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

Autorentext
Toby Segaran is the author of Programming Collective Intelligence, a very popular O'Reilly title. He was the founder of Incellico, a biotech software company later acquired by Genstruct. He currently holds the title of Data Magnate at Metaweb Technologies and is a frequent speaker at technology conferences.

Klappentext
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

Zusammenfassung
Helps you explore the opportunities and challenges involved in working with the many number of datasets made available by the Web. This book also helps you learn how to visualize trends in urban crime, using maps and data mashups, and discover the challenges of designing a data processing system that works within the constraints of space travel.

Inhalt
Dedication Preface Chapter 1: Seeing Your Life in Data Chapter 2: The Beautiful People: Keeping Users in Mind When Designing Data Collection Methods Chapter 3: Embedded Image Data Processing on Mars Chapter 4: Cloud Storage Design in a PNUTShell Chapter 5: Information Platforms and the Rise of the Data Scientist Chapter 6: The Geographic Beauty of a Photographic Archive Chapter 7: Data Finds Data Chapter 8: Portable Data in Real Time Chapter 9: Surfacing the Deep Web Chapter 10: Building Radiohead's House of Cards Chapter 11: Visualizing Urban Data Chapter 12: The Design of Sense.us Chapter 13: What Data Doesn't Do Chapter 14: Natural Language Corpus Data Chapter 15: Life in Data: The Story of DNA Chapter 16: Beautifying Data in the Real World Chapter 17: Superficial Data Analysis: Exploring Millions of Social Stereotypes Chapter 18: Bay Area Blues: The Effect of the Housing Crisis Chapter 19: Beautiful Political Data Chapter 20: Connecting Data Contributors COLOPHON

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