Big Scientific Data Management

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Scientific Data Management

Scientific Data Management
Author :
Publisher : Chapman and Hall/CRC
Total Pages : 0
Release :
ISBN-10 : 1420069802
ISBN-13 : 9781420069808
Rating : 4/5 (808 Downloads)

Book Synopsis Scientific Data Management by : Arie Shoshani

Download or read book Scientific Data Management written by Arie Shoshani and published by Chapman and Hall/CRC. This book was released on 2009-12-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dealing with the volume, complexity, and diversity of data currently being generated by scientific experiments and simulations often causes scientists to waste productive time. Scientific Data Management: Challenges, Technology, and Deployment describes cutting-edge technologies and solutions for managing and analyzing vast amounts of data, helping scientists focus on their scientific goals. The book begins with coverage of efficient storage systems, discussing how to write and read large volumes of data without slowing the simulation, analysis, or visualization processes. It then focuses on the efficient data movement and management of storage spaces and explores emerging database systems for scientific data. The book also addresses how to best organize data for analysis purposes, how to effectively conduct searches over large datasets, how to successfully automate multistep scientific process workflows, and how to automatically collect metadata and lineage information. This book provides a comprehensive understanding of the latest techniques for managing data during scientific exploration processes, from data generation to data analysis. Enhanced by numerous detailed color images, it includes real-world examples of applications drawn from biology, ecology, geology, climatology, and more. Check out Dr. Shoshani discuss the book during an interview with International Science Grid This Week (iSGTW): http://www.isgtw.org/?pid=1002259


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"This book discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data"--Provi