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Dataintensive science has the potential to transform scientific research and quickly translate scientific progress into complete solutions, policies, and economic success. But this collaborative science is still lacking the effective access and exchange of knowledge among scientists, researchers, and policy makers across a range of disciplines. Bringing together leaders from multiple scientific disciplines, DataIntensive Science shows how a comprehensive integration of various techniques and technological advances can effectively harness the vast amount of data being generated and significantly accelerate scientific progress to address some of the worlds most challenging problems.In the book, a diverse crosssection of application, computer, and data scientists explores the impact of dataintensive science on current research and describes emerging technologies that will enable future scientific breakthroughs. The book identifies best practices used to tackle challenges facing dataintensive science as well as gaps in these approaches. It also focuses on the integration of dataintensive science into standard research practice, explaining how components in the dataintensive science environment need to work together to provide the necessary infrastructure for communityscale scientific collaborations.Organizing the material based on a highlevel, dataintensive science workflow, this book provides an understanding of the scientific problems that would benefit from collaborative research, the current capabilities of dataintensive science, and the solutions to enable the next round of scientific advancements.
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