Scientific Data Management

Challenges, Technology, and Deployment
1. Auflage 2019
ISBN: 978-0-367-38476-0
Verlag: Taylor & Francis Ltd (Sales)

Buch, Englisch, 592 Seiten, Format (B × H): 154 mm x 227 mm, Gewicht: 974 g

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

Zielgruppe

Professional Practice & Development

Autoren/Hrsg.

Shoshani, Arie

Rotem, Doron

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

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.

Über Autor(innen)

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.