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1 SEEINGYOUR LIFE IN DATA&by Nathan Yau1

Personal Environmental Impact Report(PEIR)2

your.flowingdata(YFD)3

Personal Data Collection3

Data Storage5

Data Processing6

Data Visualization7

The Point14

How to Participate15

2 THE BEAUTIFUL PEOPLE:KEEPING USERS IN MIND WHEN DESIGNING DATA COLLECTION METHODS&by Jonathan Follett and Matthew Holm17

Introduction:User Empathy Is the New Black17

The Project:Surveying Customers About a New Luxury P roduct19

Specific Challenges to Data Collection19

Designing Our Solution21

Results and Reflection31

3 EMBEDDED IMAGE DATA PROCESSING ON MARS&by J.M.Hughes35

Abstract35

Introduction35

Some Background37

To Pack or Not to Pack40

The Three Tasks42

Slotting the Images43

Passing the Image:Communication Among the Three Tasks46

Getting the Picture:Image Download and Processing48

Image Compression50

Downlink,or,It's All Downhill from Here52

Conclusion52

4 CLOUD STORAGE DESIGN IN A PNUTSHELL&by Brian F.Cooper,Raghu Ramakrishnan,and Utkarsh Srivastava55

Introduction55

Updating Data57

Complex Queries64

Comparison with Other Systems68

Conclusion71

5 INFORMATION PLATFORMS AND THE RISE OF THE DATA SCIENTIST&by Jeff Hammerbacher73

Libraries and Brains73

Facebook Becomes Self-Aware74

A Business Intelligence System75

The Death and Rebirth of a Data Warehouse77

Beyond the Data Warehouse78

The Cheetah and the Elephant79

The Unreasonable Effectiveness of Data80

New Tools and Applied Research81

MAD Skills and Cosmos82

Information Platforms As Dataspaces83

The Data Scientist83

Conclusion84

6 THE GEOGRAPHIC BEAUTY OF A PHOTOGRAPHIC ARCHIVE&by Jason Dykes and Jo Wood85

Beauty in Data:Geograph86

Visualization,Beauty,and Treemaps89

A Geographic Perspective on Geograph Term Use91

Beauty in Discovery98

Reflection and Conclusion101

7 DATA FINDS DATA&by Jeff Jonas and Lisa Sokol105

Introduction105

The Benefits of Just-in-Time Discovery106

Corruption at the Roulette Wheel107

Enterprise Discoverability111

Federated Search Ain't All That111

Directories:Priceless113

Relevance:What Matters and to Whom?115

Components and Special Considerations115

Privacy Considerations118

Conclusion118

8 PORTABLE DATA IN REAL TIME&by Jud Valeski119

Introduction119

The State of the Art120

Social Data Normalization128

Conclusion:Mediation via GniP131

9 SURFACING THE DEEP WEB&by Alon Halevy and Jayant Madhaven133

What Is the Deep Web?133

Alternatives to Offering Deep-Web Access135

Conclusion and Future Work147

10 BUILDING RADIOHEAD'S HOUSE OF CARDS&by Aaron Koblin with Valdean Klump149

How It All Started149

The Data Capture Equipment150

The Advantages of Two Data Capture Systems154

The Data154

Capturing the Data,aka"The Shoot"155

Processing the Data160

Post-Processing the Data160

Launching the Video161

Conclusion164

11 VISUALIZING URBAN DATA&by Michal Migurski167

Introduction167

Background168

Cracking the Nut169

Making It Public174

Revisiting178

Conclusion181

12 THE DESIGN OF SENSE.US&by Jeffrey Heer183

Visualization and Social Data Analysis184

Data186

Visualization188

Collaboration194

Voyagers and Voyeurs199

Conclusion203

13 WHAT DATA DOESN'T DO&by Coco Krumme205

When Doesn't Data Drive?208

Conclusion217

14 NATURAL LANGUAGE CORPUS DATA&by Peter Norvig219

Word Segmentation221

Secret Codes228

Spelling Correction234

Other Tasks239

Discussion and Conclusion240

15 LIFE IN DATA:THE STORY OF DNA&by Matt Wood and Ben Blackburne243

DNA As a Data Store243

DNA As a Data Source250

Fighting the Data Deluge253

The Future of DNA257

16 BEAUTIFYING DATA IN THE REAL WORLD&by Jean-Claude Bradley,Rajarshi Guha,Andrew Lang,Pierre Lindenbaum,Cameron Neylon,Antony Williams,and Egon Willighagen259

The Problem with Real Data259

Providing the Raw Data Back to the Notebook260

Validating Crowdsourced Data262

Representing the Data Online263

Closing the Loop:Visualizations to Suggest New Experiments271

Building a Data Web from Open Data and Free Services274

17 SUPERFICIAL DATA ANALYSIS:EXPLORING MILLIONS OF SOCIAL STEREOTYPES&by Brendan O'Connor and Lukas Biewald279

Introduction279

Preprocessing the Data280

Exploring the Data282

Age,Attractiveness,and Gender285

Looking at Tags290

Which Words Are Gendered?294

Clustering295

Conclusion300

18 BAY AREA BLUES:THE EFFECT OF THE HOUSING CRISIS&by Hadley Wickham,Deborah F.Swayne,and David Poole303

Introduction303

How Did We Get the Data?304

Geocoding305

Data Checking305

Analysis306

The Influence of Inflation307

The Rich Get Richer and the Poor Get Poorer308

Geographic Differences311

Census Information314

Exploring San Francisco318

Conclusion319

19 BEAUTIFUL POLITICAL DATA&by Andrew Gelman,Jonathan P.Kastellec,and Yair Ghitza323

Example 1:Redistricting and Parti san Bias324

Example 2:Time Series of Estimates326

Example 3:Age and Voting328

Example 4:Public Opinion and Senate Voting on Supreme Court Nominees328

Example 5:Localized Partisanship in Pennsylvania330

Conclusion332

20 CONNECTING DATA&by Toby Segaran335

What Public Data Is There,Really?336

The Possibilities of Connected Data337

Within Companies338

Impediments to Connecting Data339

Possible Solutions343

Conclusion348

CONTRIBUTORS349

INDEX357