科学データ管理<br>Scientific Data Management : Challenges, Technology, and Deployment

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科学データ管理
Scientific Data Management : Challenges, Technology, and Deployment

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  • 製本 Hardcover:ハードカバー版/ページ数 590 p.
  • 言語 ENG
  • 商品コード 9781420069808
  • DDC分類 502.8

基本説明

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.

Full Description

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

Contents

Storage Technology and Efficient Storage Access. Data Transfer and Scheduling. Specialized Retrieval Techniques and Database Systems. Data Analysis, Integration, and Visualization Methods. Scientific Process Management. Conclusions and Future Outlook. Index.

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