Quan Bai & Stephen Giugni 
Data Provenance and Data Management in eScience [PDF ebook] 

Supporto

e Science allows scientific research to be carried out in highly distributed environments. The complex nature of the interactions in an e Science infrastructure, which often involves a range of instruments, data, models, application, 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 e Science process. Data Provenance and Data Management in e Science identifies the gaps between DPDM foundations and their practice within e Science 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 e Science domains.

€115.37
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Lingua Inglese ● Formato PDF ● ISBN 9783642299315 ● Editore Quan Bai & Stephen Giugni ● Casa editrice Springer Berlin Heidelberg ● Pubblicato 2012 ● Scaricabile 3 volte ● Moneta EUR ● ID 6322862 ● Protezione dalla copia Adobe DRM
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