TY  - BOOK
AU  - Liu,Qing
AU  - Bai,Quan
AU  - Giugni,Stephen
AU  - Williamson,Darrell
AU  - Taylor,John
ED  - SpringerLink (Online service)
TI  - Data Provenance and Data Management in eScience
T2  - Studies in Computational Intelligence,
SN  - 9783642299315
AV  - TA1-2040 
U1  - 620 23
PY  - 2013///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Engineering
KW  - Artificial intelligence
KW  - Engineering, general
KW  - Artificial Intelligence (incl. Robotics)
N1  - 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
N2  - 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
UR  - http://dx.doi.org/10.1007/978-3-642-29931-5
ER  -