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Scientific Data Management: Challenges, Technology, and Deployment (Chapman & Hall/CRC Computational Science) [Hardcover]

by Arie Shoshani, Doron Rotem
5.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

December 16, 2009 1420069802 978-1420069808 0

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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Editorial Reviews

Review

"… Each chapter contains insights and experience gleaned by experts and luminaries in storage who are confronting and managing the data tsunami that has now inundated the leading-edge scientific and supercomputing centers around the world. Individuals in a variety of scientific and commercial areas who are struggling to manage large amounts of data should find this book both educational and useful."
—Ron Farber, Scientific Computing, 2010

About the Author

Arie Shoshani is a senior staff scientist at Lawrence Berkeley National Laboratory, where he heads the Scientific Data Management Research Group. Dr. Shoshani is also the director of the Scientific Data Management Center, one of several large computer science centers supported by the SciDAC program of the U.S. Department of Energy.

Doron Rotem is a senior staff scientist at Lawrence Berkeley National Laboratory, where he heads the research program on scientific data management.


Product Details

  • Series: Chapman & Hall/CRC Computational Science
  • Hardcover: 590 pages
  • Publisher: Chapman and Hall/CRC (December 16, 2009)
  • Language: English
  • ISBN-10: 1420069802
  • ISBN-13: 978-1420069808
  • Product Dimensions: 9.3 x 6.1 x 1.4 inches
  • Shipping Weight: 2.2 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,101,403 in Books (See Top 100 in Books)

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1 of 2 people found the following review helpful
5.0 out of 5 stars Excellent survey January 25, 2011
Format:Hardcover
Excellent survey of methods and tools to manage massive amounts of scientific data. The chapter "Metadata and Provenance Management" is particularly helpful since this is an area my workgroup has been weak in.

Contents
List of Figures
List of Tables
Acknowledgments
Contributors
Introduction
Part I: Storage Technology and Efficient Storage Access
Chapter 1. Storage Technology
Chapter 2. Parallel Data Storage and Access
Chapter 3. Dynamic Storage Management
Part II: Data Transfer and Scheduling
Chapter 4. Coordination of Access to Large-Scale Datasets in Distributed Environments
Chapter 5. High Throughput Data Movement
Part III: Specialized Retrieval Techniques and Database Systems
Chapter 6. Accelerating Queries on Very Large Datasets
Chapter 7. Emerging Database Systems in Support of Scientific Data
Part IV: Data Analysis, Integration, and Visualization Methods
Chapter 8. Scientific Data Analysis*
Chapter 9. Scientific Data Management Challenges in High-Performance Visual Data Analysis
Chapter 10. Interoperability and Data Integration in the Geosciences
Chapter 11. Analyzing Data Streams in Scientific Applications*
Part V: Scientific Process Management
Chapter 12. Metadata and Provenance Management
Chapter 13. Scientific Process Automation and Workflow Management
Conclusions and Future Outlook
Index
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