Matches in ScholarlyData for { ?s ?p ?o. }
- 8 sameAs 8.
- 8 abstract "To-date, the application of high-performance computing resources to Semantic Web data has largely focused on commodity hardware and distributed memory platforms. In this paper we make the case that more specialized hardware can offer superior scaling and close to an order of magnitude improvement in performance. In particular we examine the Cray XMT. Its key characteristics, a large, global sharedmemory, and processors with a memory-latency tolerant design, offer an environment conducive to programming for the Semantic Web and have engendered results that far surpass current state of the art. We examine three fundamental pieces requisite for a fully functioning semantic database: dictionary encoding, RDFS inference, and query processing. We show scaling up to 512 processors (the largest configuration we had available), and the ability to process 20 billion triples completely inmemory.".
- 8 hasAuthorList authorList.
- 8 isPartOf proceedings.
- 8 keyword "Cray XMT".
- 8 keyword "Dictionary Encoding".
- 8 keyword "RDFS Inference".
- 8 keyword "SPARQL".
- 8 keyword "Semantic Web".
- 8 title "High-performance Computing Applied to Semantic Web Databases".
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- item-1 hasContent eric-goodman.
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- item-2 type ListItem.
- item-2 hasContent edward-jimenez.
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- item-3 type ListItem.
- item-3 hasContent david-mizell.
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- item-4 type ListItem.
- item-4 hasContent sinan-al-saffar.
- item-4 next item-5.
- item-4 previous item-3.
- item-5 type ListItem.
- item-5 hasContent bob-adolf.
- item-5 next item-6.
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- item-6 type ListItem.
- item-6 hasContent david-haglin.
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- 3 creator kerry-taylor.
- 3 creator lucas-leidinger.
- 3 type InProceedings.
- 3 label "Ontology-Driven Complex Event Processing in Heterogeneous Sensor Networks".
- 3 sameAs 3.
- 3 abstract "Modern scientific applications of sensor networks are driving the development of technologies to make heterogeneous sensor networks easier to deploy, program and use in multiple application contexts. One key requirement, addressed in this work, is the need for methods to detect events in real time that arise from complex correlations of measurements made by independent sensing devices. Because the mapping of such complex events to direct sensor measurements may be poorly understood, such methods must support experimental and frequent specification of the events of interest. This means that the event specification method must be embedded in the problem domain of the end-user, must support the user to discover observable properties of interest, and must provide automatic and efficient enaction of the specification. This paper proposes the use of ontologies to specify and recognise complex events that arise as selections and correlations (including temporal correlations) of structured digital messages, typically streamed from multiple sensor networks. Ontologies are used as a basis for the definition of contextualised complex events of interest which are translated to selections and temporal combinations of streamed messages. The method is implemented in software built in as a plug-in to Protégé 4.0 that interfaces with a commercial Complex Event Processing (CEP) software package. The interface uses a domain-independent OWL 2.0 ontology of sensed phenomena and events to permit the user to define new events as selections and compositions of the initial events with the ontology providing context for the events. Supported by description logic reasoning, the new event descriptions are translated to the native language of the CEP and executed under the control of the CEP. The software is currently deployed for micro-climate monitoring of experimental crop plants, where precise knowledge and control of growing conditions is needed to map phenotypical traits to the plant genome.".
- 3 hasAuthorList authorList.
- 3 isPartOf proceedings.
- 3 keyword "Phenomics".
- 3 keyword "complex event processing".
- 3 keyword "semantic sensor network".
- 3 keyword "streaming data".
- 3 title "Ontology-Driven Complex Event Processing in Heterogeneous Sensor Networks".
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- item-1 type ListItem.
- item-1 hasContent kerry-taylor.
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- item-2 type ListItem.
- item-2 hasContent lucas-leidinger.
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- 5 creator alasdair-j-g-gray.
- 5 creator alex-frazer.
- 5 creator alvaro-a-a-fernandes.
- 5 creator asuncion-gomez-perez.
- 5 creator david-de-roure.
- 5 creator ixent-galpin.
- 5 creator jason-sadler.
- 5 creator jean-paul-calbimonte.
- 5 creator kevin-page.
- 5 creator kirk-martinez.
- 5 creator kostis-kyzirakos.
- 5 creator manolis-koubarakis.
- 5 creator manos-karpathiotakis.
- 5 creator norman-w-paton.
- 5 creator oscar-corcho.
- 5 creator raul-garcia-castro.
- 5 type InProceedings.
- 5 label "A Semantically Enabled Service Architecture for Mashups over Streaming and Stored Data".
- 5 sameAs 5.
- 5 abstract "Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g. flood emergency response. However, in order to interpret the readings from the sensors, the data needs to be put in context through correlation with other sensor readings, sensor data histories, and stored data, as well as juxtaposing with maps and forecast models. In this paper we use a flood emergency response planning application to identify requirements for a semantic sensor web. We propose a generic service architecture to satisfy the requirements that uses semantic annotations to support well-informed interactions between the services. We present the SemSorGrid4Env realisation of the architecture and illustrate its capabilities in the context of the example application.".
- 5 hasAuthorList authorList.
- 5 isPartOf proceedings.
- 5 keyword "Sensor web architecture".
- 5 keyword "mashups".
- 5 keyword "semantic sensor networks".
- 5 keyword "sensor network ontology".
- 5 keyword "use case".
- 5 title "A Semantically Enabled Service Architecture for Mashups over Streaming and Stored Data".
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