Beautiful Data

In this insightful book, you'll learn from the best data practitioners in the field just how wide-ranging -- and beautiful -- working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video.

With Beautiful Data, you will:

• Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web
• Learn how to visualize trends in urban crime, using maps and data mashups
• Discover the challenges of designing a data processing system that works within the constraints of space travel
• Learn how crowdsourcing and transparency have combined to advance the state of drug research
• Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data
• Learn about the massive infrastructure required to create, capture, and process DNA data

That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include:

Nathan Yau

Jonathan Follett and Matt Holm

J.M. Hughes

Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava

Jeff Hammerbacher

Jason Dykes and Jo Wood

Jeff Jonas and Lisa Sokol

Jud Valeski

Alon Halevy and Jayant Madhavan

Aaron Koblin with Valdean Klump

Michal Migurski

Jeff Heer

Coco Krumme

Peter Norvig

Matt Wood and Ben Blackburne

Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen

Lukas Biewald and Brendan O'Connor

Hadley Wickham, Deborah Swayne, and David Poole

Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza

Toby Segaran