The Fourth Paradigm: Data-Intensive Scientific Discovery Kindle Edition
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The Fourth Paradigm is a collection of papers talks on research areas that aim to improve the research cycle. The talks are a memorial to Microsoft Tech Fellow Jim Gray. Gray had the insight that science has gone through four paradigms so far. The first paradigm, which has lasted over the last few thousand years, was empirical science which describes natural phenomena. Over the last few hindered years, the second paradigm of theoretical science using models and generalizations has occurred. Within the last 50 to 70 years, the third paradigm of computational science has developed to simulate complex phenomena. Finally, the fourth paradigm (also known as eScience) has developed to unify theory, experiment, and simulation. Jim Gray says:"... it is worth distinguishing data-intensive science from computational science as a new, fourth paradigm for scientific exploration."
The book itself is divided into four major sections: Earth and Environment, Health and Wellbeing, Scientific Infrastructure, and Scholarly Communications with 6 to 8 papers per section. The emphasis here is on science; however, I'd assert that all these areas directly impact engineering as well. For example, the flight test of a new product involves an enormous amount of data, which produces much analysis, knowledge, and understanding. The principle idea of eScience (and eEngineering) is that the data and analysis interoperate with each other, such that information is at your fingertips for everyone, everywhere. The payoff is a large increase in information velocity and productivity.Read more ›
It is a very interesting book, made of papers, and a starting point for a vision. Dedicated to a great person and researcher.
I hope that the "Microsoft" tag wouldn't lead someone to ignore it, not always there is a hidden plot, and in this case it's just a book that people working with someone felt to write to honor his work and his memory.
However, all of the papers were top-down overviews. I wanted to dig into some case studies. For example, Microsoft has a working project: World Wide Telescope. How many data sources do they use? How do they blend data from conflicting sources? How do they curate the data? How much telescope gear (and how much computer hardware and software) would I need to contribute? None of the essays went into details on these projects.
Several papers did make some useful, interesting points.
Much of scientific research today is cottage industry: one group puts together some instruments, gathers data, analyzes it, publishes paper. A revolution akin to the industrial revolution will happen: specialized groups will operate instruments and publish data; other groups will analyze the data.
The data repositories of the future must accommodate large numbers of disparate groups gathering data -- and the scientific community must reward them. Data organization, provision of metadata, provenance are all big unsolved questions. (I'd have liked more detailed information here, too).
Some scientific instruments collect data so fast that the bottleneck is no longer data acquisition but data interpretation. Similarly, data repositories are so large that making copies of the dataset is expensive -- it will actually be cheaper for data repositories to offer services where researchers run custom programs against the data.
This high-level overview is grand, but it's hard to test. Surely these pronouncements are based on experience in actual scientific projects. I wanted to read more at this lower level.
Most Recent Customer Reviews
Very timely topic that is explained lucidly for the layman and expert alike.
The book presents the issues in a comprehensive and interesting fashion.
This book is often tedious reading, but it is tedious reading about topics, approaches and philosophies that are essential in the emerging field of data science. Read morePublished on July 4, 2012 by Jeanne D'Arcy
I bought the book for my IPhone. Great book. Enjoyed the price (.99 dls for the Iphone; 39 dollars for the paper back)Published on May 28, 2010 by Carlos Casasus Lopez