Data Provenance and Data Management in eScience: Studies in Computational Intelligence, cartea 426
Editat de Qing Liu, Quan Bai, Stephen Giugni, Darrell Williamson, John Tayloren Limba Engleză Hardback – 4 aug 2012
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.
Toate formatele și edițiile | Preț | Express |
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Paperback (1) | 552.12 lei 38-44 zile | |
Springer Berlin, Heidelberg – 20 sep 2014 | 552.12 lei 38-44 zile | |
Hardback (1) | 562.85 lei 38-44 zile | |
Springer Berlin, Heidelberg – 4 aug 2012 | 562.85 lei 38-44 zile |
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Specificații
ISBN-13: 9783642299308
ISBN-10: 364229930X
Pagini: 190
Ilustrații: XII, 184 p.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.45 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 364229930X
Pagini: 190
Ilustrații: XII, 184 p.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.45 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Provenance Model for Randomized Controlled Trials.- Evaluating Workflow Trust Using Hidden Markov Modeling and Provenance Data.- Unmanaged Workflows: Their Provenance and Use.- Sketching Distributed Data Provenance.- A Mobile Cloud with Trusted Data Provenance Services for Bioinformatics Research.- Data Provenance and Management in Radio Astronomy: A Stream Computing Approach.- Using Provenance to Support Good Laboratory Practice in Grid Environments.
Recenzii
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 be particularly useful for researchers in the area of data provenance, as well as for those in data management in the application domains covered in the book.” (Sergio Ilarri, Computing Reviews, April, 2013)
“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 be particularly useful for researchers in the area of data provenance, as well as for those in data management in the application domains covered in the book.” (Sergio Ilarri, Computing Reviews, April, 2013)
Textul de pe ultima copertă
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.
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.
Caracteristici
Recent research on Data Provenance and Data Management for eScience How to use advanced semantic and AI techniques to track and manage information which describe the life cycle of data items and products Written by leading experts in the field