Journalism in the Age of Data: Telling Stories with Vis and Infographics

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Journalism in the Age of Data Telling Stories with Visualization and Infographics Geoff McGhee Malofiej 19 Infographics Summit March 25, 2011

description

Presentation to Malofiej 19 Infographics Summit, Pamplona, Spain, March 25, 2011

Transcript of Journalism in the Age of Data: Telling Stories with Vis and Infographics

Page 1: Journalism in the Age of Data: Telling Stories with Vis and Infographics

Journalism in the Age of DataTelling Stories with Visualization and Infographics

Geoff McGheeMalofiej 19 Infographics SummitMarch 25, 2011

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Study Year at Stanford

2009-2010 Knight Journalism Fellowship

knight.stanford.edu

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2009-2010 Knight Journalism Fellowship

knight.stanford.edu

Study Year at Stanford

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2009-2010 Knight Journalism Fellowship

knight.stanford.edu

Study Year at Stanford

• Databases and database management• Web application development• Visualization theory and techniques• Geographic information systems• Statistics

Back to School

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2009-2010 Knight Journalism Fellowship

knight.stanford.edu

Study Year at Stanford

• Databases and database management• Web application development• Visualization theory and techniques• Geographic information systems• Statistics• Business school classes, wine tasting,

tennis, piano

Back to School

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2009-2010 Knight Journalism Fellowship

knight.stanford.edu

Study Year at Stanford

• Propose project that leads to a “tangible result”

Knight Fellowship:New Focus on Journalism Innovation

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2009-2010 Knight Journalism Fellowship

knight.stanford.edu

Study Year at Stanford

• Propose project that leads to a “tangible result”

• Templates for infographics, data maps?

Knight Fellowship:New Focus on Journalism Innovation

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2009-2010 Knight Journalism Fellowship

knight.stanford.edu

Study Year at Stanford

• Propose project that leads to a “tangible result”

• Templates for infographics, data maps?Hard to develop alone, support long term, Flash in decline

Knight Fellowship:New Focus on Journalism Innovation

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2009-2010 Knight Journalism Fellowship

knight.stanford.edu

Study Year at Stanford

• Propose project that leads to a “tangible result”

• Templates for infographics, data maps?Hard to develop alone, support long term, Flash in decline

• Guide to visualization techniques?

Knight Fellowship:New Focus on Journalism Innovation

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2009-2010 Knight Journalism Fellowship

knight.stanford.edu

Study Year at Stanford

• Propose project that leads to a “tangible result”

• Templates for infographics, data maps?Hard to develop alone, support long term, Flash in decline

• Guide to visualization techniques?Boring, who will read it?

Knight Fellowship:New Focus on Journalism Innovation

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20-odd people in journalism, academia, research and art

Interviews About Data Visualization

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datajournalism.stanford.edu

Video Documentary

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Video Documentary

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Video Documentary

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Video Documentary

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Other Formats

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Other Formats

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First Chapter

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Main Points

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Excitement

“I think that there’s a sense that data is something more like a medium, something that can be used to tell stories, and to do all of the things that a medium can do, to delight and inspire...”

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But...

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Communication Medium?

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How are journalists using data vis?

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“Amanda studied stats in college and she's brought both a little bit more of a focus on data to the department and also just sort of an amazing ability to process data.”

New Players

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“We have some open positions right now, and I would love for those positions to be geared towards somebody that had that skill set: ‘Here’s what the data is and the story is, here’s how we’d want to shape the story based on this data.’”

Re-tooling

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Re-tooling

“We've changed the focus of our team to concentrate more on database journalism.”

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Skepticism

“You can do beautiful things with computers and lots of data that look very, very nice, and are almost completely incomprehensible.”

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“We are very interested in how visualizations are being taken up in mass media, particularly in journalism, so we simply collected as many examples of that as we could.”

Data StoryFormats

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Fig. 7. Design space analysis of narrative visualization. Columns indicate recurring design elements and selected regions highlight patterns in the data. Region (1) shows clusters of orderingstrategies that correspond to distinct genres of visual narration. Region (2) highlights the consistency of interactive designs used by visualizations. Region (3) shows the under-utilization of strategiesto engage the user in the interactive functionality. Region (4) shows the under-utilization of common storytelling techniques across narrative visualizations.

Segal and Heer, 2010

Analysis ofVis in Media

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Fig. 7. Design space analysis of narrative visualization. Columns indicate recurring design elements and selected regions highlight patterns in the data. Region (1) shows clusters of orderingstrategies that correspond to distinct genres of visual narration. Region (2) highlights the consistency of interactive designs used by visualizations. Region (3) shows the under-utilization of strategiesto engage the user in the interactive functionality. Region (4) shows the under-utilization of common storytelling techniques across narrative visualizations.

Analysis ofVis in Media

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email protected]:" 7%&"&;%",(B%:'6 E V E E E E E E V V E E E E V E E E E E E E V E V E EG'"/,+(I@@'&6%P'\(B",%>"&(-**";D6(%&(5"D%6*"& 7%&"&;%",(B%:'6 E V E E E E E E V V E E V E E E E V E E E E E E E V E V V V E V E V V E V E V E0G5(!.P'6(>+()';*.1 7%&"&;%",(B%:'6 E V E E E E E E V E E E V E E E E E E E E E E E V EF](=;.&.:%;(G"*" 7%&"&;%",(B%:'6 E V E E E E E E V E E E V E E E E E E E E E E E V E V V E V V E E V E E E E V EA?/#'*(^_`_\(M'";*%.&(@1.:("1.?&/(*3'(F] 0?"1/%"& E V E E E E E E V E E E V E E E E V E E E E E E V E V V E V E E E V V E V E E E7.1:?,"(I&'(^_`_\(G1%P'1Z6(M"&D%&#6 0?"1/%"& E V E E E E E E V E E E V E E E E V E E E E E E V E V V E V V E E V E E E E E EN%#3*%&#(F2(O"/1%"&Z6(X",, 0?"1/%"& E V E E E E E V E E E E V E E E E E E E E E E E V E E V E V V E E V V E E E V E!"22%&#(O+/1.2.8'1(O.*62.*6(";1.66(*3'(F] 0?"1/%"& E V E E E E E E V E E E V E E E E E E E E E V E V E V V E V V E E V V E V E E E!.6;.8(!'*1.(A.:>6\(%&*'1";*%P'(:"2 0?"1/%"& E V E E E E E E V E E E V E E E E E E E E E E E V E E V E V V E E V V E V E E EB3'(X.1,/(=;.&.:+(B?1&6(*3'(9.1&'1 0?"1/%"& E V E E E E E E V E E E E E E E E E E E E E E E V E V V E V E E E V E E E E E E!%&&'6.*"(=:2,.+:'&*(=S2,.1'1 !%&&'6.*"(5?>,%;(M"/%. E V E E E E E E E E E V V E V E E E E E E V V E V E V V E V V E E V V V E E V E-(!"2(.@(I,+:2%;(!'/",6 Q'8(Y.1D(B%:'6 E V E E E E E E V V E E E E E E E E E E E V V E V E V V E-,,(.@(R&@,"*%.&Z6(N%**,'(5"1*6 Q'8(Y.1D(B%:'6 E V E E E E E V V E E E V E E E V E E E E V V E V E V V E V E E E V V E E E V E5"*36(*.(*3'(B.2(.@(*3'(O.:'(M?&(93"1*6 Q'8(Y.1D(B%:'6 E V E E E E E E V E E E V E V E E E E E E E E E V E V V E V V E V V V E E E E EB3'(=>>("&/(7,.8(.@(!.P%'6\(A.S(I@@%;'(M';'%2*6(`abc(d( Q'8(Y.1D(B%:'6 E V E E E E E E V V E E V E E E E E E V E E E E V E V V E V V E E V V E E E E EB3'(T.>,'66(M"*'(@.1(5'.2,'(N%D'(Y.? Q'8(Y.1D(B%:'6 E V E E E E E E V E V E V E E E E E E E E V V E V E V V E V V E E V E E E E E E-/P'1*%6':'&*\(A?6 F&%*'/(B';3&.,.#+ E V E E E E E-/P'1*%6':'&*\(O',%;.2*'1 F&%*'/(B';3&.,.#+ E V E E E E E-&",+$%&#(I>":"Z6();3'/?,' X"63%&#*.&(5.6* E V E E E E E E E V E E V E E E E V E E E E E E V E V V V E V E E E E E E E V EI6;"16(^_`_\(B3'(A'6*(5%;*?1'(Q.:%&''6 0?"1/%"& E E V E E E E V V E V E V E E E E E E E E E E E V E V V E V E E E V V E V E E EB3'(9.&6?:'1("&/(M'*"%,(51%;'(R&/%;'6(6%&;'(^__c 0?"1/%"& E E V E E E E V V V E E V E V E E E E E E V E E V E V V E V V E EF](<.*%&#(R&*'&*%.&6 0?"1/%"& E E V E E E E V V V E E V E V E E E E E E V E E V E9.:2"1%6.&(.@(A'"1(!"1D'*6 Q'8(Y.1D(B%:'6 E E V E E E E E V V E E V E V E E E E V E V V E V E V V E V V E V V V E E E E E7";'6(.@(*3'(G'"/ Q'8(Y.1D(B%:'6 E E V E E E E E V E E E V E E E E E E E E E E E V E

Analysis ofVis in Media

Segal and Heer, 2010

vis.stanford.edu/papers/narrative

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Identify Common Narrative FormatsDescriptive, Not Prescriptive

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Sources of Inspiration:Comic Books

MoviesVideo Games

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The “Science Fair Poster”Using Space to Lay Out Regions; Directional Reading

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The “Martini Glass”Linear Narrative Followed by Individual Exploration

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The “Martini Glass”Linear Narrative Followed by Individual Exploration

First read: narrative

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The “Martini Glass”Linear Narrative Followed by Individual Exploration

First read: narrativeSecond read: reference

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The “Data Slide Show”Linear Narrative With Interaction Within Each Frame

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The “Data Slide Show”Linear Narrative With Interaction Within Each Frame

Search All NYTimes.com

Public workers make more …Surveys by the Bureau of EconomicAnalysis show that public workers’annual compensation — salary plusbenefits — is higher on average thanprivate sector workers, and they suggestthat the gap is growing.

… especially when figured per hourof work.Public workers also put in significantlyfewer hours per week. According to theBureau of Labor Statistics, theircompensation per hour is muchhigher.

Most of the advantage is in benefits.They cost state and local governments$14 an hour on average, about 70percent more than private employerspay for their workers.

But comparisons are tricky …Economists point out that governmentwork tends to be in highly skilledcategories, so it is misleading tocompare the groups as a whole.

Published: March 6, 2011

Are State and Local Government Employees Paid Too Much?It’s not an easy question to answer for a number of reasons. Here’s a primer on the issue.

Welcome, gmcghee Log Out Help TimesPeopleHOME PAGE TODAY'S PAPER VIDEO MOST POPULAR TIMES TOPICS

U.S.WORLD U.S. N.Y. / REGION BUSINESS TECHNOLOGY SCIENCE HEALTH SPORTS OPINION ARTS STYLE TRAVEL JOBS REAL ESTATE AUTOS

POLITICS EDUCATION BAY AREA CHICAGO TEXAS

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The “Drill-Down Story”Wide-Angle View; Presents Links to Selected Closer Views

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The “Drill-Down Story”Wide-Angle View; Presents Links to Selected Closer Views

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“Videographics”Linear Narratives Using Motion Graphics, Voiceover

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“Videographics”Linear Narratives Using Motion Graphics, Voiceover

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“Videographics”Could be as simple as a screencast

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Chapters

Part 1: IntroductionMeet some of the researchers who have helped popularize data visualization for art and communication.

Part 2: Data Visualization in JournalismHow data reporting and presentation are starting to change the face of newsrooms.

Part 3: Telling “Data Stories”How journalists are adapting traditional narrative formats to data visualization.

Part 4: A New Era in InfographicsData vis whizzes are the new rock stars in a field where people have been making charts for over 200 years.

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Part 5: Life as a Data StreamUsing data as an expressive medium, and experiencing live events through information streams.

Part 6: Exploring DataThe importance of data analysis to good journalism.

Part 7: Technologies and ToolsA new generation of web browsers is changing the game for online visualization and interactive graphics. A look at emerging technologies and tools.

Part 8: First StepsNew tools, tutorials and websites about visualization are appearing all the time. A look at where to get started.

Chapters

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Reception

Minimal promotion after initial press release by fellowship (one of 20 projects announced)

Benefited from viral promotion by friends and colleagues. Thanks for the Tweets!

Mentions on infographics and data journalism blogs and sites

About 50,000 unique visitors since September on Flash site

Another 60,000+ views on Vimeo last time I checked

Condensed version aired by 3Sat television, Germany

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Wider Story

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Data journalism: What it isJournalists have always worked with dataWe've analysed council tax rates, changes brought about by Budgetmeasures, and all sorts of statistics thrown at us by government,business, unions, pressure groups and other organisations.Our goal has always been to find the stories in the data - and it still is.

But how we work with data is being revolutionised because of the possibilities that usingcomputers to make sense of huge data sets opens up.

Journalist and information architect Mirko Lorenz, quoted in Data-driven Journalism, hasthis explanation of what data journalism is: “Today data-driven journalism can be definedas a workflow, where data is the basis for analysis, visualisation and – most importantly –storytelling.

"With cloud computing, powerful PCs on the desktop and high bandwidth, we all havethe potential to use technology to filter and process data that would have been asensation just 15, 10, maybe even five years ago.”

Here’s his visualisation of how things have changed, reproduced from a pdf report on theData-driven Journalism conference, which you can download here.

You can see from this graphic that there is filtering going on. As in more traditionalmodes of journalism, our eye on a story, our sifting of the facts and separating them fromthe falsities, are still vital. And we can sift from facts that are easily available to us, andothers that are not – the not-so-open data in the graphic.

Adam Westbrook, also quoted in Data-driven Journalism, makes clear that working withdata is a very traditional journalistic activity:

“It is journalism in its truest essence: uncovering and mining through information thepublic do not have enough time to do themselves, interrogating it, and making sense of itbefore sharing it with the audience.”

Mirko Lorenz has a second graphic to illustrate that process:

Masterclasses

Masterclass 20: Getting startedin data journalism

Data journalism: What it is

Data journalism: What it canachieve

Data journalism: How to do it

Data journalism: How TheGuardian does it

Data journalism: Tools and datasources

How to, project 4: Tableau

How to, project 5: ScraperWiki

Masterclass 19: Improve yourvideo storytelling

Masterclass 18: Drupal websitebuilding for non-coders

Masterclass 17: A guide tohyperlocal

Masterclass 16: Smartphoneapps for non-coders

Masterclass 15: Law essentialupdate

Masterclass 14: iPhone forJournalism

Masterclass 13: How to get yourfirst job

Masterclass 12: How to buildyour own job

Masterclass 11: Going Mobile

Masterclass 8: Search (andeverything else) is going social

Masterclass 6: How to masterFacebook and Twitter

Masterclass 5: How to win acommission

Masterclass 2: Web 3.0 andSocial Media

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“Data Journalism”

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“Data Journalism”

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Vis Toolkits“Data Journalism”

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Open Data Principles and Infographics

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Transparency

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Transparency

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Conversation

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Conversation

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Conversation

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Conversation

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Cross-Pollination Between Programmers & Journalists

• Wattenberg/Viegas’ TimeSeer

• Jer Thorp “artist in residence” at NY Times

• Events like IRE’s “News Camp”

• Hacks/Hackers Meetups

• Journalist/Programmer Degree Programs

• Heer/Segal Paper on Narrative Visualization

• Stamen’s “Citytracking” project wins Knight News Challenge grant

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What Now?

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What Now?

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Rural West Project

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Rural West Project

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John McChesney

Veteran NPR Reporter

• Multimedia field reporting

• Stories on rural issues in contemporary West

• Accompanying infographics and data vis

Rural West Project

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• Environment and Resources

• Economy and Political Science

• History and Culture of the West

Issue Areas

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Water in the West

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Water in the West

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• Environment and Resources

• Economy and Political Science

• History and Culture of the West

Issue Areas

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Mapping Texts

Collaboration with University of North Texas

Research Assistants Yinfeng Qin and Rio Akasaka

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• Environment and Resources

• Economy and Political Science

• History and Culture of the West

• Data visualization for journalism    and scholarship

Issue Areas

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Journalism/Communications

Humanities

ComputerScience/

HCI

Natural Sciences/Engineering

Social Sciences

Collaborations

Bill Lane CenterFor the American West

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Questions?