Enlightenment 2.0: A New Era of Collaboration and Storytelling with Data

A New Era of Collaboration and Storytelling with Data

Geoff McGheeGartner Business Intelligence Summit, Los AngelesMay 3, 2011

Enlightenment 2.0

http://www.stanford.edu/group/toolingup/rplviz/

Visualizing the Enlightenment

“Mapping the Republic of Letters,” Stanford University (2009)




Visualizing the Enlightenment

“Mapping the Republic of Letters,” Stanford University (2009)

https://republicofletters.stanford.edu/






















































• Great age of inquiry and discovery, from roughly 1680 to 1820

• Triumph of evidence based, empirical reasoning

• Collaboration and communication across borders, disciplines

• Self-sustaining/accelerating as insight begets more insight

Enlightenment 1.0What Was the Age of Enlightenment?

“Mankind’s final coming of age, the emancipation of the human consciousness from an immature state of ignorance and error.”

– Immanuel Kant

Enlightenment 1.0

• Development of scientific method

• Aftermath of blockbuster discoveries, from Galileo to Isaac Newton

• Exploration of the world

• Growth of American colonies, path to independence and self determination

• End of Thirty Years’ War

Origins of the Enlightenment


Interaction Across DisciplinesPhilosophers, essayists, botanists, mathematicians, economists, composers grappling individually – and together – with revolutionary ideas, inventions and movements.


John Locke

Thomas Paine

Adam Smith

Thomas Jefferson

Jean-Jacques Rousseau Benjamin Franklin

Voltaire Carl Linnaeus

What about today?

http://vimeo.com/2598878

http://vimeo.com/2598878

• Explosion of electronic data collection and storage

• Moore’s law: increasingly powerful processors, including GPUs

• Digitization of media (photos, music, books...)

• Remote sensors, RFID tags, POS systems

• Cheap storage

• Data formats (XML, JSON, RDF… ), APIs

• Social media, open source, crowdsourcing

Conditions for a “Second Enlightenment”

Enlightenment 2.0?

• Finding meaning in a flood of dataEstimated 5 exabytes a day… in 2003!

• Increasing velocity of decision-making, advent of real-time (or close) data

• Responsible use of powerful information technology: smartphone tracking, facial recognition, other data collection methods

• Government, business and individuals rethinking long-held habits in light of new, actionable information

Enlightenment 2.0?

Challenges of the 21st Century

“We are confronted today with insurmountable opportunities.”

– Walt Kelly, Pogo

Enlightenment 2.0?

Enlightenment 1.0

Coffee houses as gathering places

Enlightenment 2.0?

“Laptopistan”

Physicist, Inventor of the Hypertext ProtocolTim Berners-Lee

• Envisioned the World Wide Web as a tool for sharing data

• Published influential article, “the semantic web,” in 2001

• End result of a “semantic web” – machine-readable documents, all the web’s content as (or convertible into) structured data

Enlightenment 2.0?Heroes of a Second EnlightenmentData Journalism“Programmer Journalists”

Rise of programmer-journalists who “know their CSV

from their RDF, can throw together some quick

MySQL queries for a PHP or Python output … and

discover the story lurking in datasets released by

governments, local authorities, agencies, or any

combination of them – even across national

borders.”

“Journalists need to be data-savvy. It used to be that you would get stories by chatting to people in bars...”

“But now it's also going to be about poring over data and equipping yourself with the tools to analyse it and picking out what's interesting. And keeping it in perspective, helping people out by really seeing where it all fits together, and what's going on in the country.” – Tim Berners-Lee, Nov. 2010

Computer Scientists, Data Visualization PioneersBen Shneiderman, Jock Mackinlay

Developed science of human-computer interaction, built on principles of information graphics going back to 1700s and early works of Charles Minard, Edward Playfair.

Also adapted rules from Jacques Bertin’s “semiology of graphics,” left, to computer visualization

Heroes of a Second EnlightenmentEnlightenment 2.0?

Programmers, ArtistsBen Fry and Casey Reas

• Developed Processing, Java-based tool for authoring generative art and data visualizations

• Popular with computer scientists AND artists

• Instrumental in making visualization sexy


Processing.org

http://processing.org

http://processing.org

Chief Economist, GoogleHal Varian

“I keep saying the sexy job in the next ten years will be statisticians…. The ability to take data - to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it’s going to be a hugely important skill in the next decades.”

– Interview with McKinsey Quarterly


http://www.mckinseyquarterly.com/Hal_Varian_on_how_the_Web_challenges_managers_2286

http://www.mckinseyquarterly.com/Hal_Varian_on_how_the_Web_challenges_managers_2286

Public Health ResearcherHans Rosling


The Joy of Stats on BBC Television

• Known for exuberant TED Talks on human development statistics over time

• Model for narrative data storytelling with heart – Jacques Cousteau of data?

160-Year-Old Newspaper CompanyThe New York Times

• Using visualization for news

• Tapping into academic and scientific literature

• Developing new gold standard for narrative vis

Enlightenment 2.0?Heroes of a Second Enlightenment

How Different Groups Spend Their Day (2009)

http://www.nytimes.com/interactive/2009/07/31/business/20080801-metrics-graphic.html?src=tp

http://www.nytimes.com/interactive/2009/07/31/business/20080801-metrics-graphic.html?src=tp

The Unknown Coder


• People who contribute countless hours to open source projects from Open Street Maps to Wikipedia to Linux OS to… to…

• Hackers and tinkerers who develop and share tools to make high-end data processing and visualization possible for little or no cost

What Does This Enlightenment Look Like?

Everyday Use of Data to Make DecisionsEnlightenment 2.0?

Maps, GPS with live traffic

Donation Dashboard

Farecast search results

Greatschools.org

Zillow, Trulia, real estate search engines

SF Park

= We’re learning things that used to be unknown, unknowable or impractical to know.

http://sfpark.org/

http://sfpark.org/

http://dd.berkeley.edu/user/index.php

http://dd.berkeley.edu/user/index.php

Twitter visualizations Google Public Data Explorer

But also larger insights about society ...

Politifact Obameter U.S. State Department: “Opinion Space”

Enlightenment 2.0?

http://tweettopicexplorer.neoformix.com/

http://tweettopicexplorer.neoformix.com/

http://google.com/publicdata



http://www.politifact.com/truth-o-meter/promises/obameter/

http://www.politifact.com/truth-o-meter/promises/obameter/

http://www.state.gov/opinionspace/

http://www.state.gov/opinionspace/

Google N-Grams Baby Name Voyager

… and new insights about the past.

Gapminder: Human Development Over Time Immigration Explorer

Enlightenment 2.0?

http://ngrams.googlelabs.com/graph?content=television%252C+radio&year_start=1800&year_end=2000&corpus=4&smoothing=3

http://ngrams.googlelabs.com/graph?content=television%252C+radio&year_start=1800&year_end=2000&corpus=4&smoothing=3

http://www.bewitched.com/namevoyager.html



http://www.gapminder.org/world/%23$majorMode=chart$is;shi=t;ly=2003;lb=f;il=t;fs=11;al=21;stl=t;st=t;nsl=t;se=t$wst;tts=C$ts;sp=6;ti=2006$zpv;v=0$inc_x;mmid=XCOORDS;iid=phAwcNAVuyj1jiMAkmq1iMg;by=ind$inc_y;mmid=YCOORDS;iid=phAwcNAVuyj1gkNuUEXOGag;by=ind$inc_s;uniValue=8.21;iid=phAwcNAVuyj1NHPC9MyZ9SQ;by=ind$inc_c;uniValue=255;gid=CATID0;iid=pyj6tScZqmEfbZyl0qjbiRQ;by=grp$map_x;scale=log;dataMin=294;dataMax=76977$map_y;scale=lin;dataMin=-1.2196;dataMax=26$map_s;sma=58;smi=1$cd;bd=0$inds=;modified=6

http://www.gapminder.org/world/%23$majorMode=chart$is;shi=t;ly=2003;lb=f;il=t;fs=11;al=21;stl=t;st=t;nsl=t;se=t$wst;tts=C$ts;sp=6;ti=2006$zpv;v=0$inc_x;mmid=XCOORDS;iid=phAwcNAVuyj1jiMAkmq1iMg;by=ind$inc_y;mmid=YCOORDS;iid=phAwcNAVuyj1gkNuUEXOGag;by=ind$inc_s;uniValue=8.21;iid=phAwcNAVuyj1NHPC9MyZ9SQ;by=ind$inc_c;uniValue=255;gid=CATID0;iid=pyj6tScZqmEfbZyl0qjbiRQ;by=grp$map_x;scale=log;dataMin=294;dataMax=76977$map_y;scale=lin;dataMin=-1.2196;dataMax=26$map_s;sma=58;smi=1$cd;bd=0$inds=;modified=6

http://www.nytimes.com/interactive/2009/03/10/us/20090310-immigration-explorer.html

http://www.nytimes.com/interactive/2009/03/10/us/20090310-immigration-explorer.html

Enlightenment 2.0?

Mapping, Text Mining Texas Newpaper Archives “Personal Annual Report”

Data Vis For, and By Everyone

LinkedIn Maps Assessing NFL Draft Picks Through their Words

http://mappingtexts.org/texas_v100gm

http://mappingtexts.org/texas_v100gm

http://feltron.com/ar10_01.html



http://www.slate.com/id/2292312/

http://www.slate.com/id/2292312/

The Challenge of Data

We are mining information to find insights and make decisions... But how do we do this at such a large scale? As individuals? As companies?

• Bypass language centers, go direct to the visual cortex

• Leverage ability to recognize patterns, visual sense-making

• Powerful graphics chips enable animation, live data processing possible

The Promise of Data Visualization

Using the Eye-Brain Connection

Map of New Brainland by Unit Seven via Flickr

http://flightpatterns.com


“Flight Patterns,” Aaron Koblin (2005)



http://hint.fm/projects/flickr/

“Flickr Flow,” Fernanda Viégas and Martin Wattenberg (2009)


http://hint.fm/projects

http://hint.fm/projects





http://blog.blprnt.com/blog/blprnt/goodmorning

“Good Morning,” Jer Thorp (2009)


http://livepage.apple.com/






















































The Challenge of Data Visualization

“God Mode” visualizations keep the data at arm’s length. Why? Production time, technology used to produce them.

How do we get closer? How do we provide texture and story?

Journey of Discovery

10 Years in Infographics and Multimedia

ABC News, 1999-2000The New York Times, 2000-2008

http://www.nytimes.com/packages/khtml/2004/12/26/international/20041227_QUAKE_FEATURE.html?scp=13&sq=deadly+waves&st=m

http://www.nytimes.com/packages/khtml/2004/12/26/international/20041227_QUAKE_FEATURE.html?scp=13&sq=deadly+waves&st=m

http://www.nytimes.com/packages/khtml/2003/07/19/arts/20030719_FELA_FEATURE.html?scp=1&sq=finding+fela&st=m

http://www.nytimes.com/packages/khtml/2003/07/19/arts/20030719_FELA_FEATURE.html?scp=1&sq=finding+fela&st=m

http://www.nytimes.com/packages/khtml/2004/02/18/politics/20040218_px_WISCONSIN_FEATURE.html?scp=1&sq=super+tuesday+2004+results&st=m

http://www.nytimes.com/packages/khtml/2004/02/18/politics/20040218_px_WISCONSIN_FEATURE.html?scp=1&sq=super+tuesday+2004+results&st=m

http://www.nytimes.com/specials/chinarises/intro/index.html

http://www.nytimes.com/specials/chinarises/intro/index.html

http://www.nytimes.com/images/2001/11/12/politics/recount/

http://www.nytimes.com/images/2001/11/12/politics/recount/

http://www.nytimes.com/packages/khtml/2003/02/01/national/20030201_ss_COLUMBIA_FEATURE.html?scp=4&sq=loss+of+the+shuttle&st=m

http://www.nytimes.com/packages/khtml/2003/02/01/national/20030201_ss_COLUMBIA_FEATURE.html?scp=4&sq=loss+of+the+shuttle&st=m

10 Years in Infographics and Multimedia

Le Monde, 2008-2009

http://abonnes.lemonde.fr/elections-europeennes/visuel/2009/04/23/la-situation-economique-des-vingt-sept_1184601_1168667.html

http://abonnes.lemonde.fr/elections-europeennes/visuel/2009/04/23/la-situation-economique-des-vingt-sept_1184601_1168667.html

http://www.lemonde.fr/elections-americaines/visuel/2008/09/29/les-elections-americaines-a-la-carte_1100729_829254.html

http://www.lemonde.fr/elections-americaines/visuel/2008/09/29/les-elections-americaines-a-la-carte_1100729_829254.html

Study Year at Stanford

2009-2010 John S. Knight Journalism Fellowship

http://knight.stanford.edu/innovation/

http://knight.stanford.edu/innovation/

Study Year at Stanford

2009-2010 John S. Knight Journalism Fellowship

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

Interviews About Data Visualization

Video Documentary

http://datajournalism.stanford.edu/


Video Documentary

datajournalism.stanford.edu






































Podcast Available on iTunes

http://www.google.com/url?sa=t&source=web&cd=1&sqi=2&ved=0CBkQFjAA&url=http%253A%252F%252Fitunes.apple.com%252Fus%252Fpodcast%252Fjournalism-in-the-age-of-data%252Fid426058616&ei=1LXATaDbK5PSsAOewNGZCw&usg=AFQjCNHPoGiDas6HIf8HVbt6OeFpVR17hg&sig2=kEk4GvVCILcsqwEUItAuXQ


























































































































Video Documentary

How are journalists using data vis?Question:






















































“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

Data Visualization in Journalism

Budget Forecasts, Compared with Reality (2009)

All of Inflation’s Little Parts (2009)

http://www.nytimes.com/interactive/2008/05/03/business/20080403_SPENDING_GRAPHIC.html



http://www.nytimes.com/interactive/2010/02/02/us/politics/20100201-budget-porcupine-graphic.html

http://www.nytimes.com/interactive/2010/02/02/us/politics/20100201-budget-porcupine-graphic.html

“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


Seeds of Recovery (2008)

Stimulus Tracker (2008)

Re-tooling

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


Traffic Deaths (2009)

Afghan Casualty Tracker (2008)

http://news.bbc.co.uk/2/hi/uk_news/8412891.stm





Collaboration

“What you see is this incredibly fluid flow of ideas, and to me that’s really what's exciting. Maybe 15 years ago, there were these very distinct silos and people in completely different fields had no idea–everyone was working toward the same thing but today there's starting to fuse, it’s fun, it’s competitive, well look around all the time, where’s the next amazing thing going to come from?”


Map of the Market (1998)

Timeflow, an analytical timeline for journalists (2010)

http://www.smartmoney.com/map-of-the-market/





































Enlightenment?

http://nytimes.com/recall



http://west.stanford.edu/

http://west.stanford.edu/

Journalism/Communications

Humanities

ComputerScience/

HCI

Natural Sciences/Engineering

Social Sciences

Collaborations

Bill Lane CenterFor the American West

“People come up to me all the time and ask, what’s with this data visualization thing?”

http://www.nytimes.com/2010/11/17/arts/17digital.html?scp=1&sq=digital%2520keys%2520for%2520unlocking%2520humanities&st=cse






• Follow these three blogs (via RSS, email, Flipboard etc), you’ll catch virtually everything interesting that comes along

• Cover visualization for news, science, marketing, art

Cross-Disciplinary CommunicationVis Blogs: The Virtual Water Cooler

Infosthetics.com Visual Complexity Flowing Data

http://infosthetics.com

http://infosthetics.com

http://www.visualcomplexity.com/vc/

http://www.visualcomplexity.com/vc/

http://flowingdata.com

http://flowingdata.com

Excitement

Visualization as a Medium?

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

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

Visualization as a Communication Medium?

http://stamen.com/

http://stamen.com/

http://stamen.com/

Communication Medium?

How do we tell stories with data?

How do we approach data in an enlightened way?

Data StorytellingFrom Discovery to Communication

Discovery/Acquisition Analysis Visualization

Traditional Approach

Enterprise DBSpreadsheetExternal Source

Office Productivity AppSPSS...


Discovery/Acquisition

Cleaning/“Munging”

Analysis/ExploratoryVisualization

Iteration Publication

“Enlightened” Approach


Google RefineData Wrangler

TableauSpotfireMS OfficeGephiCognosFusion TablesR

Static Image orInteractive app:FlashProcessingHTML5









































Iteration Publication Feedback CollectiveExploration




User Testing Comment Threads

Save state/BookmarkIn-Context CommentsSharing
















Save state/BookmarkIn-Context CommentsShare

Use of proven methods of user engagement and storytelling


The Traditional ApproachHand-waving and Powerpoint

The Enlightened Approach


Takes advantage of proven models of narrative storytelling and user engagement.

The Traditional ApproachHand-waving and Powerpoint

“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 StorytellingStory Formats: Learning BestPractices

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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

Data StorytellingAnalysis of Visin Media

Data Storytelling

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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.


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-1;3%*';*?1'("&/(T?6*%;'(KA1..D,+&(91%:'(A,.;D6L 9.,?:>%"(F&%PU()RGN V E E E E E E VT.3&()&.8W6(93"1*(.@(G'"*36(@1.:(93.,'1" =/8"1/(B?@*' V E E E E E E5.,%*%;%"&6(->?6'(*3'%1(71''E:"%,%&#(51%P%,'#'6(>'@.1'(=,';* =/8"1/(B?@*' V E E E E E E7..*>",,(G1"8%&#6 <%6?",(9.:2,'S%*+ V E E E E E E5'/'6*1%"&6(91.66%&#(*3'()*1''* <%6?",(9.:2,'S%*+ V E E E E E EB3'(9,%:"*'(-#'&/" X"63%&#*.&(5.6* V E E E E E E E V V E E V E V E E V E E E V V E V EX3'&(G%/(Y.?1(9.?&*+Z6(T.>6(G%6"22'"1[ X"63%&#*.&(5.6* V E E E E E E E V V E E V E E E E E E E E E E E V E-;"/":'*1%;6(O.?6'(51%;'(R&/'S 7%&"&;%",(B%:'6 E V E E E E E V V E E E V E E E E E E E E E E E V EA"&D6W(="1&%&#6\(O.8(9.:2'&6"*%.&(M',"*'6(*.(5'[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(àbc(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

Segal and Heer, 2010

vis.stanford.edu/papers/narrative


http://vis.stanford.edu/papers/narrative


Sources of Inspiration:Comic Books

MoviesVideo Games

The Enlightened OrganizationTakes advantage of proven models of narrative storytelling and user engagement.

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

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

“Stimulating Default View”



The “Martini Glass” Linear Narrative Followed by Individual Exploration





The “Martini Glass”Linear Narrative Followed by Individual Exploration

First read: narrative

The “Martini Glass”Linear Narrative Followed by Individual Exploration

First read: narrativeSecond read: reference

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

The “Data Slide Show”Or just a series of annotated, sequenced charts

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

http://www.nytimes.com/interactive/2011/03/06/us/public-private-employees.html?hp



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

The “Data Slide Show”Or just a series of annotated, sequenced charts





Wide-Angle View; Presents Links to Selected Closer Views

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






http://www.washingtonpost.com/wp-srv/special/world/north-korean-prison-camps-2009/








http://www.msnbc.msn.com/id/33498869/ns/us_news-the_stimulus_tracker/







Find yourself in the data





Linear Narratives Using Motion Graphics, Voiceover“Videographics”

http://economist.com/videographics

http://economist.com/videographics

Could be as simple as a screencast“Videographics”

Data StorytellingEngaging the Audience

The Traditional ApproachViews interactive media as a one-way avenueto present its message



Adds a social component to allow users to return feedback and participate in discovery

The Traditional ApproachViews interactive media as a one-way avenueto present its message

Data StorytellingGoing Social








Data StorytellingGoing Social








Data StorytellingGoing Social: Linked Comment Thread

http://ruralwest.stanford.edu/cgi-bin/web/Viz_DemographicChangePage.php







Data StorytellingGoing Social: Twitter/Facebook Integration with Saved State

http://projects.nytimes.com/census/2010/explorer




Data StorytellingGoing Social: Twitter/Facebook Integration with Saved State


























































Data StorytellingGoing Social: Annotation

http://vis.berkeley.edu/papers/sense.us/



Data StorytellingGoing Social: Annotation

Data StorytellingGoing Social: Prediction

http://www.trefis.com

http://www.trefis.com

Data StorytellingGoing Social: Prediction

Public Posture in a Two-Way World?

• Publish reports as static charts and tables

• Lock down internal metrics, reports

• Limit distribution within company

Traditional ApproachAggressively protect proprietary data

Data and the Public Sphere

• Create public spaces for conversations about data related to your industry, even vis tools

• Promote data vis “competitions” around issues important to your customers

• Release some company information, reports as structured data, or through API

• Rigorously scrub public data to anonymize,protect sensitive information

Enlightened ApproachJudicious Sharing and Publication


ManyEyes by IBM/Cognos

http://www-958.ibm.com/software/data/cognos/manyeyes/



http://visualizing.org

Data and the Public Sphere: Creating Community

“Visualizing.org” by General Electric and Seed Media Group








“Visualizing.org” by General Electric and Seed Media Group

Data and the Public Sphere: Competitions



http://www.wnyc.org/shows/bl/census/

“Map Your Moves” by WNYC Public Radio







































“Map Your Moves” by WNYC Public Radio




http://www.nytimes.com/interactive/2010/01/10/nyregion/20100110-netflix-map.html

Data and the Public Sphere: Peeks/Leaks

“A Peek into Netflix Queues,” The New York Times (2010)





































The Alternative?

http://www.youtube.com/watch?v=5YGc4zOqozo























• Need to follow Twitter, Facebook, other social media to know how people are reacting to your products and services

• Growing list of companies doing real-time analysis with sophisticated natural language processing tools/ artificial intelligence: topic modeling, sentiment analysis...

Customer Mood Watch

Data and the Public SphereKeeping an Ear to the Ground

http://clara.is


Clara, Social Media Monitoring for Video Game Communities

http://clara.is

http://clara.is


The Traditional ApproachTake existing presentation materials andhire a design firm to add “wow” factor



Create data visualizations to explain performance, provide industry context, or engage customers in how they use their product.

Use best visual practices that leverage research on effectiveness of visual language through clarity and simplicity

The Traditional ApproachTake existing presentation materials andhire a design firm to add “wow” factor

• Bertin’s rules for visual encodings: Length/height, position, color, area, symbol etc, in descending order of effectiveness

• Clean layout and design based in gestalt language of grouping, symbology

• Especially when introducing unfamiliar data

• Prominent key/legend on all graphics!

Importance of Good Fundamentals


Data StorytellingSeek Out the Experts

Edward Tufte Stephen Few Connie Malamed

Best Guides for Visual Communication

http://www.edwardtufte.com/tufte/books_vdqi



























































































































http://www.perceptualedge.com/library.php







Data StorytellingBut Have a Little Fun, Too

Article by Martin Wattenberg and Fernanda Viégas

http://edition.cnn.com/2011/OPINION/04/19/sexy.data/



Data StorytellingBut Have a Little Fun, Too

Article by Martin Wattenberg and Fernanda Viégas

“Graphs have become easier to read, though their minimalist uniformity sometimes feels like a library where all the books were written by Hemingway.”



































































































































Data StorytellingJoin the Conversation

Bring on the Debates!

Thanks!

[email protected]

Documents

Enlightenment 2.0: A New Era of Collaboration and Storytelling with Data