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" Data provenance and data management in eScience "
Qing Liu [and others] (eds.).
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BL
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| Record Number
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747467
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b567418
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| Main Entry
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Qing Liu [and others] (eds.).
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| Title & Author
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Data provenance and data management in eScience\ Qing Liu [and others] (eds.).
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| Publication Statement
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Berlin ; New York : Springer, ©2013.
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| Series Statement
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Studies in computational intelligence, 426.
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| ISBN
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364229930X
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: 3642299318
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: 9783642299308
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: 9783642299315
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| Contents
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Provenance Model for Randomized Controlled Trials / Vasa Curcin, Roxana Danger, Wolfgang Kuchinke, Simon Miles and Adel Taweel, et al. --; Evaluating Workflow Trust Using Hidden Markov Modeling and Provenance Data / Mahsa Naseri and Simone A. Ludwig --; Unmanaged Workflows: Their Provenance and Use / Mehmet S. Aktas, Beth Plale, David Leake and Nirmal K. Mukhi --; Sketching Distributed Data Provenance / Tanu Malik, Ashish Gehani, Dawood Tariq and Fareed Zaffar --; A Mobile Cloud with Trusted Data Provenance Services for Bioinformatics Research / Jinhui Yao, Jingyu Zhang, Shiping Chen, Chen Wang and David Levy, et al. --; Data Provenance and Management in Radio Astronomy: A Stream Computing Approach / Mahmoud S. Mahmoud, Andrew Ensor, Alain Biem, Bruce Elmegreen and Sergei Gulyaev --; Using Provenance to Support Good Laboratory Practice in Grid Environments / Miriam Ney, Guy K. Kloss and Andreas Schreiber.
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| Abstract
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EScience allows scientific research to be carried out in highly distributed environments. The complex nature of the interactions in an eScience infrastructure, which often involves a range of instruments, data, models, applications, people and computational facilities, suggests there is a need for data provenance and data management (DPDM). The W3C Provenance Working Group defines the provenance of a resource as a "record that describes entities and processes involved in producing and delivering or otherwise influencing that resource". It has been widely recognised that provenance is a critical issue to enable sharing, trust, authentication and reproducibility of eScience process. Data Provenance and Data Management in eScience identifies the gaps between DPDM foundations and their practice within eScience domains including clinical trials, bioinformatics and radio astronomy. The book covers important aspects of fundamental research in DPDM including provenance representation and querying. It also explores topics that go beyond the fundamentals including applications. This book is a unique reference for DPDM with broad appeal to anyone interested in the practical issues of DPDM in eScience domains.
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Database Management Systems.
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Database management.
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Science -- Databases.
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| LC Classification
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Q224.5Q645 2013
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Qing Liu
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