Data Provenance and Data Management in Escience

ISBN-13: 9783642441585 / Angielski / Miękka / 2014 / 184 str.

Qing Liu; Quan Bai; Stephen Giugni

Opis

This book covers important aspects of fundamental research in data provenance and data management(DPDM), including provenance representation and querying, as well as practical applications in such domains as clinical trials, bioinformatics and radio astronomy.

Recenzje

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)

Spis treści

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.

O autorze

John Taylor ist Bassist und Gründungsmitglied von Duran Duran. Bis heute hat die Band mehr als 80 Millionen Tonträger verkauft und wurde dafür mit sechs Lifetime Achievement Awards belohnt, darunter BRIT- und MTV-Awards. Er lebt mit seiner Frau und den drei Kindern abwechselnd in Wiltshire/England und Los Angeles.

Blurb

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.