Dissertation/Thesis
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M.: A native and adaptive approach for unified processing of linked streams and linked data

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: M.: A native and adaptive approach for unified processing of linked streams and linked data
Συγγραφείς: Danh Le-phuoc, Minh Dao-tran, Josiane Xavier Parreira, Manfred Hauswirth
Συνεισφορές: The Pennsylvania State University CiteSeerX Archives
Πηγή: http://iswc2011.semanticweb.org/fileadmin/iswc/Papers/Research_Paper/05/70310368.pdf.
Έτος έκδοσης: 2010
Συλλογή: CiteSeerX
Θεματικοί όροι: Linked Streams, RDF Streams, Linked Data, stream processing, dynamic query planning
Περιγραφή: In this paper we address the problem of scalable, native and adaptive query processing over Linked Stream Data integrated with Linked Data. Linked Stream Data consists of data generated by stream sources, e.g., sensors, enriched with semantic descriptions, following the standards proposed for Linked Data. This enables the integration of stream data with Linked Data collections and facilitates a wide range of novel applications. Currently available systems use a “black box ” approach which delegates the processing to other engines such as stream/event processing engines and SPARQL query processors by translating to their provided languages. As the experimental results described in this paper show, the need for query translation and data transformation, as well as the lack of full control over the query execution, pose major drawbacks in terms of efficiency. To remedy these drawbacks, we present CQELS (Continuous Query Evaluation over Linked Streams), a native and adaptive query processor for unified query processing over Linked Stream Data and Linked Data. In contrast to the existing systems, CQELS uses a “white box ” approach and implements the required query operators natively to avoid the overhead and limitations of closed system regimes. CQELS provides
Τύπος εγγράφου: Thesis
Περιγραφή αρχείου: application/pdf
Γλώσσα: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.361.1369; http://iswc2011.semanticweb.org/fileadmin/iswc/Papers/Research_Paper/05/70310368.pdf
Διαθεσιμότητα: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.361.1369
http://iswc2011.semanticweb.org/fileadmin/iswc/Papers/Research_Paper/05/70310368.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Αριθμός Καταχώρησης: edsbas.1C3BCF84
Βάση Δεδομένων: BASE
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  – Url: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.361.1369#
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PubType: Dissertation/Thesis
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  Data: M.: A native and adaptive approach for unified processing of linked streams and linked data
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  Data: <searchLink fieldCode="AR" term="%22Danh+Le-phuoc%22">Danh Le-phuoc</searchLink><br /><searchLink fieldCode="AR" term="%22Minh+Dao-tran%22">Minh Dao-tran</searchLink><br /><searchLink fieldCode="AR" term="%22Josiane+Xavier+Parreira%22">Josiane Xavier Parreira</searchLink><br /><searchLink fieldCode="AR" term="%22Manfred+Hauswirth%22">Manfred Hauswirth</searchLink>
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  Data: The Pennsylvania State University CiteSeerX Archives
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  Data: <i>http://iswc2011.semanticweb.org/fileadmin/iswc/Papers/Research_Paper/05/70310368.pdf</i>.
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  Data: 2010
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  Data: <searchLink fieldCode="DE" term="%22Linked+Streams%22">Linked Streams</searchLink><br /><searchLink fieldCode="DE" term="%22RDF+Streams%22">RDF Streams</searchLink><br /><searchLink fieldCode="DE" term="%22Linked+Data%22">Linked Data</searchLink><br /><searchLink fieldCode="DE" term="%22stream+processing%22">stream processing</searchLink><br /><searchLink fieldCode="DE" term="%22dynamic+query+planning%22">dynamic query planning</searchLink>
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  Label: Description
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  Data: In this paper we address the problem of scalable, native and adaptive query processing over Linked Stream Data integrated with Linked Data. Linked Stream Data consists of data generated by stream sources, e.g., sensors, enriched with semantic descriptions, following the standards proposed for Linked Data. This enables the integration of stream data with Linked Data collections and facilitates a wide range of novel applications. Currently available systems use a “black box ” approach which delegates the processing to other engines such as stream/event processing engines and SPARQL query processors by translating to their provided languages. As the experimental results described in this paper show, the need for query translation and data transformation, as well as the lack of full control over the query execution, pose major drawbacks in terms of efficiency. To remedy these drawbacks, we present CQELS (Continuous Query Evaluation over Linked Streams), a native and adaptive query processor for unified query processing over Linked Stream Data and Linked Data. In contrast to the existing systems, CQELS uses a “white box ” approach and implements the required query operators natively to avoid the overhead and limitations of closed system regimes. CQELS provides
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  Data: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.361.1369<br />http://iswc2011.semanticweb.org/fileadmin/iswc/Papers/Research_Paper/05/70310368.pdf
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      – Text: English
    Subjects:
      – SubjectFull: Linked Streams
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      – SubjectFull: RDF Streams
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      – SubjectFull: Linked Data
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      – SubjectFull: stream processing
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      – SubjectFull: dynamic query planning
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      – TitleFull: M.: A native and adaptive approach for unified processing of linked streams and linked data
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            NameFull: Danh Le-phuoc
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            NameFull: Minh Dao-tran
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            NameFull: Josiane Xavier Parreira
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            NameFull: Manfred Hauswirth
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            NameFull: The Pennsylvania State University CiteSeerX Archives
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              Y: 2010
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