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Data Provenance and Data Management in eScience
ISBN-13:
9783642299315
Veröffentl:
2012
Seiten:
184
Autor:
Qing Liu
Serie:
426, Studies in Computational Intelligence
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
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.
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.
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