The Fourth Paradigm: Data-Intensive Scientific Discovery

by Tony Hey

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.

Genres: Science, Technology, Nonfiction, Computer Science, Technical

284 pages, Kindle Edition

First published October 1, 2009

Reviews

[Albert · Rating 4 out of 5]

A broad and low tech survey of research in the golden age of data. Since no reader is likely to know all of these domains, there is surely something to be learned. The price can't be beat; the eBook is free online from Microsoft.

[Max Hager · Rating 5 out of 5]

1. Foster both the development of software tools and support for these tools.
2. Invest in tools at all levels of the funding pyramid.
3. Foster the development of generic Laboratory Information Management
Systems (LIMS).
4. Foster research into scientific data management, data analysis, data visualiza-
tion, and new algorithms and tools.
5. Establish digital libraries that support other sciences in the same way the National Library of Medicine supports the bio-sciences.
6. Foster the development of new document authoring tools and publication models.
7. Foster the development of digital data libraries that contain scientific data (not just the metadata) and support integration with published literature.

(from the book)

[Cassandra Lee Yieng]

This book is sobering, especially in light of global crises. It's also brimming with confidence regarding data-intensive computing for all fields. Not sure if caution should rather be exercised.

[Ed Terrell · Rating 5 out of 5]

"Scientists are generally doing one of two things: looking for needles in haystacks or looking for the haystacks themselves…” Jim Gray

“Find me the daily river flow and suspended sediment discharge data from all watersheds Washington state with more than 30 inches of annual rainfall”
The Fourth Paradigm

The Fourth Paradigm is a collection of essays on data intensive science. They follow, both intimately and broadly, Jim Gray’s 2007 NRC talk on the need for new tools for data capture, curation, analysis and visualization. These papers cover the environment, health, our scientific infrastructure and scientific communication.

Theory and experimentation merged with computer modeling to provide the scientific platform that we know today. The continuing success of Moore’s law on semiconductor speed has resulted in nothing short of a deluge of data from embedded sensors, large scientific projects as well as from the proliferation of everyday computers and phones. How we ultimately deal with this data is the Fourth Paradigm.

At it's heart is the open access and open science needed to maximize benefits to society. The problems are enormous not just due to the sheer amounts of data (sometimes terabytes from single experiments) but also the heterogeneity of the datasets. Computer scientists spend 80% of their time deciphering data into correctly parsed formats. New data analysis and visualization tools are being created. More tools are needed. Many scientists rely solely on Excel and Matlab with higher capable programming platforms out of reach due to long learning curves. Another major hurdle is the need for the files to be self describing. Today HDF5 files are starting to be used for data interchange and carry their schema with them.

I found The Fourth Paradigm a highly enjoyable read written from a wide variety of perspectives.

[Matt Heavner · Rating 4 out of 5]

This is a collection of papers about the eScience or data-intensive science paradigm from 2009. The collection is an interesting snapshot in time. This book is a mixed bag because it is from diverse set of authors on diverse topics. Some of the papers are very insightful and still quite relevant. Others were insightful but the future has already overcome the paper. One or two of the papers fell flat for me. Disappointingly, the fourthparadigm.org web site to support this collection no longer exists (it is an educational outreach page now). Some of the threads of the collection have flourished, others obviously have not. A good view from the past to take a look at where we are now and where we are going.

[Lara · Rating 4 out of 5]

A nice overview of how science has shifted from data poor to data intensive in the last decades. The book is a collection of essays from various fields detailing how data has enriched and changed various disciplines from health to earth science, and how researchers have dealt with the new problems posed by (dare I say it?) too MUCH data. The final chapters come from computer scientists and from those who are thinking more philosophically how the new data-driven paradigm will change how science is done.

Now, a decade plus after the publication of this book, some of the chapters feel like soothsaying. In particular, the chapters anticipating the time between discovery and adoption of new treatments in light of Covid are prescient. In contrast, the chapters anticipating the changes to academia fell flat as many fields have failed to adopt unifying principles and methods for using data. An interesting read for people, even now, to understand the challenges and exciting opportunities of the data deluge.

[Ooi Ghee Leng · Rating 5 out of 5]

This book will easily top the list of titles I have read this year. It has profoundly changed my perspectives on scientific research. Perhaps for the CS people, there is nothing new to offer but this book offers the first probe into the thinking of highlighting "data" as the chief agent of change we will come to embrace in the coming decade.

If you love science, or you are an engineer, please take some time to leaf through the book if you are not familiar with "the fourth paradigm shift", envisioned by Gray and Szalay by unifying experiments, theory and simulations in the era of data deluge. The way we do science will be utterly different as the technology for data curation, provenance tracking, management and exploration take hold. It's a world you would never have thought about, and it's a truly wonderful place to live in as we harness the new paradigm to combat with climate change and energy deprivation.

[Stephanie · Rating 4 out of 5]

We have lots of data to store and analyze from watersheds to the world wide telescope to DNA. This was an enjoyable collection of short scientific papers all about data. I learned about brainbows, semantic escience, and of course Jim Gray.

[Joshua]

A good conversation starter.

[Oleksandr Nikitin · Rating 3 out of 5]

neat overview of data science written just before the hype started

[Leandro Zanotto · Rating 4 out of 5]

Good book. Reccomend