The Data Journalism Handbook by Jonathan Gray, Lucy Chambers -- Read -- Imperial Library of Trantor

Index

The Data Journalism Handbook Preface

For the Great Unnamed Contributors What This Book Is (And What It Isn’t) Conventions Used in This Book Safari® Books Online How to Contact Us

1. Introduction

What Is Data Journalism? Why Journalists Should Use Data Why Is Data Journalism Important?

Filtering the Flow of Data New Approaches to Storytelling Like Photo Journalism with a Laptop Data Journalism Is the Future Number-Crunching Meets Word-Smithing Updating Your Skills Set A Remedy for Information Asymmetry An Answer to Data-Driven PR Providing Independent Interpretations of Official Information Dealing with the Data Deluge Our Lives Are Data A Way to Save Time An Essential Part of the Journalists’ Toolkit Adapting to Changes in Our Information Environment A Way to See Things You Might Not Otherwise See A Way To Tell Richer Stories

Some Favorite Examples

Do No Harm in the Las Vegas Sun Government Employee Salary Database Full-Text Visualization of the Iraqi War Logs, Associated Press Murder Mysteries Message Machine Chartball

Data Journalism in Perspective

Computer-Assisted Reporting and Precision Journalism Data Journalism and Computer-Assisted Reporting Data Journalism Is About Mass Data Literacy

2. In The Newsroom

The ABC’s Data Journalism Play

Our Team Where Did We Get the Data From? What Did We Learn? The Big Picture: Some Ideas

Data Journalism at the BBC

Make It Personal Simple Tools Mining The Data Understanding An Issue Team Overview

How the News Apps Team at the Chicago Tribune Works Behind the Scenes at the Guardian Datablog Data Journalism at the Zeit Online How to Hire a Hacker Harnessing External Expertise Through Hackathons Following the Money: Data Journalism and Cross-Border Collaboration Our Stories Come As Code Kaas & Mulvad: Semi-Finished Content for Stakeholder Groups

Processes: Innovative IT Plus Analysis Value Created: Personal and Firm Brands and Revenue Key Insights of This Example

Business Models for Data Journalism

3. Case Studies

The Opportunity Gap A Nine Month Investigation into European Structural Funds

1. Identify who keeps the data and how it is kept 2. Download and prepare the data 3. Create a database 4. Double-checking and analysis

The Eurozone Meltdown Covering the Public Purse with OpenSpending.org Finnish Parliamentary Elections and Campaign Funding

1. Find data and developers 2. Brainstorm for ideas 3. Implement the idea on paper and on the Web 4. Publish the data

Electoral Hack in Realtime (Hacks/Hackers Buenos Aires)

What Data Did We Use? How Was It Developed? Pros Cons Implications

Data in the News: WikiLeaks Mapa76 Hackathon The Guardian Datablog’s Coverage of the UK Riots

Phase One: The Riots As They Happened Phase Two: Reading the Riots

Illinois School Report Cards Hospital Billing Care Home Crisis The Tell-All Telephone Which Car Model? MOT Failure Rates Bus Subsidies in Argentina

Who Worked on the Project? What Tools Did We Use?

Citizen Data Reporters The Big Board for Election Results Crowdsourcing the Price of Water

4. Getting Data

A Five Minute Field Guide

Streamlining Your Search Browse Data Sites and Services Ask a Forum Ask a Mailing List Join Hacks/Hackers Ask an Expert Learn About Government IT Search Again Write an FOI Request

Your Right to Data Wobbing Works. Use It!

Case Study 1: Farm Subsidy Case Study 2: Side Effects Case Study 3: Smuggling Death

Getting Data from the Web

What Is Machine-Readable Data? Scraping Websites: What For? What You Can and Cannot Scrape Tools That Help You Scrape How Does a Web Scraper Work? The Anatomy of a Web Page An Example: Scraping Nuclear Incidents with Python

The Web as a Data Source

Web Tools Web Pages, Images, and Videos Emails Trends

Crowdsourcing Data at the Guardian Datablog How the Datablog Used Crowdsourcing to Cover Olympic Ticketing Using and Sharing Data: the Black Letter, the Fine Print, and Reality

5. Understanding Data

Become Data Literate in Three Simple Steps

1. How was the data collected?

Amazing GDP growth Crime is always on the rise What you can do

2. What’s in there to learn?

Risk of Multiple Sclerosis doubles when working at night On average, 1 in every 15 Europeans totally illiterate What you can do

3. How reliable is the information?

The sample size problem Drinking tea lowers the risk of stroke What you can do

Tips for Working with Numbers in the News Basic Steps in Working with Data

Know the Questions You Want to Answer Cleaning Messy Data Data May Have Undocumented Features

The £32 Loaf of Bread Start With the Data, Finish With a Story Data Stories Data Journalists Discuss Their Tools of Choice Using Data Visualization to Find Insights in Data

Using Visualization to Discover Insights

Learn how to visualize data Analyze and interpret what you see Document your insights and steps Transform data

Which Tools to Use An Example: Making Sense of US Election Contribution Data What To Learn From This Get the Source Code

6. Delivering Data

Presenting Data to the Public

To Visualize or Not to Visualize? Using Motion Graphics Telling the World Publishing the Data Opening Up Your Data Starting an Open Data Platform Making Data Human Open Data, Open Source, Open News Add A Download Link Know Your Scope

How to Build a News App

Who Is My Audience and What Are Their Needs? How Much Time Should I Spend on This? How Can I Take Things to the Next Level? Wrapping Up

News Apps at ProPublica Visualization as the Workhorse of Data Journalism

Tip 1: Use small multiples to quickly orient yourself in a large dataset Tip 2: Look at your data upside down and sideways Tip 3: Don’t assume Tip 4: Avoid obsessing over precision Tip 5: Create chronologies of cases and events Tip 6: Meet with your graphics department early and often Tips For Publication

Using Visualizations to Tell Stories

Seeing the Familiar in a New Way Showing Change Over Time Comparing Values Showing Connections and Flows Designing With Data Showing Hierarchy Browsing Large Databases Envisioning Alternate Outcomes When Not To Use Data Visualization

Different Charts Tell Different Tales Data Visualization DIY: Our Top Tools

Google Fusion Tables Tableau Public Google Spreadsheet Charts Datamarket Many Eyes Color Brewer And Some More

How We Serve Data at Verdens Gang

Numbers Networks Maps Text Mining Concluding Notes

Public Data Goes Social Engaging People Around Your Data

About the Authors Colophon Copyright

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