2,158 research outputs found

    The pragmatic proof: hypermedia API composition and execution

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    Machine clients are increasingly making use of the Web to perform tasks. While Web services traditionally mimic remote procedure calling interfaces, a new generation of so-called hypermedia APIs works through hyperlinks and forms, in a way similar to how people browse the Web. This means that existing composition techniques, which determine a procedural plan upfront, are not sufficient to consume hypermedia APIs, which need to be navigated at runtime. Clients instead need a more dynamic plan that allows them to follow hyperlinks and use forms with a preset goal. Therefore, in this paper, we show how compositions of hypermedia APIs can be created by generic Semantic Web reasoners. This is achieved through the generation of a proof based on semantic descriptions of the APIs' functionality. To pragmatically verify the applicability of compositions, we introduce the notion of pre-execution and post-execution proofs. The runtime interaction between a client and a server is guided by proofs but driven by hypermedia, allowing the client to react to the application's actual state indicated by the server's response. We describe how to generate compositions from descriptions, discuss a computer-assisted process to generate descriptions, and verify reasoner performance on various composition tasks using a benchmark suite. The experimental results lead to the conclusion that proof-based consumption of hypermedia APIs is a feasible strategy at Web scale.Peer ReviewedPostprint (author's final draft

    The Use of Ontologies in Contextually Aware Environments

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    In this paper we outline work in progress related to the construction of contextually aware pervasive computing environments, through the use of semantic and knowledge technologies. Key to this activity is modelling both where and what a user is doing at any given time. We present a prototype application to illustrate this work and describe part of its implementation

    Ontology-based semantic interpretation of cylindricity specification in the next-generation GPS

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    Cylindricity specification is one of the most important geometrical specifications in geometrical product development. This specification can be referenced from the rules and examples in tolerance standards and technical handbooks in practice. These rules and examples are described in the form of natural language, which may cause ambiguities since different designers may have different understandings on a rule or an example. To address the ambiguous problem, a categorical data model of cylindricity specification in the next-generation Geometrical Product Specifications (GPS) was proposed at the University of Huddersfield. The modeling language used in the categorical data model is category language. Even though category language can develop a syntactically correct data model, it is difficult to interpret the semantics of the cylindricity specification explicitly. This paper proposes an ontology-based approach to interpret the semantics of cylindricity specification on the basis of the categorical data model. A scheme for translating the category language to the OWL 2 Web Ontology Language (OWL 2) is presented in this approach. Through such a scheme, the categorical data model is translated into a semantically enriched model, i.e. an OWL 2 ontology for cylindricity specification. This ontology can interpret the semantics of cylindricity specification explicitly. As the benefits of such semantic interpretation, consistency checking, inference procedures and semantic queries can be performed on the OWL 2 ontology. The proposed approach could be easily extended to support the semantic interpretations of other kinds of geometrical specifications

    Application of semantic web technologies for automatic multimedia annotation

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    The OCarePlatform : a context-aware system to support independent living

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    Background: Currently, healthcare services, such as institutional care facilities, are burdened with an increasing number of elderly people and individuals with chronic illnesses and a decreasing number of competent caregivers. Objectives: To relieve the burden on healthcare services, independent living at home could be facilitated, by offering individuals and their (in)formal caregivers support in their daily care and needs. With the rise of pervasive healthcare, new information technology solutions can assist elderly people ("residents") and their caregivers to allow residents to live independently for as long as possible. Methods: To this end, the OCarePlatform system was designed. This semantic, data-driven and cloud based back-end system facilitates independent living by offering information and knowledge-based services to the resident and his/her (in)formal caregivers. Data and context information are gathered to realize context-aware and personalized services and to support residents in meeting their daily needs. This body of data, originating from heterogeneous data and information sources, is sent to personalized services, where is fused, thus creating an overview of the resident's current situation. Results: The architecture of the OCarePlatform is proposed, which is based on a service-oriented approach, together with its different components and their interactions. The implementation details are presented, together with a running example. A scalability and performance study of the OCarePlatform was performed. The results indicate that the OCarePlatform is able to support a realistic working environment and respond to a trigger in less than 5 seconds. The system is highly dependent on the allocated memory. Conclusion: The data-driven character of the OCarePlatform facilitates easy plug-in of new functionality, enabling the design of personalized, context-aware services. The OCarePlatform leads to better support for elderly people and individuals with chronic illnesses, who live independently. (C) 2016 Elsevier Ireland Ltd. All rights reserved

    Leveraging Semantic Web Technologies for Managing Resources in a Multi-Domain Infrastructure-as-a-Service Environment

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    This paper reports on experience with using semantically-enabled network resource models to construct an operational multi-domain networked infrastructure-as-a-service (NIaaS) testbed called ExoGENI, recently funded through NSF's GENI project. A defining property of NIaaS is the deep integration of network provisioning functions alongside the more common storage and computation provisioning functions. Resource provider topologies and user requests can be described using network resource models with common base classes for fundamental cyber-resources (links, nodes, interfaces) specialized via virtualization and adaptations between networking layers to specific technologies. This problem space gives rise to a number of application areas where semantic web technologies become highly useful - common information models and resource class hierarchies simplify resource descriptions from multiple providers, pathfinding and topology embedding algorithms rely on query abstractions as building blocks. The paper describes how the semantic resource description models enable ExoGENI to autonomously instantiate on-demand virtual topologies of virtual machines provisioned from cloud providers and are linked by on-demand virtual connections acquired from multiple autonomous network providers to serve a variety of applications ranging from distributed system experiments to high-performance computing
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