The Fourth Paradigm: Data-intensive Scientific DiscoveryAnthony J. G. Hey, Stewart Tansley, Kristin Michele Tolle This book presents the first broad look at the rapidly emerging field of data-intensive science, with the goal of influencing the worldwide scientific and computing research communities and inspiring the next generation of scientists. Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud-computing technologies. This collection of essays expands on the vision of pioneering computer scientist Jim Gray for a new, fourth paradigm of discovery based on data-intensive science and offers insights into how it can be fully realized. |
Contents
INTRODUCTION Dan | 3 |
REDEFINING ECOLOGICAL SCIENCE USING DATA | 21 |
DISCOVERIES IN THE DATA DELUGE | 39 |
Copyright | |
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ability algorithms allow analyze applications approach archiving astronomers automated behavior biological brain capture challenges climate change clinical cloud cloud computing collaboration collection complex computer science created curation cyberinfrastructure data analysis data deluge data management data-centric data-intensive science database datasets discovery disease distributed domain EARTH AND ENVIRONMENT ecological Electronic Health Records emerging enable engine environmental eScience example exploration Figure fourth paradigm genome global Harry Pearce healthcare human images individual infrastructure integration interactions interface Internet Jim Gray Large Hadron Collider large-scale machine learning MapReduce Mark Stoermer Medicine metadata Microsoft Research million models National neurons next-generation nodes NxKM Pan-STARRS parallel patient petabytes potential processes programming projects PubMed Central queries real-time scale scholarly communication scientists semantic Semantic Web sensor sequence simulations snow Szalay technologies telescope terabytes tion understanding University users visualization workflows