9 research outputs found

    Deploying Semantic Web Services-Based Applications in the e-Government Domain

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    Joining up services in e-Government usually implies governmental agencies acting in concert without a central control regime. This requires to the sharing scattered and heterogeneous data. Semantic Web Service (SWS) technology can help to integrate, mediate and reason between these datasets. However, since a few real-world applications have been developed, it is still unclear which are the actual benefits and issues of adopting such a technology in the e-Government domain. In this paper, we contribute to raising awareness of the potential benefits in the e-Government communityby analyzing motivations, requirements and expected results, before proposing a reusable SWS-based framework. We demonstrate the application of this framework by showing how integration and interoperability emerge from this model through a cooperative and multi-viewpoint methodology. Finally, we illustrate added values and lessons learned by two compelling case studies: a change of circumstances notification system and a GIS-based emergency planning system, and describe key challenges which remain to be addressed

    A semantically enriched Hypercat-enabled internet of things data hub

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    Large volumes of data is generated from the increasing num-ber of sensor networks and smart devices. Such data is generated and published in multiple formats, thus highlighting the significance of inter-operability for the success of what has come to be known as the Internet of Things (IoT). The BT Hypercat Data Hub provides a focal point for the sharing and consumption of available datasets from a wide range of sources. In this work, we present a series of optimizations applied on the BT Hypercat Data Hub that enabled scalable SPARQL query answering over relational databases and an access control mechanism that filters SPARQL results based on user's subscriptions.Full Tex

    Optimizing a Semantically Enriched Hypercat-Enabled Internet of Things Data Hub (Short Paper)

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    Large volumes of data is generated from the increasing num-ber of sensor networks and smart devices. Such data is generated and published in multiple formats, thus highlighting the significance of inter-operability for the success of what has come to be known as the Internet of Things (IoT). The BT Hypercat Data Hub provides a focal point for the sharing and consumption of available datasets from a wide range of sources. In this work, we present a series of optimizations applied on the BT Hypercat Data Hub that enabled scalable SPARQL query answering over relational databases and an access control mechanism that filters SPARQL results based on user's subscriptions.Full Tex

    A Semantically Enriched Hypercat-enabled Internet of Things Data Hub

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    A huge amount of information is generated from the rapidly increasing number of sensor networks and smart devices, generating and publishing information in multiple formats, thus highlighting interoperability as one of the key prerequisites for the success of the Internet of Things (IoT). The BT Hypercat Data Hub provides a focal point for the sharing and consumption of available datasets from a wide range of sources. In this work, we present a semantic enrichment of the data hub, using a number of widely-used Semantic Web standards and tools

    A Hypercat-enabled Semantic Internet of Things Data Hub

    No full text
    An increasing amount of information is generated from the rapidly increasing number of sensor networks and smart devices. A wide variety of sources generate and publish information in different formats, thus highlighting interoperability as one of the key prerequisites for the success of Internet of Things (IoT). The BT Hypercat Data Hub provides a focal point for the sharing and consumption of available datasets from a wide range of sources. In this work, we propose a semantic enrichment of the BT Hypercat Data Hub, using well-accepted Semantic Web standards and tools. We propose an ontology that captures the semantics of the imported data and present the BT SPARQL Endpoint by means of a mapping between SPARQL and SQL queries. Furthermore, federated SPARQL queries allow queries over multiple hub-based and external data sources. Finally, we provide two use cases in order to illustrate the advantages afforded by our semantic approach
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