SlideShare a Scribd company logo
Nicholas Felton
ACCUMULATIONSWebdagene
NYC
BROOKLYN STUDIO
SIGNS OF WEAR
😍😍
SIGNS OF WEAR
ACTIONS > PATTERNS > INFORMATIONVisualization without Intermediation
PHYSICAL PEDOMETER
REGULAR DISTRIBUTION
FELTRON ANNUAL REPORTS
BETWEEN FIVE BELLS
REPORTER APP
DESIGNER
PROGRAMMER
JOURNALIST
STATISTICIAN
color, typography,
composition & texture
data, scripting,
& interactivity
research, narrative
& accountability
analysis &
correlation
1.
COLLECT2.
COMPREHEND3.
COMMUNICATE
1.
COLLECT2.
COMPREHEND3.
COMMUNICATE
1. Hoard
2. Wrangle
3. Design
Part One
COLLECTQuestion > Data
Ask a
QUESTIONWhat does a year look like?
Can you visualize a wine?
YES NOHAS THE EVENT HAPPENED?
YES
RESEARCH
1.
BIKECYCLE
2.
2010 ANNUAL REPORT
NOHAS THE EVENT HAPPENED?
2015
BIKECYCLEQuestion > Data
DATA DUMP
2010–2011
FAR 2010Question > Data
GORDON PAUL FELTON, 1929–2010
DAD’S MEMENTOS
Applications
Audio Recordings
Books
Calendars
Certificates
Driver’s Licenses
Expense Logs
Family Trees
Fast Trak Statements
Itineraries
Legal Documents
Letters
Lists
Medical Records
Newspaper Clippings
Notebooks
Passports
Photos
Police Certification
Postcards
Receipts
School Reports
Slides
Tickets
Union Registration Form
AVAILABLE
SOURCES4,348 items in 25 categories
1 EKG
Jul 24, 1989: Vale of Rheidal & Devils bridge on
old train out of Aberriswyth, walk to Devils
cauldron. Nick checks out tidepools at Aber--.
N&M move into camper.
Jul 25, 1989: Oliver taken to beauty parlor.
Jags over house low level. Meet Mervyn Evans at
pub for lunch in local. Visit Newtown Montgomery
& Welschpool. Interesting ruin of border fortress
at Mowtgy.
Jul 26, 1989: To Fistiniog to very visit to Slate
Minesa Museum. Visit damm & locked in for 45mins.
Beautiful drive by coast through Aberdovey. Drink
with Russ & Anita & call Wilson’s
Jul 27, 1989: Dep. Wales to Loboro. Visit
aerospace museum at Cosford. Drop by Brush,
David Harris. To Les & Gail & brief visit with
Les Hollingsworth. Dinner for N&M at L’boro
McDonald
Jul 28, 1989: Lunch at White House Kegworth.
Breakfast at Cafe. To Nottingham Castle Robinhood
Adventure. ‘Out of Order.’ Visit still positive
Dad ‘outlaw’ N&M are ‘Pardoned’ by King. Movie
Karate Kid III. N&M call Carol
4,440 CALENDAR ENTRIES
Jun 8, 1959
Mr. Gordon Felton, c/o Mr. Ed. Brophy, 248-05 87th
Avenue, Bellerose 6/ New York
Oct 18, 1960
G. Felton, Esq. (??), Apt. 103, 451 Lee St.,
Oakland. California.
Jun 14, 1962
Mr. Gordon Felton, 22 Terra Vista, San Francisco
05, California
Sep 18, 1962
Mr. Gordon Felton, 22 Terra Vista Ap. E-2, San
Francisco, California
Sep 19, 1962
Mr. Gordon Felton, 22. Terra Vista Ap. E-2, San
Francisco, California
Sep 16, 1962
Mr. Gordon Felton, Terra Vista E-2, San Francisco,
California
Sep 26, 1962
Mr. Gordon Felton, 22 Terra Viesta, San Francisco,
California
169 RECEIVED POSTCARDS
Jul 27, 1957
Havana, Cuba
Aug 4, 1957
Fort Erie, Ontario,
Canada
Dec 2, 1957
Malton, Canada
May 5, 1958
Melsbroek Air Base,
De Kleetlaan, Machelen,
Flemish Region, Belgium
May 5, 1958
Berlin Tempelhof
Airport, Germany
May 9, 1958
Melsbroek Air Base,
De Kleetlaan, Machelen,
Flemish Region, Belgium
May 9, 1958
Montreal Airport,
Roméo-Vachon Boulevard
North, Montreal,
Quebec, Canada
Sep 14, 1959
Toronto, Canada
Oct 18, 1959
Malton, Canada
Feb 24, 1960
Buffalo, NY
Dec 12, 1961
San Francisco, CA
Jan 2, 1962
San Francisco, CA
Jan 2, 1962
San Francisco, CA
Jan 2, 1962
San Francisco, CA
Jan 2, 1962
San Francisco, CA
Jan 3, 1962
San Francisco, CA
239 PASSPORT STAMPS
Montevideo
Buenos Aires
Cape of Good Hope
Cape Town
Johannesburg
Iguacu
Rio De Janeiro
Ascotan - Chile
La Paz
Brasilia
Cuzco
Macchu Pichu
Lima - Peru
Arusha
Ngorongoro Crater
Manaos
KNOWN CONTEXT
DISCOVERABLE CONTEXT
DISCOVERABLE CONTEXT
DISCOVERABLE CONTEXT
YES
INSTRUMENT
1.
2009
2.
2013
3.
2014 ANNUAL REPORTS
NOHAS THE EVENT HAPPENED?
2009–2011
FAR 2009Question > Data
2010/2011 CALENDAR
2009 SURVEY CARD
2009 SURVEY CARD
Encounter Date
Jan 28, 2009
Name
Adam B.
Card No.
68
Relationship
Friend
Friendship Duration
5 years
Encounter Length
1 hour
Activities
Talking, drinking,
congratulating,
planning sushi
Mood
happy, engaged
Where
Shebeen
Elsewhere
No
Eat
No
Drink
Stella(s)
Transportation
No
Conversation Topics
Work, wrestling in
studio, our fathers,
skiing, Feltron AR,
letterpress and
Willy, sushi,
printing in China
Favorite Moment
seeing/receiving/
feeling business
card & leaving
happier than I came.
Anything Else
Nicholas instigated
this encounter.
Tangential encounters
with people I knew
already: 11
Tangential encounters
with people I just
met: 3
SAMPLE
SURVEY
RESPONSENo. 37 of 560
:)
adventurous
affable
agitated
agreeable
alert
amiable
amicable
animated
anticipation
anxious
appreciated
appreciative
apprehensive
approachable
at ease
attentive
attuned
awake
awesome
ball busted
beatific
beery
bemused
boozed
bored
bouyant
bubbling
bummed
buoyant
busy
buzzy
Californian
calm
calm-ish
careful
cautious
celebratory
charming
chatty
cheered up
cheerful
cheery
chill
chipper
chirpy
chopsticks
chummy
COLLECTIVE
MOOD
RESPONSESMoods 1–48 of 300
2012–2014
FAR 2013Question > Data
Metadata Data
EMAIL Google
SMS Apple / ATT
CHAT Facebook
PHONE ATT
MAIL USPS
CONVERSATION
COMM.
SOURCES3 online / 3 offline
Who with
Conversation Type
Greeting, Non-Verbal, Pleasantry,
Functional, Sporadic, Chat,
Question, Answer, Meeting,
Telephone, Video Conference,
Breakfast, Brunch, Lunch, Dinner,
Coffee, Drink, Other
Non-Verbal
Type Wave, Smile, Nod, Raise
Eyebrows, Hand Shake, Hug, Kiss,
Point, Wink, Fist Bump, Hi-Five,
Other
Greeting Type
Good morning, What’s up?, Dude,
Hey, Hi, Hello, How are you?, Nice
to meet you, Bye, Goodbye, Good
night, Take care, See you, Later,
Other
Pleasantry Type
Thank you, Thanks, Bless you,
Pardon me, Excuse me, Sorry, Other
Description
Location
Time
Duration
Momentary, 1 minute, 2 minutes, 3
minutes, 5 minutes, 10 minutes, 15
minutes, 30 minutes, 1 hour, Other
FULCRUM
CONV.
SURVEYFinal version
Who with: Olga
Conversation Type: Greeting, Non-Verbal, Lunch
Non-Verbal Type: Kiss
Greeting Type: Hello
Pleasantry Type:
Description: Olga’s rehearsal schedule. delicious flat whole wheat ev-
erything bagel with whitefish and avocado lunch. Dropbox camera roll
backup. The definition of scrappy.
Location: Home
Coordinates: 40.713337, -73.949233
Date: September 24, 2015
Time: 13:07 – 13:45
Duration: 38m
SAMPLE
CONV.
ENTRYNo. 9,640 of 12,707
2013 CONVERSATIONS
2013 CONVERSATIONS
2013 CONVERSATIONS
book video
2014–2015
FAR 2014Question > Data
Location
Calendar Calendar Calendar Digital
Analog
Activity Weather Body CarWork Sleep Photos MEDIA
Last.fm
DATA SOURCES2005
Location
Human App
Day One
Rove
Lapka BAM
Moves App
Automatic
Breeze
Photo
Exif Data
Activity
Fitbit
Nike
Fuelband
Human App
Trace App
Moves App
Basis
Watch
Nike
Running
Skitracks
App
Healthkit
Weather
Weather
Underground
Day One
Body
Withings
Scale
Lapka BAM
Basis
Watch
Car
Automatic
Work
Github
RescueTime
Dropbox
Sleep
Basis
Watch
Photos
Narrative
Clip
Camera
Roll
MEDIA
Netflix
Kindle
Last.fm
Soundcloud
Amazon
Prime
DATA SOURCES2014
Instagram
Camera
Roll
Instagram
Skitracks
App
Moves App
INSTRUMENTING PHONE
Last.fm
RescueTime
Netflix
INSTRUMENTING LAPTOP
Photos
GPS EXIF
NARRATIVE CAMERA
Steps Heartrate
Activity
Types
Sleep
BASIS WATCH
Blood
Alcohol
LAPKA BAM
Location
Driving
Stats
Location
AUTOMATIC
Weight
Body Fat
WITHINGS SCALE
DATA
ACCESSServices used
Access via API
Lapka BAM
Instagram
Fitbit
Moves
Hacks Required
Basis Watch
Netflix
Direct Download
Automatic
RescueTime
Day One
Withings
Scale
Skitracks
App
Best Worse
NO DATA
Soundcloud
Amazon
Prime
Kindle
DropboxLast.fm
Part Two
COMPREHENDData > Understanding
2009–2011
FAR 2009Data > Understanding
BASIC DATA TYPES
yes/no or 0/1
Boolean
YES 1.0 HELLO!whole or decimal
positive or negative
Number
free text or categories
Text
SURVEY RESPONSES
Sad Happy
-5 +5
Introverted Extroverted
-5 +5
RATING
MOOD
RESPONSESWith Amazon Mechanical Turk
Turk Interface
:) 5
adventurous 3.2
affable 3.2
agitated -5
agreeable 5
alert 2.4
amiable 3
amicable 1.6
animated 4
anticipation -0.6
anxious -0.8
appreciated 3.2
appreciative 5
apprehensive -2
approachable 3.2
at ease 4
attentive 0
attuned 1.2
awake 0.6
awesome 5
ball busted -5
beatific 3.2
beery -0.4
bemused 5
boozed 0.6
bored -3.2
bouyant 5
bubbling 5
bummed -5
buoyant 3.2
busy 0
buzzy 3.2
Californian 0.4
calm 0.8
calm-ish 1
careful -0.6
cautious -0.8
celebratory 4
charming 5
chatty 1.8
cheered up 5
cheerful 5
cheery 5
chill 1.2
chipper 5
chirpy 2.4
chopsticks 0.8
chummy 4
INDEXED
MOOD
RESPONSESMoods 1–48 of 300
Processing seeks to ruin the careers of
talented designers by tempting them away
from their usual tools and into the world
of programming and computation. Similarly,
the project is designed to turn engineers
and computer scientists to less gainful
employment as artists and designers.
PROCESSING
MISSION
STATEMENTwww.processing.org
PLOTTING MOODS
2010–2011
FAR 2010Data > Understanding
people
address
entertainment
food
restaurant
type
CALENDAR
TAGS
Montevideo -34.883335 -56.166668 2
Buenos Aires -34.608418 -58.37316 4
Cape of Good Hope -34.35869 18.475363 2
Cape Town -33.92479 18.429916 12
Johannesburg -26.204445 28.045555 1
Iguacu -25.683332 -54.433334 29
Rio De Janeiro -22.90354 -43.209587 20
Ascotan - Chile -22.442776 -68.92286 1
La Paz -16.49901 -68.14625 5
Brasilia -14.235004 -51.92528 14
Cuzco -13.525 -71.97222 13
Macchu Pichu -13.163611 -72.5459 12
Lima - Peru -12.043333 -77.028336 2
Arusha -3.365789 36.67445 4
Ngorongoro Crater -3.1740036 35.563892 53
Manaos -3.1071923 -60.026127 3
GEOCODING PHOTOS
MAPPING LOCATIONS
2012–2014
FAR 2013Data > Understanding
SMS TIMESTAMPS
CLEANING CONVERSATIONSFulcrum data
Dec 27, 2014 Jan 27, 2014
Jan 4: 9h 2m Cleaning
Corpus Word Count:
6,904,901
Unique Word Count:
117,194
Most frequent word
is ‘the’ appearing
196,414 times
Top Interrogatives:
who: 4,080
what: 5,808
when: 6,476
where: 2,892
why: 1,593
how: 6,435
Profanities:
hell 172
shit 112
damn 112
sex 82
fuck 78
dick 35
dong 33
fanny 30
screw 29
balls 29
negro 26
dyke 23
ass 23
xxx 21
crap 14
bastard 13
queer 12
titty 11
poop 11
bitch 9
fart 8
vibrator 7
pussy 7
porn 7
bugger 7
sperm 6
pimp 6
homo 6
piss 5
penis 5
boobs 5
WORD
FREQUENCYWordCount_071714a
she 2696
whether 2453
him 1901
says 1740
tell 1657
going 1546
say 1464
ask 1348
asks 1330
working 943
getting 936
zoo 846
ill 838
being 767
yes 697
talk 665
dinner 642
nice 612
tomorrow 607
show 570
office 560
doing 556
king 542
drew 490
looking 474
went 473
wedding 472
trip 467
car 452
long 452
coming 436
can’t 428
place 421
little 420
happy 416
coffee 411
wants 405
food 400
building 388
down 387
yeah 387
trying 372
eat 371
cool 368
maybe 364
old 364
running 360
said 358
run 356
better 353
chat 353
soon 347
small 339
bad 337
really 335
something 335
water 334
morning 333
making 332
probably 329
tonight 329
give 328
put 328
why 327
2013
MOST
SENT
WORDSVocabularyPlot_071514a
click 15040
informa… 13765
address 13679
view 13499
percent 13056
price 11725
account 11462
code 11149
shipping 10750
emails 10609
offer 9985
sent 9693
payment 9634
customer 9577
transact… 9469
receive 9044
message 9021
twitter 8984
list 8927
details 8717
save 8306
sale 7948
change 7889
these 7456
privacy 7431
pm 7172
deal 7171
preferen… 6829
wrote 6680
follow 6632
contact 6470
read 6259
learn 6122
online 6099
music 6002
stock 5808
questions 5762
store 5725
received 5678
add 5664
reply 5479
policy 5471
available 5425
shop 5291
deals 5199
service 5188
tickets 4990
visit 4925
net 4895
image 4869
rights 4819
member 4637
share 4622
log 4618
page 4590
subject 4573
reserved 4554
terms 4494
amount 4451
valid 4441
card 4412
photos 4388
members 4296
est 4271
2013
MOST
RECEIVED
WORDSVocabularyPlot_071514a
“Ryan Case” - Conversation
195.1393 - ryan
142.47809 - ryans
101.06998 - minutiae
83.135025 - work
81.84209 - bonnie
75.954185 - facebook
61.653275 - app
52.95851 - going
52.938576 - new
51.793407 - lunch
4pm - All Communication
2445.5276 - |
2037.5258 - learn
1997.6616 - -
1216.178 - email
1206.7687 - new
1097.3185 - us
1080.9609 - will
1070.2032 - pm
1028.2096 - 2013
943.6468 - can
TERM
FREQUENCY
INVERSE
DOCUMENT
FREQUENCYTF_IDF2_082714A
>>> conversation = nltk.Text(word-
lists.words(‘AR13_conversation.
txt’))
>>> conversation.collocations()
Building collocations list
new york;
annual report;
san francisco;
say yes;
last night;
would like;
dirty projectors;
cross country;
mill valley;
moves app;
fuel band;
national geographic;
small latte;
reporter app;
las vegas;
palo alto;
los angeles;
hurricane sandy;
ice cream;
high five
>>>
NATURAL
LANGUAGE
TOOLKITPython
Person 78701
Company 49375
City 34545
FieldTerminology 16519
StateOrCounty 12239
Country 10987
Facility 10722
Organization 10389
JobTitle 8763
Technology 4322
PrintMedia 2798
GeographicFeature 2752
OperatingSystem 1738
Holiday 1103
Continent 764
Sport 410
Region 404
Degree 394
HealthCondition 323
FinancialMarketIndex 303
Crime 281
Product 267
Movie 235
EntertainmentAward 168
Drug 141
TelevisionStation 109
MusicGroup 83
TelevisionShow 79
Automobile 73
ProfessionalDegree 46
NaturalDisaster 44
SportingEvent 24
Anatomy 5
ALCHEMY
APIwww.alchemyapi.com
TYPE RELEVANCE ENTITY SOURCE
City 64% London email
Person 88% Nicholas email
Company 89% Facebook email
Technology 16% iPhone email
Country 43% Russia email
Person 67% Joe Davis email
Company 30% Apple email
JobTitle 40% reporter facebook
Person 85% Beyonce conversation
Holiday 17% Christmas email
JobTitle 38% Project Manager email
PrintMedia 28% IL magazine email
Continent 30% Europe email
Anatomy 33% calf muscle sms
Technology 69% iPhone email
ALCHEMY
APIwww.alchemyapi.com
warrens apt 38.9319 -77.0556
Williamsburg 37.2707 -76.7075
Japan 36.2048 138.253
Bowery 40.7253 -73.9903
Brussels 50.8503 4.35171
Richardson 32.9482 -96.7297
Japan. 36.2048 138.253
Brooklyn 40.65 -73.95
manhattan 40.7903 -73.9597
nyc. 40.7144 -74.006
portlandia 45.5101 -122.975
minneapolis 44.9833 -93.2667
Oslo 59.9139 10.7522
California 36.7783 -119.418
Australia -25.2744 133.775
royal tennenbaums. 36.8508 -76.2859
GEOCODINGGoogle Maps API
2014–2015
FAR 2014Data > Understanding
AUTOMATIC BUGS
BASIS WATCH BUGS
LAPKA BAM BUGS
NARRATIVE PHOTO TAGGER
MOVES APP VISUALIZATION
MOVES APP VISUALIZATION
DAILY DATA GRAPHS
DAILY STEP GRAPHS
DAILY STEP GRAPHS
DAILY HEARTRATE GRAPH
TRIP DETECTOR
CORRELATION PLOT
2015
BIKECYCLEHow do you visualize a year in
New York’s bike-sharing program?
BIKECYCLE DATA PIPELINE
322 STATIONS
102,087 ROUTES
8,080,863 RIDES
Part Three
COMMUNICATEData > Understanding
2009–2011
FAR 2009Data > Understanding
DOCUMENT ORGANIZATION
Mood
Happy
Topics
amount
Thirty Six
jan mar may jul sep novfeb apr jun aug oct dec
jan mar may jul sep novfeb apr jun aug oct dec
question 8.
please describe his mood.
Excellent!
(In disguise of a hangover).
warren, january 1
Somewhat tense,
perhaps tired.
kris, jan 7
Chummy!
kenny, jan 21
Cheery, upbeat,
Californian, unsullen.
ellen w, jan 28
Unhurried and relaxed.
jessica b, mar 20
Suffering from a cold,
sore throat.
carol, may 17
Earnestly industrious.
matthew g, may 19
Very good – exuberant
almost. More animated
and smiley than usual.
marie-claire, may 28
Pensive
(but not in a lame way).
nicholas b, july 18
Bored, oh God so bored.
mariana, september 1
Cheerful to tipsy (?)
hana, november 20
Jocular.
khoi, december 3
Festive, happy, relieved??
olga, december 31
An assessment of demeanor.
most frequent mood
76 reports, 8.8% of all moods
unique moods
300
types of negative moods
Eighty18% of all moods
reports of being “upset”
One
average temperament
Swell73.9% happy
focused to distracted ratio
9:2
synonyms for tired
Elevendrained, fading, jetlagged,
exhausted, pooped, sleeeeeepy,
sleepy, sreeepy, sweeepy, tired
and yawny
average personality
An Ambivert59.9% extrovert / 40.1% introvert
figure 11. reports of extroversion vs. introversion
figure 10. reports of happiness vs. sadness
happiness level
average temperament sadness level
degree of extroversion
degree of introversionaverage personality
question 9.
what topics were discussed?
AR08, encounters,
Asian printing, fevers.
john d, january 28
China, eggs, airplanes.
zach, february 18
Music, work, Daytum.
brian, march 21
Data visualization,
ESPN, New York, Boston,
IDEO, beer, keeping
everything from looking the
same vs. keeping everything
from looking bad.
gian, march 28
Work. Jewelry. Ikea.
sam, april 14
Blogs, Pacman,
Grand Theft Auto.
thomas, june 12
Schools attended, Daedelus,
Flying Lotus, bpm/
metronomes, Sarah Palin.
olga, august 19
Mostly family background
and computers.
aunt ruth, august 29
Work, life, ideas, data.
jordan, sepember 11
Life, the Universe and
everything! No, seriously…
warren, october 8
Eating solid foods
versus soft foods and a fear
of hard boiled eggs.
nick b, october 21
Recording in the studio,
computers, high fives.
gunnar, november 20
The breadth and depth of conversation.
figure 12. reported topics of conversation
movies discussed
Thirtyavatar, boys don’t cry, district 9,
food inc., goonies, the hangover,
ice age, legend, mad max, man on
wire, milk, million dollar baby,
nick and norah’s infinite playlist,
ratatouille, runaway, t2, tell no
one, terminator, the dark knight,
the exorcist, the hurt locker, the
neverending story, the wrestler,
top gun, tropic thunder, watchmen,
whip it, where the wild things are
and zombieland
board games discussed
Fivebalderdash, dungeons & dragons,
jenga, monopoly and scrabble
typographic discussions
17an abandoned typeface, balloon
letters, double spaces, drawing
an s, kerning, letterforms,
letterspacing, typography on
bottles, organizing type, photo
type composition, picas, points,
ragging, shipflat, titling font
families, type and type we like
music discussed
25aaliyah, animal collective, bell,
broken social scene, daedelus,
department of eagles, doveman,
edison, elliott smith, explosions in
the sky, flying lotus, grizzly bear,
here we go magic, itay talgam, jean
louis, jean luc, jonathan richman,
joy division, kevin drew, neil young,
nico muhly, prefuse 73, sam amidon,
the knife and tricky
most mentioned pet
Kingalso: francis, piper and pippin
government agencies discussed
Fivecia, fbi, homeland security, noaa
and the nsa
public personalities discussed
andy warhol, ashley olsen, balloon boy, barack obama, bill hader, bill
murray, brad bird, buckminster fuller, captain america, carl weathers,
dan barber, douglas gordon, gene kaufmann, hillary swank, jason sudeikis,
jasper johns, karim rashid, louis ck, malcolm gladwell, michael hoelke,
michael pollan, mihaly csikszentmihalyi, mitch hedberg, morgan freeman,
patrick swayze, peter arnell, robert downey jr., sarah palin, scarlett
johansson, sol lewitt, steve jobs, tiger woods, van jones, venus & serena
williams, werner herzog and wes anderson
most discussed travel destination
Mexico Cityreported 4 times
places media food work nothing
people ideas activities designthings
variety
MOOD PAGE
jan mar may jul sep novfeb apr jun aug oct dec
figure 11. reports of extroversion vs. introversion
figure 10. reports of happiness vs. sadness
happiness level
average temperament sadness level
Cheerful to tipsy (?)
hana, november 20
Jocular.
khoi, december 3
Festive, happy, relieved??
olga, december 31
types of negative moods
Eighty18% of all moods
reports of being “upset”
One
average temperament
Swell73.9% happy
focused to distracted ratio
9:2
synonyms for tired
Elevendrained, fading, jetlagged,
exhausted, pooped, sleeeeeepy,
sleepy, sreeepy, sweeepy, tired
and yawny
bivertmay jul sep novjun aug oct dec
question 8.
please describe his mood.
Excellent!
(In disguise of a hangover).
warren, january 1
Somewhat tense,
perhaps tired.
kris, jan 7
Chummy!
kenny, jan 21
Cheery, upbeat,
Californian, unsullen.
ellen w, jan 28
Unhurried and relaxed.
jessica b, mar 20
Suffering from a cold,
sore throat.
carol, may 17
vs. introversion
sadness
happiness level
t sadness level
S/M/L SCALES
S/M/L SCALES
Entire Data Set
Large
Categories of Data
Medium
Individual Data Point
Small
COLOR ADJUSTMENTS
COLOR ADJUSTMENTS
FAR10
2010–2011
FAR 2010Understanding > Expression
VISUALIZATION INSPIRATION
3D MAPPING EXPLORATION
TRIANGULATION EXPLORATIONS
FAR10 ATLAS
2012–2014
FAR 2013Understanding > Expression
WAR GAMES
Borda OCRB Landmark
Miso SourceCode
Pro Monosten
Input Sans
Condensed + Compressed
Y: 100
M: 15
C: 80
Y: 20
M: 80
Y: 60
K: 25
C: 15
Y: 100 C: 100
M: 100
Y: 100
K: 25
FAR 13 VOLUME
FAR 13 VOCABULARY
2014–2015
FAR 2014Understanding > Expression
PAGE LAYOUTS
SKETCH VISUALIZATION
SKETCH VISUALIZATION
SKETCH VISUALIZATION
SKETCH VISUALIZATION
SKETCH VISUALIZATION
VISUALIZATION ELEMENTS
Scale Connections Proximity Rotation Color
Shapes Symbols Type
318.2
Texas
Repetition Position
FINAL COVER
2015
BIKECYCLEUnderstanding > Expression
WIREFRAME
BIKECYCLE DEVELOPMENT
CITIBIKES
Design med data - Nicholas Felton
Data is the
NEW WOOD
PHOTOVIZ BOOK
SKILLSHARE CLASSES
Nicholas Felton
THANK YOUfeltron.com / @feltron

More Related Content

More from webdagene

Om å bryte tabuer på Snapchat – med Tale Maria Krohn Engvik
Om å bryte tabuer på Snapchat – med Tale Maria Krohn EngvikOm å bryte tabuer på Snapchat – med Tale Maria Krohn Engvik
Om å bryte tabuer på Snapchat – med Tale Maria Krohn Engvik
webdagene
 
Enkel og effektiv brukertesting – med Ida Aalen
Enkel og effektiv brukertesting – med Ida AalenEnkel og effektiv brukertesting – med Ida Aalen
Enkel og effektiv brukertesting – med Ida Aalen
webdagene
 
Ten realities of the internet of things – ​Alexandra Deschamps-Sonsino
Ten realities of the internet of things –  ​Alexandra Deschamps-SonsinoTen realities of the internet of things –  ​Alexandra Deschamps-Sonsino
Ten realities of the internet of things – ​Alexandra Deschamps-Sonsino
webdagene
 
Internett. Hva nå? – med Jostein Magnussen
Internett. Hva nå? – med Jostein MagnussenInternett. Hva nå? – med Jostein Magnussen
Internett. Hva nå? – med Jostein Magnussen
webdagene
 
Nysgjerrighet som drivkraft – med Louise Fuchs
Nysgjerrighet som drivkraft – med Louise FuchsNysgjerrighet som drivkraft – med Louise Fuchs
Nysgjerrighet som drivkraft – med Louise Fuchs
webdagene
 
Scaling service design and the challenge of problem-caring – Sanjay Poyzer
Scaling service design and the challenge of problem-caring – Sanjay PoyzerScaling service design and the challenge of problem-caring – Sanjay Poyzer
Scaling service design and the challenge of problem-caring – Sanjay Poyzer
webdagene
 
5 grep for kundeorientering i en digital hverdag. – med Guro Røberg og Ove Dalen
5 grep for kundeorientering i en digital hverdag. – med Guro Røberg og Ove Dalen5 grep for kundeorientering i en digital hverdag. – med Guro Røberg og Ove Dalen
5 grep for kundeorientering i en digital hverdag. – med Guro Røberg og Ove Dalen
webdagene
 
Ten realities of the internet of things - ​Alexandra Deschamps-Sonsino
Ten realities of the internet of things -  ​Alexandra Deschamps-SonsinoTen realities of the internet of things -  ​Alexandra Deschamps-Sonsino
Ten realities of the internet of things - ​Alexandra Deschamps-Sonsino
webdagene
 
Hvordan menneskesentrisk teknologi endrer kundeopplevelsen – med Claude Marie...
Hvordan menneskesentrisk teknologi endrer kundeopplevelsen – med Claude Marie...Hvordan menneskesentrisk teknologi endrer kundeopplevelsen – med Claude Marie...
Hvordan menneskesentrisk teknologi endrer kundeopplevelsen – med Claude Marie...
webdagene
 
Understanding humans – Leah Reich
Understanding humans – Leah ReichUnderstanding humans – Leah Reich
Understanding humans – Leah Reich
webdagene
 
The dark net – Jamie Bartlett
The dark net – Jamie BartlettThe dark net – Jamie Bartlett
The dark net – Jamie Bartlett
webdagene
 
UX of Story: Designing the Future of Storytelling – Mandy Mandelstein
UX of Story: Designing the Future of Storytelling  – Mandy MandelsteinUX of Story: Designing the Future of Storytelling  – Mandy Mandelstein
UX of Story: Designing the Future of Storytelling – Mandy Mandelstein
webdagene
 
Nysgjerrighet som drivkraft – med Louise Fuchs
Nysgjerrighet som drivkraft – med Louise FuchsNysgjerrighet som drivkraft – med Louise Fuchs
Nysgjerrighet som drivkraft – med Louise Fuchs
webdagene
 
The customer universe – med Gerry McGovern
The customer universe – med Gerry McGovernThe customer universe – med Gerry McGovern
The customer universe – med Gerry McGovern
webdagene
 
Jonathan MacDonald: Maximising the opportunities in a changing digital landscape
Jonathan MacDonald: Maximising the opportunities in a changing digital landscapeJonathan MacDonald: Maximising the opportunities in a changing digital landscape
Jonathan MacDonald: Maximising the opportunities in a changing digital landscape
webdagene
 
Lauren Currie: The science of doing good things
Lauren Currie: The science of doing good thingsLauren Currie: The science of doing good things
Lauren Currie: The science of doing good things
webdagene
 
Ove Dalen: Sannheten om innholdsmarkedsføring
Ove Dalen: Sannheten om innholdsmarkedsføringOve Dalen: Sannheten om innholdsmarkedsføring
Ove Dalen: Sannheten om innholdsmarkedsføring
webdagene
 
Mike Monteiro: This is the golden age of design! …and we're screwed
Mike Monteiro: This is the golden age of design! …and we're screwedMike Monteiro: This is the golden age of design! …and we're screwed
Mike Monteiro: This is the golden age of design! …and we're screwed
webdagene
 
Ida og Ida: Ta sosiale medier på alvor
Ida og Ida: Ta sosiale medier på alvorIda og Ida: Ta sosiale medier på alvor
Ida og Ida: Ta sosiale medier på alvor
webdagene
 
Jeff Gothelf: Building a culture of innovation
Jeff Gothelf: Building a culture of innovationJeff Gothelf: Building a culture of innovation
Jeff Gothelf: Building a culture of innovation
webdagene
 

More from webdagene (20)

Om å bryte tabuer på Snapchat – med Tale Maria Krohn Engvik
Om å bryte tabuer på Snapchat – med Tale Maria Krohn EngvikOm å bryte tabuer på Snapchat – med Tale Maria Krohn Engvik
Om å bryte tabuer på Snapchat – med Tale Maria Krohn Engvik
 
Enkel og effektiv brukertesting – med Ida Aalen
Enkel og effektiv brukertesting – med Ida AalenEnkel og effektiv brukertesting – med Ida Aalen
Enkel og effektiv brukertesting – med Ida Aalen
 
Ten realities of the internet of things – ​Alexandra Deschamps-Sonsino
Ten realities of the internet of things –  ​Alexandra Deschamps-SonsinoTen realities of the internet of things –  ​Alexandra Deschamps-Sonsino
Ten realities of the internet of things – ​Alexandra Deschamps-Sonsino
 
Internett. Hva nå? – med Jostein Magnussen
Internett. Hva nå? – med Jostein MagnussenInternett. Hva nå? – med Jostein Magnussen
Internett. Hva nå? – med Jostein Magnussen
 
Nysgjerrighet som drivkraft – med Louise Fuchs
Nysgjerrighet som drivkraft – med Louise FuchsNysgjerrighet som drivkraft – med Louise Fuchs
Nysgjerrighet som drivkraft – med Louise Fuchs
 
Scaling service design and the challenge of problem-caring – Sanjay Poyzer
Scaling service design and the challenge of problem-caring – Sanjay PoyzerScaling service design and the challenge of problem-caring – Sanjay Poyzer
Scaling service design and the challenge of problem-caring – Sanjay Poyzer
 
5 grep for kundeorientering i en digital hverdag. – med Guro Røberg og Ove Dalen
5 grep for kundeorientering i en digital hverdag. – med Guro Røberg og Ove Dalen5 grep for kundeorientering i en digital hverdag. – med Guro Røberg og Ove Dalen
5 grep for kundeorientering i en digital hverdag. – med Guro Røberg og Ove Dalen
 
Ten realities of the internet of things - ​Alexandra Deschamps-Sonsino
Ten realities of the internet of things -  ​Alexandra Deschamps-SonsinoTen realities of the internet of things -  ​Alexandra Deschamps-Sonsino
Ten realities of the internet of things - ​Alexandra Deschamps-Sonsino
 
Hvordan menneskesentrisk teknologi endrer kundeopplevelsen – med Claude Marie...
Hvordan menneskesentrisk teknologi endrer kundeopplevelsen – med Claude Marie...Hvordan menneskesentrisk teknologi endrer kundeopplevelsen – med Claude Marie...
Hvordan menneskesentrisk teknologi endrer kundeopplevelsen – med Claude Marie...
 
Understanding humans – Leah Reich
Understanding humans – Leah ReichUnderstanding humans – Leah Reich
Understanding humans – Leah Reich
 
The dark net – Jamie Bartlett
The dark net – Jamie BartlettThe dark net – Jamie Bartlett
The dark net – Jamie Bartlett
 
UX of Story: Designing the Future of Storytelling – Mandy Mandelstein
UX of Story: Designing the Future of Storytelling  – Mandy MandelsteinUX of Story: Designing the Future of Storytelling  – Mandy Mandelstein
UX of Story: Designing the Future of Storytelling – Mandy Mandelstein
 
Nysgjerrighet som drivkraft – med Louise Fuchs
Nysgjerrighet som drivkraft – med Louise FuchsNysgjerrighet som drivkraft – med Louise Fuchs
Nysgjerrighet som drivkraft – med Louise Fuchs
 
The customer universe – med Gerry McGovern
The customer universe – med Gerry McGovernThe customer universe – med Gerry McGovern
The customer universe – med Gerry McGovern
 
Jonathan MacDonald: Maximising the opportunities in a changing digital landscape
Jonathan MacDonald: Maximising the opportunities in a changing digital landscapeJonathan MacDonald: Maximising the opportunities in a changing digital landscape
Jonathan MacDonald: Maximising the opportunities in a changing digital landscape
 
Lauren Currie: The science of doing good things
Lauren Currie: The science of doing good thingsLauren Currie: The science of doing good things
Lauren Currie: The science of doing good things
 
Ove Dalen: Sannheten om innholdsmarkedsføring
Ove Dalen: Sannheten om innholdsmarkedsføringOve Dalen: Sannheten om innholdsmarkedsføring
Ove Dalen: Sannheten om innholdsmarkedsføring
 
Mike Monteiro: This is the golden age of design! …and we're screwed
Mike Monteiro: This is the golden age of design! …and we're screwedMike Monteiro: This is the golden age of design! …and we're screwed
Mike Monteiro: This is the golden age of design! …and we're screwed
 
Ida og Ida: Ta sosiale medier på alvor
Ida og Ida: Ta sosiale medier på alvorIda og Ida: Ta sosiale medier på alvor
Ida og Ida: Ta sosiale medier på alvor
 
Jeff Gothelf: Building a culture of innovation
Jeff Gothelf: Building a culture of innovationJeff Gothelf: Building a culture of innovation
Jeff Gothelf: Building a culture of innovation
 

Recently uploaded

Technoblade The Legacy of a Minecraft Legend.
Technoblade The Legacy of a Minecraft Legend.Technoblade The Legacy of a Minecraft Legend.
Technoblade The Legacy of a Minecraft Legend.
Techno Merch
 
NHR Engineers Portfolio 2023 2024 NISHANT RATHI
NHR Engineers Portfolio 2023 2024 NISHANT RATHINHR Engineers Portfolio 2023 2024 NISHANT RATHI
NHR Engineers Portfolio 2023 2024 NISHANT RATHI
NishantRathi18
 
UNIT V ACTIONS AND COMMANDS, FORMS AND CONTROLS.pptx
UNIT V ACTIONS AND COMMANDS, FORMS AND CONTROLS.pptxUNIT V ACTIONS AND COMMANDS, FORMS AND CONTROLS.pptx
UNIT V ACTIONS AND COMMANDS, FORMS AND CONTROLS.pptx
GOWSIKRAJA PALANISAMY
 
一比一原版(UW毕业证)西雅图华盛顿大学毕业证如何办理
一比一原版(UW毕业证)西雅图华盛顿大学毕业证如何办理一比一原版(UW毕业证)西雅图华盛顿大学毕业证如何办理
一比一原版(UW毕业证)西雅图华盛顿大学毕业证如何办理
kecekev
 
Storytelling For The Web: Integrate Storytelling in your Design Process
Storytelling For The Web: Integrate Storytelling in your Design ProcessStorytelling For The Web: Integrate Storytelling in your Design Process
Storytelling For The Web: Integrate Storytelling in your Design Process
Chiara Aliotta
 
Heuristics Evaluation - How to Guide.pdf
Heuristics Evaluation - How to Guide.pdfHeuristics Evaluation - How to Guide.pdf
Heuristics Evaluation - How to Guide.pdf
Jaime Brown
 
哪里办理美国中央华盛顿大学毕业证双学位证书原版一模一样
哪里办理美国中央华盛顿大学毕业证双学位证书原版一模一样哪里办理美国中央华盛顿大学毕业证双学位证书原版一模一样
哪里办理美国中央华盛顿大学毕业证双学位证书原版一模一样
qo1as76n
 
AHMED TALAAT ARCHITECTURE PORTFOLIO .pdf
AHMED TALAAT ARCHITECTURE PORTFOLIO .pdfAHMED TALAAT ARCHITECTURE PORTFOLIO .pdf
AHMED TALAAT ARCHITECTURE PORTFOLIO .pdf
talaatahm
 
Divertidamente SLIDE.pptxufururururuhrurid8dj
Divertidamente SLIDE.pptxufururururuhrurid8djDivertidamente SLIDE.pptxufururururuhrurid8dj
Divertidamente SLIDE.pptxufururururuhrurid8dj
lunaemel03
 
EASY TUTORIAL OF HOW TO USE CAPCUT BY: FEBLESS HERNANE
EASY TUTORIAL OF HOW TO USE CAPCUT BY: FEBLESS HERNANEEASY TUTORIAL OF HOW TO USE CAPCUT BY: FEBLESS HERNANE
EASY TUTORIAL OF HOW TO USE CAPCUT BY: FEBLESS HERNANE
Febless Hernane
 
Branding de la empresa de Bolt- 2024.pdf
Branding de la empresa de Bolt- 2024.pdfBranding de la empresa de Bolt- 2024.pdf
Branding de la empresa de Bolt- 2024.pdf
PabloMartelLpez
 
一比一原版(BU毕业证)波士顿大学毕业证如何办理
一比一原版(BU毕业证)波士顿大学毕业证如何办理一比一原版(BU毕业证)波士顿大学毕业证如何办理
一比一原版(BU毕业证)波士顿大学毕业证如何办理
peuce
 
定制美国西雅图城市大学毕业证学历证书原版一模一样
定制美国西雅图城市大学毕业证学历证书原版一模一样定制美国西雅图城市大学毕业证学历证书原版一模一样
定制美国西雅图城市大学毕业证学历证书原版一模一样
qo1as76n
 
Top Interior Designers in Bangalore.pdf1
Top Interior Designers in Bangalore.pdf1Top Interior Designers in Bangalore.pdf1
Top Interior Designers in Bangalore.pdf1
Decomart Studio
 
UNIT IV-VISUAL STYLE AND MOBILE INTERFACES.pptx
UNIT IV-VISUAL STYLE AND MOBILE INTERFACES.pptxUNIT IV-VISUAL STYLE AND MOBILE INTERFACES.pptx
UNIT IV-VISUAL STYLE AND MOBILE INTERFACES.pptx
GOWSIKRAJA PALANISAMY
 
Maximize Your Content with Beautiful Assets : Content & Asset for Landing Page
Maximize Your Content with Beautiful Assets : Content & Asset for Landing Page Maximize Your Content with Beautiful Assets : Content & Asset for Landing Page
Maximize Your Content with Beautiful Assets : Content & Asset for Landing Page
pmgdscunsri
 
原版定做(penn毕业证书)美国宾夕法尼亚大学毕业证文凭学历证书原版一模一样
原版定做(penn毕业证书)美国宾夕法尼亚大学毕业证文凭学历证书原版一模一样原版定做(penn毕业证书)美国宾夕法尼亚大学毕业证文凭学历证书原版一模一样
原版定做(penn毕业证书)美国宾夕法尼亚大学毕业证文凭学历证书原版一模一样
gpffo76j
 
Game Concept Presentation for Ukrainian Mythology Based Game With Designs
Game Concept Presentation for Ukrainian Mythology Based Game With DesignsGame Concept Presentation for Ukrainian Mythology Based Game With Designs
Game Concept Presentation for Ukrainian Mythology Based Game With Designs
184804
 
Revolutionizing the Digital Landscape: Web Development Companies in India
Revolutionizing the Digital Landscape: Web Development Companies in IndiaRevolutionizing the Digital Landscape: Web Development Companies in India
Revolutionizing the Digital Landscape: Web Development Companies in India
amrsoftec1
 
ARENA - Young adults in the workplace (Knight Moves).pdf
ARENA - Young adults in the workplace (Knight Moves).pdfARENA - Young adults in the workplace (Knight Moves).pdf
ARENA - Young adults in the workplace (Knight Moves).pdf
Knight Moves
 

Recently uploaded (20)

Technoblade The Legacy of a Minecraft Legend.
Technoblade The Legacy of a Minecraft Legend.Technoblade The Legacy of a Minecraft Legend.
Technoblade The Legacy of a Minecraft Legend.
 
NHR Engineers Portfolio 2023 2024 NISHANT RATHI
NHR Engineers Portfolio 2023 2024 NISHANT RATHINHR Engineers Portfolio 2023 2024 NISHANT RATHI
NHR Engineers Portfolio 2023 2024 NISHANT RATHI
 
UNIT V ACTIONS AND COMMANDS, FORMS AND CONTROLS.pptx
UNIT V ACTIONS AND COMMANDS, FORMS AND CONTROLS.pptxUNIT V ACTIONS AND COMMANDS, FORMS AND CONTROLS.pptx
UNIT V ACTIONS AND COMMANDS, FORMS AND CONTROLS.pptx
 
一比一原版(UW毕业证)西雅图华盛顿大学毕业证如何办理
一比一原版(UW毕业证)西雅图华盛顿大学毕业证如何办理一比一原版(UW毕业证)西雅图华盛顿大学毕业证如何办理
一比一原版(UW毕业证)西雅图华盛顿大学毕业证如何办理
 
Storytelling For The Web: Integrate Storytelling in your Design Process
Storytelling For The Web: Integrate Storytelling in your Design ProcessStorytelling For The Web: Integrate Storytelling in your Design Process
Storytelling For The Web: Integrate Storytelling in your Design Process
 
Heuristics Evaluation - How to Guide.pdf
Heuristics Evaluation - How to Guide.pdfHeuristics Evaluation - How to Guide.pdf
Heuristics Evaluation - How to Guide.pdf
 
哪里办理美国中央华盛顿大学毕业证双学位证书原版一模一样
哪里办理美国中央华盛顿大学毕业证双学位证书原版一模一样哪里办理美国中央华盛顿大学毕业证双学位证书原版一模一样
哪里办理美国中央华盛顿大学毕业证双学位证书原版一模一样
 
AHMED TALAAT ARCHITECTURE PORTFOLIO .pdf
AHMED TALAAT ARCHITECTURE PORTFOLIO .pdfAHMED TALAAT ARCHITECTURE PORTFOLIO .pdf
AHMED TALAAT ARCHITECTURE PORTFOLIO .pdf
 
Divertidamente SLIDE.pptxufururururuhrurid8dj
Divertidamente SLIDE.pptxufururururuhrurid8djDivertidamente SLIDE.pptxufururururuhrurid8dj
Divertidamente SLIDE.pptxufururururuhrurid8dj
 
EASY TUTORIAL OF HOW TO USE CAPCUT BY: FEBLESS HERNANE
EASY TUTORIAL OF HOW TO USE CAPCUT BY: FEBLESS HERNANEEASY TUTORIAL OF HOW TO USE CAPCUT BY: FEBLESS HERNANE
EASY TUTORIAL OF HOW TO USE CAPCUT BY: FEBLESS HERNANE
 
Branding de la empresa de Bolt- 2024.pdf
Branding de la empresa de Bolt- 2024.pdfBranding de la empresa de Bolt- 2024.pdf
Branding de la empresa de Bolt- 2024.pdf
 
一比一原版(BU毕业证)波士顿大学毕业证如何办理
一比一原版(BU毕业证)波士顿大学毕业证如何办理一比一原版(BU毕业证)波士顿大学毕业证如何办理
一比一原版(BU毕业证)波士顿大学毕业证如何办理
 
定制美国西雅图城市大学毕业证学历证书原版一模一样
定制美国西雅图城市大学毕业证学历证书原版一模一样定制美国西雅图城市大学毕业证学历证书原版一模一样
定制美国西雅图城市大学毕业证学历证书原版一模一样
 
Top Interior Designers in Bangalore.pdf1
Top Interior Designers in Bangalore.pdf1Top Interior Designers in Bangalore.pdf1
Top Interior Designers in Bangalore.pdf1
 
UNIT IV-VISUAL STYLE AND MOBILE INTERFACES.pptx
UNIT IV-VISUAL STYLE AND MOBILE INTERFACES.pptxUNIT IV-VISUAL STYLE AND MOBILE INTERFACES.pptx
UNIT IV-VISUAL STYLE AND MOBILE INTERFACES.pptx
 
Maximize Your Content with Beautiful Assets : Content & Asset for Landing Page
Maximize Your Content with Beautiful Assets : Content & Asset for Landing Page Maximize Your Content with Beautiful Assets : Content & Asset for Landing Page
Maximize Your Content with Beautiful Assets : Content & Asset for Landing Page
 
原版定做(penn毕业证书)美国宾夕法尼亚大学毕业证文凭学历证书原版一模一样
原版定做(penn毕业证书)美国宾夕法尼亚大学毕业证文凭学历证书原版一模一样原版定做(penn毕业证书)美国宾夕法尼亚大学毕业证文凭学历证书原版一模一样
原版定做(penn毕业证书)美国宾夕法尼亚大学毕业证文凭学历证书原版一模一样
 
Game Concept Presentation for Ukrainian Mythology Based Game With Designs
Game Concept Presentation for Ukrainian Mythology Based Game With DesignsGame Concept Presentation for Ukrainian Mythology Based Game With Designs
Game Concept Presentation for Ukrainian Mythology Based Game With Designs
 
Revolutionizing the Digital Landscape: Web Development Companies in India
Revolutionizing the Digital Landscape: Web Development Companies in IndiaRevolutionizing the Digital Landscape: Web Development Companies in India
Revolutionizing the Digital Landscape: Web Development Companies in India
 
ARENA - Young adults in the workplace (Knight Moves).pdf
ARENA - Young adults in the workplace (Knight Moves).pdfARENA - Young adults in the workplace (Knight Moves).pdf
ARENA - Young adults in the workplace (Knight Moves).pdf
 

Design med data - Nicholas Felton

  • 5. ACTIONS > PATTERNS > INFORMATIONVisualization without Intermediation
  • 11. DESIGNER PROGRAMMER JOURNALIST STATISTICIAN color, typography, composition & texture data, scripting, & interactivity research, narrative & accountability analysis & correlation
  • 15. Ask a QUESTIONWhat does a year look like? Can you visualize a wine?
  • 16. YES NOHAS THE EVENT HAPPENED?
  • 21. GORDON PAUL FELTON, 1929–2010
  • 23. Applications Audio Recordings Books Calendars Certificates Driver’s Licenses Expense Logs Family Trees Fast Trak Statements Itineraries Legal Documents Letters Lists Medical Records Newspaper Clippings Notebooks Passports Photos Police Certification Postcards Receipts School Reports Slides Tickets Union Registration Form AVAILABLE SOURCES4,348 items in 25 categories
  • 24. 1 EKG
  • 25. Jul 24, 1989: Vale of Rheidal & Devils bridge on old train out of Aberriswyth, walk to Devils cauldron. Nick checks out tidepools at Aber--. N&M move into camper. Jul 25, 1989: Oliver taken to beauty parlor. Jags over house low level. Meet Mervyn Evans at pub for lunch in local. Visit Newtown Montgomery & Welschpool. Interesting ruin of border fortress at Mowtgy. Jul 26, 1989: To Fistiniog to very visit to Slate Minesa Museum. Visit damm & locked in for 45mins. Beautiful drive by coast through Aberdovey. Drink with Russ & Anita & call Wilson’s Jul 27, 1989: Dep. Wales to Loboro. Visit aerospace museum at Cosford. Drop by Brush, David Harris. To Les & Gail & brief visit with Les Hollingsworth. Dinner for N&M at L’boro McDonald Jul 28, 1989: Lunch at White House Kegworth. Breakfast at Cafe. To Nottingham Castle Robinhood Adventure. ‘Out of Order.’ Visit still positive Dad ‘outlaw’ N&M are ‘Pardoned’ by King. Movie Karate Kid III. N&M call Carol 4,440 CALENDAR ENTRIES
  • 26. Jun 8, 1959 Mr. Gordon Felton, c/o Mr. Ed. Brophy, 248-05 87th Avenue, Bellerose 6/ New York Oct 18, 1960 G. Felton, Esq. (??), Apt. 103, 451 Lee St., Oakland. California. Jun 14, 1962 Mr. Gordon Felton, 22 Terra Vista, San Francisco 05, California Sep 18, 1962 Mr. Gordon Felton, 22 Terra Vista Ap. E-2, San Francisco, California Sep 19, 1962 Mr. Gordon Felton, 22. Terra Vista Ap. E-2, San Francisco, California Sep 16, 1962 Mr. Gordon Felton, Terra Vista E-2, San Francisco, California Sep 26, 1962 Mr. Gordon Felton, 22 Terra Viesta, San Francisco, California 169 RECEIVED POSTCARDS
  • 27. Jul 27, 1957 Havana, Cuba Aug 4, 1957 Fort Erie, Ontario, Canada Dec 2, 1957 Malton, Canada May 5, 1958 Melsbroek Air Base, De Kleetlaan, Machelen, Flemish Region, Belgium May 5, 1958 Berlin Tempelhof Airport, Germany May 9, 1958 Melsbroek Air Base, De Kleetlaan, Machelen, Flemish Region, Belgium May 9, 1958 Montreal Airport, Roméo-Vachon Boulevard North, Montreal, Quebec, Canada Sep 14, 1959 Toronto, Canada Oct 18, 1959 Malton, Canada Feb 24, 1960 Buffalo, NY Dec 12, 1961 San Francisco, CA Jan 2, 1962 San Francisco, CA Jan 2, 1962 San Francisco, CA Jan 2, 1962 San Francisco, CA Jan 2, 1962 San Francisco, CA Jan 3, 1962 San Francisco, CA 239 PASSPORT STAMPS
  • 28. Montevideo Buenos Aires Cape of Good Hope Cape Town Johannesburg Iguacu Rio De Janeiro Ascotan - Chile La Paz Brasilia Cuzco Macchu Pichu Lima - Peru Arusha Ngorongoro Crater Manaos KNOWN CONTEXT
  • 37. Encounter Date Jan 28, 2009 Name Adam B. Card No. 68 Relationship Friend Friendship Duration 5 years Encounter Length 1 hour Activities Talking, drinking, congratulating, planning sushi Mood happy, engaged Where Shebeen Elsewhere No Eat No Drink Stella(s) Transportation No Conversation Topics Work, wrestling in studio, our fathers, skiing, Feltron AR, letterpress and Willy, sushi, printing in China Favorite Moment seeing/receiving/ feeling business card & leaving happier than I came. Anything Else Nicholas instigated this encounter. Tangential encounters with people I knew already: 11 Tangential encounters with people I just met: 3 SAMPLE SURVEY RESPONSENo. 37 of 560
  • 40. Metadata Data EMAIL Google SMS Apple / ATT CHAT Facebook PHONE ATT MAIL USPS CONVERSATION COMM. SOURCES3 online / 3 offline
  • 41. Who with Conversation Type Greeting, Non-Verbal, Pleasantry, Functional, Sporadic, Chat, Question, Answer, Meeting, Telephone, Video Conference, Breakfast, Brunch, Lunch, Dinner, Coffee, Drink, Other Non-Verbal Type Wave, Smile, Nod, Raise Eyebrows, Hand Shake, Hug, Kiss, Point, Wink, Fist Bump, Hi-Five, Other Greeting Type Good morning, What’s up?, Dude, Hey, Hi, Hello, How are you?, Nice to meet you, Bye, Goodbye, Good night, Take care, See you, Later, Other Pleasantry Type Thank you, Thanks, Bless you, Pardon me, Excuse me, Sorry, Other Description Location Time Duration Momentary, 1 minute, 2 minutes, 3 minutes, 5 minutes, 10 minutes, 15 minutes, 30 minutes, 1 hour, Other FULCRUM CONV. SURVEYFinal version
  • 42. Who with: Olga Conversation Type: Greeting, Non-Verbal, Lunch Non-Verbal Type: Kiss Greeting Type: Hello Pleasantry Type: Description: Olga’s rehearsal schedule. delicious flat whole wheat ev- erything bagel with whitefish and avocado lunch. Dropbox camera roll backup. The definition of scrappy. Location: Home Coordinates: 40.713337, -73.949233 Date: September 24, 2015 Time: 13:07 – 13:45 Duration: 38m SAMPLE CONV. ENTRYNo. 9,640 of 12,707
  • 48. Location Calendar Calendar Calendar Digital Analog Activity Weather Body CarWork Sleep Photos MEDIA Last.fm DATA SOURCES2005
  • 49. Location Human App Day One Rove Lapka BAM Moves App Automatic Breeze Photo Exif Data Activity Fitbit Nike Fuelband Human App Trace App Moves App Basis Watch Nike Running Skitracks App Healthkit Weather Weather Underground Day One Body Withings Scale Lapka BAM Basis Watch Car Automatic Work Github RescueTime Dropbox Sleep Basis Watch Photos Narrative Clip Camera Roll MEDIA Netflix Kindle Last.fm Soundcloud Amazon Prime DATA SOURCES2014 Instagram
  • 57. DATA ACCESSServices used Access via API Lapka BAM Instagram Fitbit Moves Hacks Required Basis Watch Netflix Direct Download Automatic RescueTime Day One Withings Scale Skitracks App Best Worse NO DATA Soundcloud Amazon Prime Kindle DropboxLast.fm
  • 58. Part Two COMPREHENDData > Understanding
  • 59. 2009–2011 FAR 2009Data > Understanding
  • 60. BASIC DATA TYPES yes/no or 0/1 Boolean YES 1.0 HELLO!whole or decimal positive or negative Number free text or categories Text
  • 62. Sad Happy -5 +5 Introverted Extroverted -5 +5 RATING MOOD RESPONSESWith Amazon Mechanical Turk Turk Interface
  • 63. :) 5 adventurous 3.2 affable 3.2 agitated -5 agreeable 5 alert 2.4 amiable 3 amicable 1.6 animated 4 anticipation -0.6 anxious -0.8 appreciated 3.2 appreciative 5 apprehensive -2 approachable 3.2 at ease 4 attentive 0 attuned 1.2 awake 0.6 awesome 5 ball busted -5 beatific 3.2 beery -0.4 bemused 5 boozed 0.6 bored -3.2 bouyant 5 bubbling 5 bummed -5 buoyant 3.2 busy 0 buzzy 3.2 Californian 0.4 calm 0.8 calm-ish 1 careful -0.6 cautious -0.8 celebratory 4 charming 5 chatty 1.8 cheered up 5 cheerful 5 cheery 5 chill 1.2 chipper 5 chirpy 2.4 chopsticks 0.8 chummy 4 INDEXED MOOD RESPONSESMoods 1–48 of 300
  • 64. Processing seeks to ruin the careers of talented designers by tempting them away from their usual tools and into the world of programming and computation. Similarly, the project is designed to turn engineers and computer scientists to less gainful employment as artists and designers. PROCESSING MISSION STATEMENTwww.processing.org
  • 66. 2010–2011 FAR 2010Data > Understanding
  • 68. Montevideo -34.883335 -56.166668 2 Buenos Aires -34.608418 -58.37316 4 Cape of Good Hope -34.35869 18.475363 2 Cape Town -33.92479 18.429916 12 Johannesburg -26.204445 28.045555 1 Iguacu -25.683332 -54.433334 29 Rio De Janeiro -22.90354 -43.209587 20 Ascotan - Chile -22.442776 -68.92286 1 La Paz -16.49901 -68.14625 5 Brasilia -14.235004 -51.92528 14 Cuzco -13.525 -71.97222 13 Macchu Pichu -13.163611 -72.5459 12 Lima - Peru -12.043333 -77.028336 2 Arusha -3.365789 36.67445 4 Ngorongoro Crater -3.1740036 35.563892 53 Manaos -3.1071923 -60.026127 3 GEOCODING PHOTOS
  • 70. 2012–2014 FAR 2013Data > Understanding
  • 72. CLEANING CONVERSATIONSFulcrum data Dec 27, 2014 Jan 27, 2014 Jan 4: 9h 2m Cleaning
  • 73. Corpus Word Count: 6,904,901 Unique Word Count: 117,194 Most frequent word is ‘the’ appearing 196,414 times Top Interrogatives: who: 4,080 what: 5,808 when: 6,476 where: 2,892 why: 1,593 how: 6,435 Profanities: hell 172 shit 112 damn 112 sex 82 fuck 78 dick 35 dong 33 fanny 30 screw 29 balls 29 negro 26 dyke 23 ass 23 xxx 21 crap 14 bastard 13 queer 12 titty 11 poop 11 bitch 9 fart 8 vibrator 7 pussy 7 porn 7 bugger 7 sperm 6 pimp 6 homo 6 piss 5 penis 5 boobs 5 WORD FREQUENCYWordCount_071714a
  • 74. she 2696 whether 2453 him 1901 says 1740 tell 1657 going 1546 say 1464 ask 1348 asks 1330 working 943 getting 936 zoo 846 ill 838 being 767 yes 697 talk 665 dinner 642 nice 612 tomorrow 607 show 570 office 560 doing 556 king 542 drew 490 looking 474 went 473 wedding 472 trip 467 car 452 long 452 coming 436 can’t 428 place 421 little 420 happy 416 coffee 411 wants 405 food 400 building 388 down 387 yeah 387 trying 372 eat 371 cool 368 maybe 364 old 364 running 360 said 358 run 356 better 353 chat 353 soon 347 small 339 bad 337 really 335 something 335 water 334 morning 333 making 332 probably 329 tonight 329 give 328 put 328 why 327 2013 MOST SENT WORDSVocabularyPlot_071514a
  • 75. click 15040 informa… 13765 address 13679 view 13499 percent 13056 price 11725 account 11462 code 11149 shipping 10750 emails 10609 offer 9985 sent 9693 payment 9634 customer 9577 transact… 9469 receive 9044 message 9021 twitter 8984 list 8927 details 8717 save 8306 sale 7948 change 7889 these 7456 privacy 7431 pm 7172 deal 7171 preferen… 6829 wrote 6680 follow 6632 contact 6470 read 6259 learn 6122 online 6099 music 6002 stock 5808 questions 5762 store 5725 received 5678 add 5664 reply 5479 policy 5471 available 5425 shop 5291 deals 5199 service 5188 tickets 4990 visit 4925 net 4895 image 4869 rights 4819 member 4637 share 4622 log 4618 page 4590 subject 4573 reserved 4554 terms 4494 amount 4451 valid 4441 card 4412 photos 4388 members 4296 est 4271 2013 MOST RECEIVED WORDSVocabularyPlot_071514a
  • 76. “Ryan Case” - Conversation 195.1393 - ryan 142.47809 - ryans 101.06998 - minutiae 83.135025 - work 81.84209 - bonnie 75.954185 - facebook 61.653275 - app 52.95851 - going 52.938576 - new 51.793407 - lunch 4pm - All Communication 2445.5276 - | 2037.5258 - learn 1997.6616 - - 1216.178 - email 1206.7687 - new 1097.3185 - us 1080.9609 - will 1070.2032 - pm 1028.2096 - 2013 943.6468 - can TERM FREQUENCY INVERSE DOCUMENT FREQUENCYTF_IDF2_082714A
  • 77. >>> conversation = nltk.Text(word- lists.words(‘AR13_conversation. txt’)) >>> conversation.collocations() Building collocations list new york; annual report; san francisco; say yes; last night; would like; dirty projectors; cross country; mill valley; moves app; fuel band; national geographic; small latte; reporter app; las vegas; palo alto; los angeles; hurricane sandy; ice cream; high five >>> NATURAL LANGUAGE TOOLKITPython
  • 78. Person 78701 Company 49375 City 34545 FieldTerminology 16519 StateOrCounty 12239 Country 10987 Facility 10722 Organization 10389 JobTitle 8763 Technology 4322 PrintMedia 2798 GeographicFeature 2752 OperatingSystem 1738 Holiday 1103 Continent 764 Sport 410 Region 404 Degree 394 HealthCondition 323 FinancialMarketIndex 303 Crime 281 Product 267 Movie 235 EntertainmentAward 168 Drug 141 TelevisionStation 109 MusicGroup 83 TelevisionShow 79 Automobile 73 ProfessionalDegree 46 NaturalDisaster 44 SportingEvent 24 Anatomy 5 ALCHEMY APIwww.alchemyapi.com
  • 79. TYPE RELEVANCE ENTITY SOURCE City 64% London email Person 88% Nicholas email Company 89% Facebook email Technology 16% iPhone email Country 43% Russia email Person 67% Joe Davis email Company 30% Apple email JobTitle 40% reporter facebook Person 85% Beyonce conversation Holiday 17% Christmas email JobTitle 38% Project Manager email PrintMedia 28% IL magazine email Continent 30% Europe email Anatomy 33% calf muscle sms Technology 69% iPhone email ALCHEMY APIwww.alchemyapi.com
  • 80. warrens apt 38.9319 -77.0556 Williamsburg 37.2707 -76.7075 Japan 36.2048 138.253 Bowery 40.7253 -73.9903 Brussels 50.8503 4.35171 Richardson 32.9482 -96.7297 Japan. 36.2048 138.253 Brooklyn 40.65 -73.95 manhattan 40.7903 -73.9597 nyc. 40.7144 -74.006 portlandia 45.5101 -122.975 minneapolis 44.9833 -93.2667 Oslo 59.9139 10.7522 California 36.7783 -119.418 Australia -25.2744 133.775 royal tennenbaums. 36.8508 -76.2859 GEOCODINGGoogle Maps API
  • 81. 2014–2015 FAR 2014Data > Understanding
  • 94. 2015 BIKECYCLEHow do you visualize a year in New York’s bike-sharing program?
  • 100. 2009–2011 FAR 2009Data > Understanding
  • 102. Mood Happy Topics amount Thirty Six jan mar may jul sep novfeb apr jun aug oct dec jan mar may jul sep novfeb apr jun aug oct dec question 8. please describe his mood. Excellent! (In disguise of a hangover). warren, january 1 Somewhat tense, perhaps tired. kris, jan 7 Chummy! kenny, jan 21 Cheery, upbeat, Californian, unsullen. ellen w, jan 28 Unhurried and relaxed. jessica b, mar 20 Suffering from a cold, sore throat. carol, may 17 Earnestly industrious. matthew g, may 19 Very good – exuberant almost. More animated and smiley than usual. marie-claire, may 28 Pensive (but not in a lame way). nicholas b, july 18 Bored, oh God so bored. mariana, september 1 Cheerful to tipsy (?) hana, november 20 Jocular. khoi, december 3 Festive, happy, relieved?? olga, december 31 An assessment of demeanor. most frequent mood 76 reports, 8.8% of all moods unique moods 300 types of negative moods Eighty18% of all moods reports of being “upset” One average temperament Swell73.9% happy focused to distracted ratio 9:2 synonyms for tired Elevendrained, fading, jetlagged, exhausted, pooped, sleeeeeepy, sleepy, sreeepy, sweeepy, tired and yawny average personality An Ambivert59.9% extrovert / 40.1% introvert figure 11. reports of extroversion vs. introversion figure 10. reports of happiness vs. sadness happiness level average temperament sadness level degree of extroversion degree of introversionaverage personality question 9. what topics were discussed? AR08, encounters, Asian printing, fevers. john d, january 28 China, eggs, airplanes. zach, february 18 Music, work, Daytum. brian, march 21 Data visualization, ESPN, New York, Boston, IDEO, beer, keeping everything from looking the same vs. keeping everything from looking bad. gian, march 28 Work. Jewelry. Ikea. sam, april 14 Blogs, Pacman, Grand Theft Auto. thomas, june 12 Schools attended, Daedelus, Flying Lotus, bpm/ metronomes, Sarah Palin. olga, august 19 Mostly family background and computers. aunt ruth, august 29 Work, life, ideas, data. jordan, sepember 11 Life, the Universe and everything! No, seriously… warren, october 8 Eating solid foods versus soft foods and a fear of hard boiled eggs. nick b, october 21 Recording in the studio, computers, high fives. gunnar, november 20 The breadth and depth of conversation. figure 12. reported topics of conversation movies discussed Thirtyavatar, boys don’t cry, district 9, food inc., goonies, the hangover, ice age, legend, mad max, man on wire, milk, million dollar baby, nick and norah’s infinite playlist, ratatouille, runaway, t2, tell no one, terminator, the dark knight, the exorcist, the hurt locker, the neverending story, the wrestler, top gun, tropic thunder, watchmen, whip it, where the wild things are and zombieland board games discussed Fivebalderdash, dungeons & dragons, jenga, monopoly and scrabble typographic discussions 17an abandoned typeface, balloon letters, double spaces, drawing an s, kerning, letterforms, letterspacing, typography on bottles, organizing type, photo type composition, picas, points, ragging, shipflat, titling font families, type and type we like music discussed 25aaliyah, animal collective, bell, broken social scene, daedelus, department of eagles, doveman, edison, elliott smith, explosions in the sky, flying lotus, grizzly bear, here we go magic, itay talgam, jean louis, jean luc, jonathan richman, joy division, kevin drew, neil young, nico muhly, prefuse 73, sam amidon, the knife and tricky most mentioned pet Kingalso: francis, piper and pippin government agencies discussed Fivecia, fbi, homeland security, noaa and the nsa public personalities discussed andy warhol, ashley olsen, balloon boy, barack obama, bill hader, bill murray, brad bird, buckminster fuller, captain america, carl weathers, dan barber, douglas gordon, gene kaufmann, hillary swank, jason sudeikis, jasper johns, karim rashid, louis ck, malcolm gladwell, michael hoelke, michael pollan, mihaly csikszentmihalyi, mitch hedberg, morgan freeman, patrick swayze, peter arnell, robert downey jr., sarah palin, scarlett johansson, sol lewitt, steve jobs, tiger woods, van jones, venus & serena williams, werner herzog and wes anderson most discussed travel destination Mexico Cityreported 4 times places media food work nothing people ideas activities designthings variety MOOD PAGE
  • 103. jan mar may jul sep novfeb apr jun aug oct dec figure 11. reports of extroversion vs. introversion figure 10. reports of happiness vs. sadness happiness level average temperament sadness level Cheerful to tipsy (?) hana, november 20 Jocular. khoi, december 3 Festive, happy, relieved?? olga, december 31 types of negative moods Eighty18% of all moods reports of being “upset” One average temperament Swell73.9% happy focused to distracted ratio 9:2 synonyms for tired Elevendrained, fading, jetlagged, exhausted, pooped, sleeeeeepy, sleepy, sreeepy, sweeepy, tired and yawny bivertmay jul sep novjun aug oct dec question 8. please describe his mood. Excellent! (In disguise of a hangover). warren, january 1 Somewhat tense, perhaps tired. kris, jan 7 Chummy! kenny, jan 21 Cheery, upbeat, Californian, unsullen. ellen w, jan 28 Unhurried and relaxed. jessica b, mar 20 Suffering from a cold, sore throat. carol, may 17 vs. introversion sadness happiness level t sadness level S/M/L SCALES
  • 104. S/M/L SCALES Entire Data Set Large Categories of Data Medium Individual Data Point Small
  • 114. Borda OCRB Landmark Miso SourceCode Pro Monosten
  • 115. Input Sans Condensed + Compressed
  • 116. Y: 100 M: 15 C: 80 Y: 20 M: 80 Y: 60 K: 25 C: 15 Y: 100 C: 100 M: 100 Y: 100 K: 25
  • 126. VISUALIZATION ELEMENTS Scale Connections Proximity Rotation Color Shapes Symbols Type 318.2 Texas Repetition Position