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Data provenance and data management in eScience

Autor: Qing Liu; et al
Editorial: Berlin ; New York : Springer, ©2013.
Serie: Studies in computational intelligence, 426.
Edición/Formato:   Libro-e : Documento : Inglés (eng)Ver todas las ediciones y todos los formatos
Base de datos:WorldCat
Resumen:
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  Leer más
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Detalles

Género/Forma: Electronic books
Databases
Tipo de material: Documento, Recurso en Internet
Tipo de documento: Recurso en Internet, Archivo de computadora
Todos autores / colaboradores: Qing Liu; et al
ISBN: 9783642299315 3642299318 364229930X 9783642299308
Número OCLC: 805947540
Descripción: 1 online resource.
Contenido: 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.
Título de la serie: Studies in computational intelligence, 426.
Responsabilidad: Qing Liu...[et al.] (eds.).

Resumen:

The highly distributed scientific research enabled by 'escience' features complex interactions in its infrastructure and thus needs strong data provenance and management systems. This book explains  Leer más

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From the reviews: "This book, a compilation of independent chapters, reflects the research work of several groups in the field of data provenance and data management for eScience. ... the book will Leer más

 
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