungsentwickler, semantische, interoperable IoT-Anwendungen mit minimalem Aufwand zu entwerfen und entwicklen Unser Ansatz beschleunigt die Anwendungsentwicklungsprozesse durch Einführung neuartiger semantischer Anwendungsvorlagen namens Rezepte für Node-RED. Durch die Verwendung von Rezepten können komplexe Anwendungsentwicklungsaufgaben wie das Abgleichen von Funktionen zwischen Rezepten und vorhandenen Strukturen automatisiert werden. Wir demonstrieren Skill-Matching in der Cloud oder am Industrial Edge eines Automatisierungssystems. Wir haben dafür quantitative und qualitative Bewertung unseres Ansatzes durchgeführt, um die Machbarkeit und Skalierbarkeit des Ansatzes in realen Szenarien zu testen. Die Ergebnisse der Bewertung werden in dieser Arbeit vorgestellt und diskutiert

    A abordagem POESIA para a integração de dados e serviços na Web semantica

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    Orientador: Claudia Bauzer MedeirosTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: POESIA (Processes for Open-Ended Systems for lnformation Analysis), a abordagem proposta neste trabalho, visa a construção de processos complexos envolvendo integração e análise de dados de diversas fontes, particularmente em aplicações científicas. A abordagem é centrada em dois tipos de mecanismos da Web semântica: workflows científicos, para especificar e compor serviços Web; e ontologias de domínio, para viabilizar a interoperabilidade e o gerenciamento semânticos dos dados e processos. As principais contribuições desta tese são: (i) um arcabouço teórico para a descrição, localização e composição de dados e serviços na Web, com regras para verificar a consistência semântica de composições desses recursos; (ii) métodos baseados em ontologias de domínio para auxiliar a integração de dados e estimar a proveniência de dados em processos cooperativos na Web; (iii) implementação e validação parcial das propostas, em urna aplicação real no domínio de planejamento agrícola, analisando os benefícios e as limitações de eficiência e escalabilidade da tecnologia atual da Web semântica, face a grandes volumes de dadosAbstract: POESIA (Processes for Open-Ended Systems for Information Analysis), the approach proposed in this work, supports the construction of complex processes that involve the integration and analysis of data from several sources, particularly in scientific applications. This approach is centered in two types of semantic Web mechanisms: scientific workflows, to specify and compose Web services; and domain ontologies, to enable semantic interoperability and management of data and processes. The main contributions of this thesis are: (i) a theoretical framework to describe, discover and compose data and services on the Web, inc1uding mIes to check the semantic consistency of resource compositions; (ii) ontology-based methods to help data integration and estimate data provenance in cooperative processes on the Web; (iii) partial implementation and validation of the proposal, in a real application for the domain of agricultural planning, analyzing the benefits and scalability problems of the current semantic Web technology, when faced with large volumes of dataDoutoradoCiência da ComputaçãoDoutor em Ciência da Computaçã

    Blueprint model and language for engineering cloud applications

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    Abstract: The research presented in this thesis is positioned within the domain of engineering CSBAs. Its contribution is twofold: (1) a uniform specification language, called the Blueprint Specification Language (BSL), for specifying cloud services across several cloud vendors and (2) a set of associated techniques, called the Blueprint Manipulation Techniques (BMTs), for publishing, querying, and composing cloud service specifications with aim to support the flexible design and configuration of an CSBA.
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