Data-intensive Science (chapman & Hall/crc Computational Science)
by Terence Critchlow /
2013 / English / PDF
39 MB Download
Data-intensive 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,
Data-intensive 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,Data-Intensive Science
Data-Intensive 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 world’s most challenging
problems.
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 world’s most challenging
problems.
In the book, a diverse cross-section of application, computer,
and data scientists explores the impact of data-intensive science
on current research and describes emerging technologies that will
enable future scientific breakthroughs. The book identifies best
practices used to tackle challenges facing data-intensive science
as well as gaps in these approaches. It also focuses on the
integration of data-intensive science into standard research
practice, explaining how components in the data-intensive science
environment need to work together to provide the necessary
infrastructure for community-scale scientific collaborations.
In the book, a diverse cross-section of application, computer,
and data scientists explores the impact of data-intensive science
on current research and describes emerging technologies that will
enable future scientific breakthroughs. The book identifies best
practices used to tackle challenges facing data-intensive science
as well as gaps in these approaches. It also focuses on the
integration of data-intensive science into standard research
practice, explaining how components in the data-intensive science
environment need to work together to provide the necessary
infrastructure for community-scale scientific collaborations.
Organizing the material based on a high-level, data-intensive
science workflow, this book provides an understanding of the
scientific problems that would benefit from collaborative
research, the current capabilities of data-intensive science, and
the solutions to enable the next round of scientific
advancements.
Organizing the material based on a high-level, data-intensive
science workflow, this book provides an understanding of the
scientific problems that would benefit from collaborative
research, the current capabilities of data-intensive science, and
the solutions to enable the next round of scientific
advancements.