TEDGlobal 2010
David McCandless: The beauty of data visualization
Dejvid Mekkendls: Čarolija vizualizacije informacija
Filmed:
Readability: 4.3
3,250,094 views
Dejvid Mekkendls pretvara složene nizove podataka, kao što su vojni budžeti širom sveta, medijske izveštaje, promene statusa na Fejsbuku i još mnogo toga, u skladne i jednostavne dijagrame. Predlaže da dizajn podataka bude alatka uz pomoć koje ćemo nalaziti put kroz svakodnevnu poplavu informacija, tako što ćemo uočavati jedinstvene sheme i veze i tako možda moći da svet sagledamo iz drugačijeg ugla.
David McCandless - Data journalist
David McCandless draws beautiful conclusions from complex datasets -- thus revealing unexpected insights into our world. Full bio
David McCandless draws beautiful conclusions from complex datasets -- thus revealing unexpected insights into our world. Full bio
Double-click the English transcript below to play the video.
00:15
It feels like we're all suffering
0
0
2000
Čini se da smo svi izloženi
00:17
from information overload or data glut.
1
2000
3000
bombardovanju podacima i da smo preopterećeni informacijama.
00:20
And the good news is there might be an easy solution to that,
2
5000
2000
Dobro je što tome svemu možda i možemo lako doskočiti
00:22
and that's using our eyes more.
3
7000
2000
tako što ćemo se više oslanjati na svoj vid.
00:24
So, visualizing information, so that we can see
4
9000
2000
Dakle, vizualizacijom podataka, možemo da vidimo
00:26
the patterns and connections that matter
5
11000
3000
sheme i veze koje su od značaja,
00:29
and then designing that information so it makes more sense,
6
14000
3000
da preoblikujemo informacije tako da imaju više smisla
00:32
or it tells a story,
7
17000
2000
ili da ispričamo neku priču
00:34
or allows us to focus only on the information that's important.
8
19000
3000
ili da se jednostavno usredsredimo samo na informacije koje su nam važne.
00:38
Failing that, visualized information can just look really cool.
9
23000
3000
Osim toga, vizualizivane informacije ponekad izgledaju veoma lepo.
00:41
So, let's see.
10
26000
2000
Hajde da pogledamo.
00:45
This is the $Billion Dollar o-Gram,
11
30000
2000
Ovo je Billion Dollar Gram (dijagram milijardu dolara)
00:47
and this image arose
12
32000
2000
i ta je slika nastala kao posledica
00:49
out of frustration I had
13
34000
2000
frustracije koju sam osećao
00:51
with the reporting of billion-dollar amounts in the press.
14
36000
2000
kad bih u štampi pisao o iznosima od milijardu dolara.
00:53
That is, they're meaningless without context:
15
38000
3000
Ti podaci su besmisleni ako nisu u kontekstu.
00:56
500 billion for this pipeline,
16
41000
2000
500 milijardi za ovaj cevovod.
00:58
20 billion for this war.
17
43000
2000
20 milijardi za onaj rat.
01:00
It doesn't make any sense, so the only way to understand it
18
45000
2000
Nema nikakvog smisla, i jedini način da išta razumete
01:02
is visually and relatively.
19
47000
2000
jeste da se podatak prikaže vizuelno i u odnosu na nešto.
01:04
So I scraped a load of reported figures
20
49000
2000
I tako sam skupio gomilu brojki o kojima se izveštava
01:06
from various news outlets
21
51000
2000
iz različitih novinskih agencija
01:08
and then scaled the boxes according to those amounts.
22
53000
3000
i prikazao ih pravougaonicima čija veličina odgovara tim iznosima.
01:11
And the colors here represent the motivation behind the money.
23
56000
3000
Boje ovde predstavljaju motivaciju koja stoji iza novca.
01:14
So purple is "fighting,"
24
59000
3000
Ljubičasta predstavlja ratovanje,
01:17
and red is "giving money away," and green is "profiteering."
25
62000
3000
a crvena doniranje novca, dok je zelena gomilanje zarade.
01:20
And what you can see straight away
26
65000
2000
I odmah se može videti
01:22
is you start to have a different relationship to the numbers.
27
67000
2000
da postoji drugačiji odnos prema brojevima.
01:24
You can literally see them.
28
69000
2000
Bukvalno ih vidite.
01:26
But more importantly, you start to see
29
71000
2000
Ali, što je još važnije, počinjete da uviđate
01:28
patterns and connections between numbers
30
73000
2000
sheme i veze među brojevima
01:30
that would otherwise be scattered across multiple news reports.
31
75000
3000
koje bi inače ostale nezapažene u moru novinskih izveštaja.
01:33
Let me point out some that I really like.
32
78000
3000
Pokazaću vam neke koje mi se veoma dopadaju.
01:36
This is OPEC's revenue, this green box here --
33
81000
2000
Ovo je prihod OPEKa, ovaj zeleni pravougaonik -
01:38
780 billion a year.
34
83000
2000
780 milijardi godišnje.
01:40
And this little pixel in the corner -- three billion --
35
85000
3000
A ovaj mali piksel u uglu - tri milijarde -
01:43
that's their climate change fund.
36
88000
3000
to je njihov fond za borbu protiv klimatskih promena.
01:46
Americans, incredibly generous people --
37
91000
2000
Amerikanci, neverovatno darežljivi ljudi -
01:48
over 300 billion a year, donated to charity every year,
38
93000
3000
doniraju u dobrotvorne svrhe preko 300 milijardi godišnje,
01:51
compared with the amount of foreign aid
39
96000
2000
u poređenju sa iznosom inostrane pomoći
01:53
given by the top 17 industrialized nations
40
98000
2000
koja dolazi od 17 najrazvijenijih zemalja
01:55
at 120 billion.
41
100000
2000
što iznosi 120 milijardi.
01:57
Then of course,
42
102000
2000
A onda, naravno,
01:59
the Iraq War, predicted to cost just 60 billion
43
104000
2000
rat u Iraku, za koji su predviđali da će da košta 60 milijardi
02:01
back in 2003.
44
106000
3000
2003. godine.
02:04
And it mushroomed slightly. Afghanistan and Iraq mushroomed now
45
109000
3000
Malčice je premašio očekivanja. Avganistan je narastao do
02:07
to 3,000 billion.
46
112000
3000
3000 milijardi danas.
02:10
So now it's great
47
115000
2000
Sada je to izvanredno
02:12
because now we have this texture, and we can add numbers to it as well.
48
117000
2000
jer sada imamo teksturu, i možemo joj dodavati brojeve.
02:14
So we could say, well, a new figure comes out ... let's see African debt.
49
119000
3000
Mogli bismo reći, na primer, nova brojka se pomalja ... da pogledamo afrički dug.
02:17
How much of this diagram do you think might be taken up
50
122000
2000
Koju površinu ovog dijagrama mislite da zauzima
02:19
by the debt that Africa owes to the West?
51
124000
2000
dugovanje Afrike prema zapadu?
02:21
Let's take a look.
52
126000
2000
Hajde da pogledamo.
02:23
So there it is:
53
128000
2000
Evo ga.
02:25
227 billion is what Africa owes.
54
130000
2000
227 milijardi duguje Afrika.
02:27
And the recent financial crisis,
55
132000
2000
A ova poslednja finansijska kriza -
02:29
how much of this diagram might that figure take up?
56
134000
2000
šta mislite koliko ovog dijagrama može zauzeti ta cifra?
02:31
What has that cost the world? Let's take a look at that.
57
136000
3000
Koliko je to koštalo ceo svet? Hajde da to pogledamo.
02:34
Dooosh -- Which I think is the appropriate sound effect
58
139000
3000
Plus! Mislim da je to odgovarajući zvučni efekat
02:37
for that much money:
59
142000
2000
za tu količinu novca.
02:39
11,900 billion.
60
144000
4000
11900 milijardi.
02:45
So, by visualizing this information,
61
150000
2000
Pretvaranjem informacije u sliku,
02:47
we turned it into a landscape
62
152000
2000
pretvorili smo je u pejzaž
02:49
that you can explore with your eyes,
63
154000
2000
koji možete istraživati gledajući ga,
02:51
a kind of map really, a sort of information map.
64
156000
2000
to postaje neka vrsta mape, mapa informacija.
02:53
And when you're lost in information,
65
158000
2000
A kada se ne snalazite u informacijama,
02:55
an information map is kind of useful.
66
160000
3000
mapa informacija je nekako korisna.
02:58
So I want to show you another landscape now.
67
163000
2000
Prikazaću vam još jedan pejzaž.
03:00
We need to imagine what a landscape
68
165000
2000
Treba da zamislimo kakav je to pejzaž
03:02
of the world's fears might look like.
69
167000
3000
koji bi oslikavao strahove čovečanstva.
03:05
Let's take a look.
70
170000
2000
Pogledajmo.
03:07
This is Mountains Out of Molehills,
71
172000
2000
Ovo su planine i brežuljci
03:09
a timeline of global media panic.
72
174000
2000
vremenska osa globalne panike.
03:11
(Laughter)
73
176000
2000
(smeh)
03:13
So, I'll label this for you in a second.
74
178000
2000
Obeležiću vam ovo začas.
03:15
But the height here, I want to point out,
75
180000
2000
Ali ovo uzvišenje, naročito hoću da istaknem,
03:17
is the intensity of certain fears
76
182000
2000
jeste intenzitet određenih strahova,
03:19
as reported in the media.
77
184000
2000
kako o njima izveštavaju mediji.
03:21
Let me point them out.
78
186000
2000
Pokazaću vam.
03:23
So this, swine flu -- pink.
79
188000
4000
Ovo - svinjski grip - ružičasto.
03:27
Bird flu.
80
192000
2000
Ptičiji grip.
03:29
SARS -- brownish here. Remember that one?
81
194000
3000
SARS - braonkasto, ovde. Sećate li se toga?
03:32
The millennium bug,
82
197000
3000
Milenijumska buba -
03:35
terrible disaster.
83
200000
2000
užasna katastrofa.
03:37
These little green peaks
84
202000
2000
ovi mali zeleni vrhovi
03:39
are asteroid collisions.
85
204000
2000
predstavljaju sudare asteroida.
03:41
(Laughter)
86
206000
2000
(smeh)
03:43
And in summer, here, killer wasps.
87
208000
2000
A u leto, ovde, pčele ubice.
03:45
(Laughter)
88
210000
8000
(smeh)
03:53
So these are what our fears look like
89
218000
2000
Ovako izgledaju naši strahovi
03:55
over time in our media.
90
220000
2000
u medijima u određenom vremenskom periodu.
03:57
But what I love -- and I'm a journalist --
91
222000
2000
Ali ono što mi se posebno dopada - a ja sam novinar -
03:59
and what I love is finding hidden patterns; I love being a data detective.
92
224000
3000
i naročito uživam u tome da pronalazim skrivene sheme; volim da budem detektiv za podatke.
04:02
And there's a very interesting and odd pattern hidden in this data
93
227000
3000
U ovim se podacima krije naročito neobična i zanimljiva shema
04:05
that you can only see when you visualize it.
94
230000
2000
koju možete primetiti samo ako je vizualizujete.
04:07
Let me highlight it for you.
95
232000
2000
Obeležiću je.
04:09
See this line, this is a landscape for violent video games.
96
234000
3000
Pogledajte ovu liniju. Ovo je model koji predstavlja nasilne video igre.
04:12
As you can see, there's a kind of odd, regular pattern in the data,
97
237000
3000
Kao što vidite, postoji naročito, pravilno ponavljanje u podacima
04:15
twin peaks every year.
98
240000
2000
vršne vrednosti dva puta godišnje
04:17
If we look closer, we see those peaks occur
99
242000
2000
Ako pogledamo detaljnije, videćemo da se vršne vrednosti
04:19
at the same month every year.
100
244000
3000
postižu istog meseca svake godine.
04:22
Why?
101
247000
2000
Zašto?
04:24
Well, November, Christmas video games come out,
102
249000
2000
Pa, u novembru se puštaju u prodaju Božićne video igre,
04:26
and there may well be an upsurge in the concern about their content.
103
251000
3000
i moguće je da zabrinutost raste zbog njihovog sadržaja.
04:29
But April isn't a particularly massive month
104
254000
3000
Ali april nije mesec naročito opterećen
04:32
for video games.
105
257000
2000
video igrama
04:34
Why April?
106
259000
2000
Zbog čega april?
04:36
Well, in April 1999 was the Columbine shooting,
107
261000
3000
Pa, u aprilu 1999. dogodila se pucnjava u Kolombajnu.
04:39
and since then, that fear
108
264000
2000
i otada, toga se straha podsećamo
04:41
has been remembered by the media
109
266000
2000
preko medija
04:43
and echoes through the group mind gradually through the year.
110
268000
2000
i on odzvanja našom kolektivnom svešću preko godine.
04:45
You have retrospectives, anniversaries,
111
270000
3000
Imate retrospektive, godišnjice,
04:48
court cases, even copy-cat shootings,
112
273000
3000
sudske procese, čak i druge pucnjave po uzoru na ovu
04:51
all pushing that fear into the agenda.
113
276000
3000
što sve taj strah stavlja u prvi plan.
04:54
And there's another pattern here as well. Can you spot it?
114
279000
2000
A postoji još jedna shema u tome. Da li je uočavate?
04:56
See that gap there? There's a gap,
115
281000
2000
Vidite ovaj razmak? Tu postoji nepravilnost
04:58
and it affects all the other stories.
116
283000
2000
koja utiče na sve druge priče.
05:00
Why is there a gap there?
117
285000
2000
Zašto ovde imamo razmak?
05:02
You see where it starts? September 2001,
118
287000
3000
Vidite li kada počinje? Septembar 2001,
05:05
when we had something very real
119
290000
2000
kada se pojavilo nešto veoma stvarno
05:07
to be scared about.
120
292000
2000
čega se trebalo plašiti.
05:09
So, I've been working as a data journalist for about a year,
121
294000
3000
Kao novinar sam istraživao podatke oko godinu dana,
05:12
and I keep hearing a phrase
122
297000
2000
i stalno sam slušao fraze
05:14
all the time, which is this:
123
299000
3000
slične ovoj:
05:17
"Data is the new oil."
124
302000
2000
"Podaci su nafta današnjice."
05:19
Data is the kind of ubiquitous resource
125
304000
3000
A podaci i jesu sveprisutni resurs
05:22
that we can shape to provide new innovations and new insights,
126
307000
3000
koji možemo oblikovati da bismo stvorili nove izume ili otvorili neke nove poglede na svet
05:25
and it's all around us, and it can be mined very easily.
127
310000
3000
i nalaze se svuda oko nas i veoma lako se mogu vaditi.
05:28
It's not a particularly great metaphor in these times,
128
313000
3000
U današnje vreme to i nije naročito uspela metafora,
05:31
especially if you live around the Gulf of Mexico,
129
316000
3000
naročito ako živite u blizini Meksičkog zaliva,
05:34
but I would, perhaps, adapt this metaphor slightly,
130
319000
2000
zato bih je malo prilagodio,
05:36
and I would say that data is the new soil.
131
321000
3000
i rekao bih da su podaci plodno tlo današnjice.
05:40
Because for me, it feels like a fertile, creative medium.
132
325000
3000
Jer, za mene, to i jeste plodan, kreativni medijum.
05:43
Over the years, online,
133
328000
2000
Vremenom smo onlajn
05:45
we've laid down
134
330000
3000
pohranili
05:48
a huge amount of information and data,
135
333000
2000
ogromne količine informacija i podataka,
05:50
and we irrigate it with networks and connectivity,
136
335000
2000
i negovali smo ih stvaranjem mreža i povezivanjem,
05:52
and it's been worked and tilled by unpaid workers and governments.
137
337000
3000
a o njima su se starali i sa njima su radili volonteri i vlade.
05:55
And, all right, I'm kind of milking the metaphor a little bit.
138
340000
3000
I, slažem se, možda malo preterujem,
05:58
But it's a really fertile medium,
139
343000
3000
Ali to je zaista veoma plodan medijum,
06:01
and it feels like visualizations, infographics, data visualizations,
140
346000
3000
i čini se da vizualizacije, grafički prikazi, prikazi podataka
06:04
they feel like flowers blooming from this medium.
141
349000
3000
naprosto cvetaju u tom medijumu.
06:07
But if you look at it directly,
142
352000
2000
Ali ako pogledamo neposredno,
06:09
it's just a lot of numbers and disconnected facts.
143
354000
2000
to je samo masa nepovezanih podataka.
06:11
But if you start working with it and playing with it in a certain way,
144
356000
3000
Ali ako krenete da se sa njima igrate na određeni način,
06:14
interesting things can appear and different patterns can be revealed.
145
359000
3000
mogu da se pojave zanimljive stvari i mogu da se otkriju različite sheme.
06:17
Let me show you this.
146
362000
2000
Pokazaću vam.
06:19
Can you guess what this data set is?
147
364000
3000
Šta mislite šta predstavljaju ovi podaci?
06:22
What rises twice a year,
148
367000
2000
Šta je to čije vrednosti skaču dva puta godišnje,
06:24
once in Easter
149
369000
2000
jednom na Uskrs
06:26
and then two weeks before Christmas,
150
371000
2000
a onda dve nedelje pred Božić,
06:28
has a mini peak every Monday,
151
373000
2000
pokazuje mali skok svakog ponedeljka
06:30
and then flattens out over the summer?
152
375000
2000
a onda potpuno padne preko leta.
06:32
I'll take answers.
153
377000
2000
Slušam odgovore.
06:34
(Audience: Chocolate.) David McCandless: Chocolate.
154
379000
2000
(Publika: Čokolada.) Dejvid Mekkendls: Čokolada.
06:36
You might want to get some chocolate in.
155
381000
3000
Možete i čokoladu dodati.
06:39
Any other guesses?
156
384000
2000
Još neko?
06:41
(Audience: Shopping.) DM: Shopping.
157
386000
2000
(Publika: Kupovina.) DM: Kupovina.
06:43
Yeah, retail therapy might help.
158
388000
3000
Jeste, terapija u maloprodaji možda pomogne.
06:46
(Audience: Sick leave.)
159
391000
2000
(Publika: Bolovanje.)
06:48
DM: Sick leave. Yeah, you'll definitely want to take some time off.
160
393000
2000
DM: Bolovanje. Jeste, sasvim ćete sigurno poželeti slobodne dane.
06:50
Shall we see?
161
395000
2000
Da pogledamo?
06:53
(Laughter)
162
398000
8000
(Smeh)
07:01
(Applause)
163
406000
3000
(Aplauz)
07:04
So, the information guru Lee Byron and myself,
164
409000
3000
Informacije koje vidite ovde, sakupili smo Li Bajron i ja
07:07
we scraped 10,000 status Facebook updates
165
412000
3000
iz 10000 ažuriranja statusa na Fejsbuku
07:10
for the phrase "break-up" and "broken-up"
166
415000
2000
tražili smo frazu "raskid" ili "raskinuli"
07:12
and this is the pattern we found --
167
417000
2000
i ovo je shema do koje smo došli -
07:14
people clearing out for Spring Break,
168
419000
2000
ljudi prave veliko spremanje pred prolećni raspust,
07:16
(Laughter)
169
421000
5000
(Smeh)
07:21
coming out of very bad weekends on a Monday,
170
426000
2000
izlaze iz groznih vikenda ponedeljkom,
07:23
being single over the summer,
171
428000
3000
preko leta nisu u vezi.
07:26
and then the lowest day of the year, of course: Christmas Day.
172
431000
3000
A onda, tu je najniža vrednost u toku godine koju beležimo na Božić.
07:29
Who would do that?
173
434000
3000
Ko bi to uradio?
07:32
So there's a titanic amount of data out there now,
174
437000
2000
Postoji nezamislivo velika količina podataka, kao
07:34
unprecedented.
175
439000
2000
nikada ranije.
07:37
But if you ask the right kind of question,
176
442000
2000
Ali ako postavite pravo pitanje,
07:39
or you work it in the right kind of way,
177
444000
2000
ili ako podatke obradite na pravi način,
07:41
interesting things can emerge.
178
446000
3000
dolazite do veoma zanimljivih stvari.
07:44
So information is beautiful. Data is beautiful.
179
449000
3000
U informacijama nalazimo lepotu. Podaci kriju lepotu.
07:47
I wonder if I could make my life beautiful.
180
452000
3000
Pitam se da li bih mogao da i sebi slične prikažem lepima.
07:50
And here's my visual C.V.
181
455000
2000
Evo moje vizualizovane biografije.
07:52
I'm not quite sure I've succeeded.
182
457000
2000
Nisam siguran da sam u tome uspeo.
07:54
Pretty blocky, the colors aren't that great.
183
459000
2000
Prilično je nezgrapno. Ni boje nisu baš nešto.
07:56
But I wanted to convey something to you.
184
461000
3000
Ali hteo sam nešto da vam ispričam.
07:59
I started as a programmer,
185
464000
2000
Počeo sam kao programer,
08:01
and then I worked as a writer for many years, about 20 years,
186
466000
2000
a onda sam niz godina radio kao pisac, skoro 20 godina,
08:03
in print, online and then in advertising,
187
468000
2000
prvo u štampanom medijumu, onlajn a onda i u reklamnoj industriji,
08:05
and only recently have I started designing.
188
470000
3000
i tek sam nedavno počeo da radim dizajn.
08:08
And I've never been to design school.
189
473000
2000
A nikada nisam išao u školu za dizajn.
08:10
I've never studied art or anything.
190
475000
3000
Niti sam studirao umetnost.
08:13
I just kind of learned through doing.
191
478000
2000
Jednostavno sam učio kroz rad.
08:15
And when I started designing,
192
480000
2000
I kada sam počeo da radim dizajn,
08:17
I discovered an odd thing about myself.
193
482000
2000
otkrio sam neke neobične stvari o sebi.
08:19
I already knew how to design,
194
484000
2000
Već sam znao kako se to radi,
08:21
but it wasn't like I was amazingly brilliant at it,
195
486000
3000
mada ne mogu reći da sam postigao neke izvanredne rezultate
08:24
but more like I was sensitive
196
489000
2000
pre bih rekao da sam imao osećaj
08:26
to the ideas of grids and space
197
491000
2000
za prostornost i za modularno predstavljanje prostora
08:28
and alignment and typography.
198
493000
2000
za tipografiju i za poravnavanje sloga strane.
08:30
It's almost like being exposed
199
495000
2000
Kao da je izloženost tom
08:32
to all this media over the years
200
497000
2000
medijumu toliko mnogo godina
08:34
had instilled a kind of dormant design literacy in me.
201
499000
3000
u meni probudilo neku pismenost za dizajn koje nisam bio svestan.
08:37
And I don't feel like I'm unique.
202
502000
2000
Ne mislim da sam jedinstveni slučaj.
08:39
I feel that everyday, all of us now
203
504000
2000
Osećam da smo svakoga dana, svi mi
08:41
are being blasted by information design.
204
506000
3000
zatrpani dizajnom informacija.
08:44
It's being poured into our eyes through the Web,
205
509000
2000
Izliva se u naše oči kroz Mrežu,
08:46
and we're all visualizers now;
206
511000
2000
i svi se oslanjamo na vizualizaciju;
08:48
we're all demanding a visual aspect
207
513000
2000
svi zahtevamo da informacije
08:50
to our information.
208
515000
3000
sadrže vizuelnu komponentu.
08:53
There's something almost quite magical about visual information.
209
518000
3000
A u vizuelnoj informaciji ima nečeg čarobnog.
08:56
It's effortless, it literally pours in.
210
521000
3000
Dešava se bez napora; bukvalno se izliva.
08:59
And if you're navigating a dense information jungle,
211
524000
3000
Ako se krećete kroz teško prohodnu džunglu informacija,
09:02
coming across a beautiful graphic
212
527000
2000
kad naiđete na neke izvanredne crteže
09:04
or a lovely data visualization,
213
529000
2000
ili na očaravajuće vizualizacije podataka,
09:06
it's a relief, it's like coming across a clearing in the jungle.
214
531000
3000
to predstavlja olakšanje, kao da ste na tom neprohodnom terenu naišli na čistinu.
09:09
I was curious about this, so it led me
215
534000
2000
Mene je radoznalost povela ka
09:11
to the work of a Danish physicist
216
536000
2000
radovima danskog fizičara
09:13
called Tor Norretranders,
217
538000
2000
po imenu Tor Noretranders,
09:15
and he converted the bandwidth of the senses into computer terms.
218
540000
3000
koji je preveo opseg čula u računarsku terminologiju.
09:19
So here we go. This is your senses,
219
544000
2000
Evo ga. Ovo su vaša čula,
09:21
pouring into your senses every second.
220
546000
2000
i ono što primate čulima svake sekunde.
09:23
Your sense of sight is the fastest.
221
548000
3000
Čulo vida je najbrže.
09:26
It has the same bandwidth as a computer network.
222
551000
3000
Ima istu brzinu kao i računarska mreža.
09:29
Then you have touch, which is about the speed of a USB key.
223
554000
3000
Onda je tu dodir, čija je brzina slična brzini USB priključka.
09:32
And then you have hearing and smell,
224
557000
2000
Potom dolaze sluh i njuh,
09:34
which has the throughput of a hard disk.
225
559000
2000
čija je brzina ekvivalentna brzini hard-diska.
09:36
And then you have poor old taste,
226
561000
2000
I na kraju imate bedno čulo ukusa,
09:38
which is like barely the throughput of a pocket calculator.
227
563000
3000
koje jedva da može da parira brzini digitrona.
09:41
And that little square in the corner, a naught .7 percent,
228
566000
3000
A ovaj malecki kvadratić, 0,7 posto,
09:44
that's the amount we're actually aware of.
229
569000
3000
to je količina podataka kojih smo zapravo svesni.
09:47
So a lot of your vision --
230
572000
2000
Tako da veliki deo vizuelnog -
09:49
the bulk of it is visual, and it's pouring in.
231
574000
2000
najveći deo ovih informacija je vizuelnog tipa, i jednostavno se uliva.
09:51
It's unconscious.
232
576000
2000
Toga nismo ni svesni.
09:53
The eye is exquisitely sensitive
233
578000
3000
Dok je oko izuzetno osetljivo
09:56
to patterns in variations in color, shape and pattern.
234
581000
3000
na varijacije u boji, obliku i uzorku.
09:59
It loves them, and it calls them beautiful.
235
584000
2000
Dopadaju mu se i smatra ih lepim.
10:01
It's the language of the eye.
236
586000
2000
To je jezik oka.
10:03
If you combine the language of the eye with the language of the mind,
237
588000
2000
A ako kombinujete jezik oka i jezik uma,
10:05
which is about words and numbers and concepts,
238
590000
3000
koji se sastoji od reči, brojeva i pojmova,
10:08
you start speaking two languages simultaneously,
239
593000
3000
govorite dva jezika istovremeno,
10:11
each enhancing the other.
240
596000
3000
i oni jedan drugog upotpunjuju.
10:14
So, you have the eye, and then you drop in the concepts.
241
599000
3000
Imate oko, i sada dodajete pojmove.
10:17
And that whole thing -- it's two languages
242
602000
2000
I sve skupa - ta dva jezika
10:19
both working at the same time.
243
604000
2000
deluje istovremeno.
10:21
So we can use this new kind of language, if you like,
244
606000
2000
Ovaj novi jezik možemo koristiti, na primer,
10:23
to alter our perspective or change our views.
245
608000
3000
da promenimo ugao gledanja ili svoja stanovišta.
10:26
Let me ask you a simple question
246
611000
2000
Postaviću vam jednostavno pitanje
10:28
with a really simple answer:
247
613000
2000
na koje je jednostavno odgovoriti.
10:30
Who has the biggest military budget?
248
615000
2000
Ko ima najveći vojni budžet?
10:32
It's got to be America, right?
249
617000
2000
Mora biti da je Amerika?
10:34
Massive. 609 billion in 2008 --
250
619000
2000
Ogroman je. 609 milijardi 2008 -
10:36
607, rather.
251
621000
2000
zapravo 607.
10:38
So massive, in fact, that it can contain
252
623000
2000
Toliko je veliki da zapravo sadrži
10:40
all the other military budgets in the world inside itself.
253
625000
3000
vojne budžete svih drugih zemalja na svetu.
10:43
Gobble, gobble, gobble, gobble, gobble.
254
628000
2000
Žder, žder, žder...
10:45
Now, you can see Africa's total debt there
255
630000
2000
Ovde vidite ukupni dug Afrike
10:47
and the U.K. budget deficit for reference.
256
632000
2000
i budžetski deficit Velike Britanije radi poređenja.
10:49
So that might well chime
257
634000
2000
U tom smislu može se reći
10:51
with your view that America
258
636000
2000
da Amerika
10:53
is a sort of warmongering military machine,
259
638000
3000
u određenom smislu investira u ratovanje, u vojnu mašineriju,
10:56
out to overpower the world
260
641000
2000
s namerom da nadvlada sve na svetu
10:58
with its huge industrial-military complex.
261
643000
3000
svojim ogromnim vojno-industrijskim kompleksom.
11:01
But is it true that America has the biggest military budget?
262
646000
3000
Ali da li je zaista tako, da li Amerika ima najveći vojni budžet?
11:04
Because America is an incredibly rich country.
263
649000
2000
To je nezamislivo bogata zemlja.
11:06
In fact, it's so massively rich
264
651000
2000
Toliko je ogromno njeno bogatstvo
11:08
that it can contain the four other
265
653000
2000
da sadrži čak četiri ekonomije
11:10
top industrialized nations' economies
266
655000
2000
vodećih industrijskih nacija
11:12
inside itself, it's so vastly rich.
267
657000
3000
toliko je nezamislivo bogata.
11:15
So its military budget is bound to be enormous.
268
660000
3000
Srazmerno tome, i vojni budžet mora biti ogroman.
11:18
So, to be fair and to alter our perspective,
269
663000
2000
Da bismo bili pošteni, i da bismo sve sagledali i iz druge perspektive,
11:20
we have to bring in another data set,
270
665000
2000
moramo da uvedeo još jedan set podataka,
11:22
and that data set is GDP, or the country's earnings.
271
667000
2000
a to je bruto nacionalni dohodak, ili ono što zemlja zarađuje.
11:24
Who has the biggest budget as a proportion of GDP?
272
669000
2000
Čiji je budžet najveći u odnosu na BND?
11:26
Let's have a look.
273
671000
2000
Da pogledamo.
11:28
That changes the picture considerably.
274
673000
3000
Slika se značajno izmenila.
11:31
Other countries pop into view that you, perhaps, weren't considering,
275
676000
3000
I druge zemlje, koje nismo uzimali u razmatranje dolaze u prvi plan.
11:34
and American drops into eighth.
276
679000
2000
a Amerikanci padaju na osmo mesto.
11:36
Now you can also do this with soldiers.
277
681000
2000
Isto to možemo uraditi sa brojem vojnika.
11:38
Who has the most soldiers? It's got to be China.
278
683000
2000
Ko ima najviše vojnika? Mora biti da je to Kina.
11:40
Of course, 2.1 million.
279
685000
2000
Naravno, 2,1 milion.
11:42
Again, chiming with your view
280
687000
2000
I opet, u skladu sa pretpostavkom
11:44
that China has a militarized regime
281
689000
2000
da je Kina zemlja vojnog režima
11:46
ready to, you know, mobilize its enormous forces.
282
691000
2000
spreman da u svakom trenutku mobilizira svoje snage.
11:48
But of course, China has an enormous population.
283
693000
3000
Ali ne zaboravimo da Kina ima ogroman broj stanovnika.
11:51
So if we do the same,
284
696000
2000
Ako opet uradimo poređenje,
11:53
we see a radically different picture.
285
698000
2000
vidimo da se slika iz korena menja.
11:55
China drops to 124th.
286
700000
2000
Kina pada na 124. mesto.
11:57
It actually has a tiny army
287
702000
2000
Zapravo ima minijaturnu vojsku
11:59
when you take other data into consideration.
288
704000
3000
kada se i drugi podaci uzmu u obzir.
12:02
So, absolute figures, like the military budget,
289
707000
2000
Apsolutne vrednosti, kao vojni budžet,
12:04
in a connected world,
290
709000
2000
u umreženom svetu,
12:06
don't give you the whole picture.
291
711000
2000
ne pružaju uvid u celu sliku.
12:08
They're not as true as they could be.
292
713000
2000
Nisu istinite u onoj meri u kojoj se to očekuje.
12:10
We need relative figures that are connected to other data
293
715000
3000
Potrebno nam je upoređivanje sa drugim podacima
12:13
so that we can see a fuller picture,
294
718000
2000
da sagledamo celu sliku,
12:15
and then that can lead to us changing our perspective.
295
720000
2000
i da tako promenimo ugao gledanja.
12:17
As Hans Rosling, the master,
296
722000
2000
Kao što kaže Hans Rosling, vrhunski stručnjak,
12:19
my master, said,
297
724000
3000
moj mentor,
12:22
"Let the dataset change your mindset."
298
727000
3000
"Dozvolite da pogled na podatke promeni vaš pogled na svet."
12:26
And if it can do that, maybe it can also change your behavior.
299
731000
3000
I ako se to dogodi, možda će se promeniti i vaše ponašanje.
12:29
Take a look at this one.
300
734000
2000
Pogledajte ovo.
12:31
I'm a bit of a health nut.
301
736000
2000
Ja sam pomalo zaluđenik zdravim životom.
12:33
I love taking supplements and being fit,
302
738000
3000
Obožavam dodatke prehrani i volim da sam u dobroj kondiciji,
12:36
but I can never understand what's going on in terms of evidence.
303
741000
3000
ali mi nikad nije bilo jasno šta se tu dešava što se može dokazati.
12:39
There's always conflicting evidence.
304
744000
2000
Dokazi su uvek kontradiktorni.
12:41
Should I take vitamin C? Should I be taking wheatgrass?
305
746000
2000
Treba li da uzimam vitamin C? Da li da jedem pšenične klice?
12:43
This is a visualization of all the evidence
306
748000
2000
Ovo je vizualizacija svih dokaza
12:45
for nutritional supplements.
307
750000
2000
koji su u vezi sa dodacima prehrani.
12:47
This kind of diagram is called a balloon race.
308
752000
3000
Ovaj dijagram se zove "nadmetanje balona".
12:50
So the higher up the image,
309
755000
2000
Što je slika na višem položaju,
12:52
the more evidence there is for each supplement.
310
757000
3000
ima više dokaza da taj dodatak deluje.
12:55
And the bubbles correspond to popularity as regards to Google hits.
311
760000
3000
A mehurići predstavljaju popularnost u odnosu na Guglove rezultate pretraživanja.
12:58
So you can immediately apprehend
312
763000
3000
Odmah se vidi odnos
13:01
the relationship between efficacy and popularity,
313
766000
3000
efikasnosti i popularnosti
13:04
but you can also, if you grade the evidence,
314
769000
3000
ali isto tako, dokaze možemo da gradiramo,
13:07
do a "worth it" line.
315
772000
2000
u niz po tome kakav im je učinak.
13:09
So supplements above this line are worth investigating,
316
774000
3000
tako iznad ove crte imamo one koje ima smisla istraživati,
13:12
but only for the conditions listed below,
317
777000
3000
ali samo u odnosu na uslove postavljene dole.
13:15
and then the supplements below the line
318
780000
3000
A onda dodaci koji su ispod crte
13:18
are perhaps not worth investigating.
319
783000
2000
pripadaju grupi koju možda nema smisla istraživati.
13:20
Now this image constitutes a huge amount of work.
320
785000
3000
Ovaj prikaz predstavlja ogroman napor u obradi podataka.
13:23
We scraped like 1,000 studies from PubMed,
321
788000
3000
Pregledali smo preko 1000 studija sa PubMed-a,
13:26
the biomedical database,
322
791000
2000
biomedicinske baze podataka,
13:28
and we compiled them and graded them all.
323
793000
3000
i sve smo ih sakupili i gradirali.
13:31
And it was incredibly frustrating for me
324
796000
2000
A za mene je to bilo neverovatno naporno
13:33
because I had a book of 250 visualizations to do for my book,
325
798000
3000
jer sam imao knjigu sa 250 vizualizacija koje je trebalo obraditi za knjigu,
13:36
and I spent a month doing this,
326
801000
2000
i proveo sam mesece u tom poslu,
13:38
and I only filled two pages.
327
803000
2000
a ispunio sam tek dve stranice.
13:40
But what it points to
328
805000
2000
Ali, to sve ukazuje
13:42
is that visualizing information like this
329
807000
2000
da je vizualizacija podataka
13:44
is a form of knowledge compression.
330
809000
2000
oblik njihove kompresije.
13:46
It's a way of squeezing an enormous amount
331
811000
2000
To je način da se ogromna količina
13:48
of information and understanding
332
813000
2000
informacija i tumačenja
13:50
into a small space.
333
815000
2000
sabije u veoma malo prostora.
13:52
And once you've curated that data, and once you've cleaned that data,
334
817000
2000
I kada se ti podaci pročiste i urede,
13:54
and once it's there,
335
819000
2000
i kada se prikažu na ovaj način,
13:56
you can do cool stuff like this.
336
821000
2000
sa njima se može raditi mnogo zanimljivih stvari.
13:58
So I converted this into an interactive app,
337
823000
2000
Ovo sam konvertovao u interaktivnu aplikaciju,
14:00
so I can now generate this application online --
338
825000
2000
i sada mogu da je pokrenem onlajn -
14:02
this is the visualization online --
339
827000
2000
ovo je vizualizacija onlajn -
14:04
and I can say, "Yeah, brilliant."
340
829000
2000
i mogu da kažem, "Jupi, izvanredno."
14:06
So it spawns itself.
341
831000
2000
Ona samu sebe generiše.
14:08
And then I can say, "Well, just show me the stuff
342
833000
2000
I sad mogu da kažem, "Pa, samo mi pokaži materijal
14:10
that affects heart health."
343
835000
2000
koji govori o uticaju na srce."
14:12
So let's filter that out.
344
837000
2000
Hajde da to izdvojimo.
14:14
So heart is filtered out, so I can see if I'm curious about that.
345
839000
3000
Srce smo izdvojili, i ako me to zanima.
14:17
I think, "No, no. I don't want to take any synthetics,
346
842000
2000
Pomisliću, "Ne, ne. Neću sintetičke proizvode.
14:19
I just want to see plants and --
347
844000
3000
Hoću da vidim samo biljke -
14:22
just show me herbs and plants. I've got all the natural ingredients."
348
847000
3000
prikaži mi samo bilje i trave. Trebaju mi samo prirodni sastojci."
14:25
Now this app is spawning itself
349
850000
2000
Evo, aplikacija samu sebe generiše
14:27
from the data.
350
852000
2000
iz podataka.
14:29
The data is all stored in a Google Doc,
351
854000
2000
Podaci su pohranjeni u Gugl dokumentima,
14:31
and it's literally generating itself from that data.
352
856000
3000
i bukvalno se ovo samo od sebe generiše iz tih podataka.
14:34
So the data is now alive; this is a living image,
353
859000
2000
Podaci su oživeli; ovo je živa slika,
14:36
and I can update it in a second.
354
861000
2000
i mogu da je ažuriram u trenu.
14:38
New evidence comes out. I just change a row on a spreadsheet.
355
863000
2000
Pojaviće se novi dokazi - i ja ću samo promeniti jedan red u tabeli.
14:40
Doosh! Again, the image recreates itself.
356
865000
4000
Pljus! Opet, slika se sama obnavlja.
14:44
So it's cool.
357
869000
2000
To je jako zgodno.
14:46
It's kind of living.
358
871000
3000
I predstavlja oblik života.
14:49
But it can go beyond data,
359
874000
2000
Ali može da dosegne i dalje od podataka,
14:51
and it can go beyond numbers.
360
876000
2000
i dalje od brojki.
14:53
I like to apply information visualization
361
878000
2000
I dopada mi se da primenjujem vizualizaciju informacija
14:55
to ideas and concepts.
362
880000
3000
na ideje i pojmove.
14:58
This is a visualization
363
883000
2000
Ovo je vizualizacija
15:00
of the political spectrum,
364
885000
2000
političkog spektra,
15:02
an attempt for me to try
365
887000
2000
u pokušaju da razumem
15:04
and understand how it works
366
889000
2000
kako to funkcioniše
15:06
and how the ideas percolate down
367
891000
2000
i kako ideje iz vlade
15:08
from government into society and culture,
368
893000
2000
dolaze u društvo i u kulturu,
15:10
into families, into individuals, into their beliefs
369
895000
3000
u porodice, u glave pojedinaca, u njihova uverenja
15:13
and back around again in a cycle.
370
898000
3000
i odatle se vraćaju u krug.
15:16
What I love about this image
371
901000
2000
U ovoj slici posebno smatram vrednim
15:18
is it's made up of concepts,
372
903000
2000
to što je sačinjena od pojmova,
15:20
it explores our worldviews
373
905000
2000
i istražuje naše poglede na svet
15:22
and it helps us -- it helps me anyway --
374
907000
2000
i pomaže nam - barem meni pomaže -
15:24
to see what others think,
375
909000
2000
da sagledam šta drugi misle,
15:26
to see where they're coming from.
376
911000
2000
da shvatim njihova stanovišta,
15:28
And it feels just incredibly cool to do that.
377
913000
3000
a to je odličan osećaj.
15:31
What was most exciting for me
378
916000
3000
Najuzbudljivije u postupku
15:34
designing this
379
919000
2000
stvaranja ove slike
15:36
was that, when I was designing this image,
380
921000
2000
za mene je bilo
15:38
I desperately wanted this side, the left side,
381
923000
3000
to što sam očajnički sebe želeo da stavim na ovu stranu, na levu stranu,
15:41
to be better than the right side --
382
926000
2000
i hteo sam da ona bude bolja od desne strane -
15:43
being a journalist, a Left-leaning person --
383
928000
3000
jer sam takav novinar - leve orijentacije -
15:46
but I couldn't, because I would have created
384
931000
2000
ali nisam mogao to da izvedem, jer bih kreirao
15:48
a lopsided, biased diagram.
385
933000
3000
pristrasan dijagram.
15:51
So, in order to really create a full image,
386
936000
3000
Tako da bih kreirao pravu sliku,
15:54
I had to honor the perspectives on the right-hand side
387
939000
3000
Morao sam da poštujem i perspektivu desne strane
15:57
and at the same time, uncomfortably recognize
388
942000
3000
a istovremeno, morao sam da s nelagodom priznam
16:00
how many of those qualities were actually in me,
389
945000
3000
da mnoge osobine i sam posedujem,
16:03
which was very, very annoying and uncomfortable.
390
948000
2000
što može biti veoma neprijatno.
16:05
(Laughter)
391
950000
4000
(Smeh)
16:09
But not too uncomfortable,
392
954000
2000
No, nije previše neprijatno,
16:11
because there's something unthreatening
393
956000
3000
jer svakako nas manje ugrožava
16:14
about seeing a political perspective,
394
959000
2000
posmatranje političke opcije,
16:16
versus being told or forced to listen to one.
395
961000
3000
nego situacija u kojoj nam se to sve saopštava usmeno
16:19
You're capable of holding conflicting viewpoints
396
964000
3000
Ovako, zapravo, možemo da sagledamo sukobljene perspektive
16:22
joyously when you can see them.
397
967000
2000
sa radošću, u situaciji u kojoj ih gledate.
16:24
It's even fun to engage with them
398
969000
2000
Čak može biti i veoma zanimljivo proučavati ih
16:26
because it's visual.
399
971000
2000
jer su predstavljene vizuelno.
16:28
So that's what's exciting to me,
400
973000
2000
Smatram da je to veoma uzbudljivo,
16:30
seeing how data can change my perspective
401
975000
2000
posmatrati kako podaci menjaju moju perspektvu
16:32
and change my mind midstream --
402
977000
2000
i menjati svoje mišljenje u tom procesu -
16:34
beautiful, lovely data.
403
979000
3000
izvanredni, divni podaci.
16:38
So, just to wrap up,
404
983000
2000
I za kraj,
16:40
I wanted to say
405
985000
2000
hteo sam da kažem
16:42
that it feels to me that design is about solving problems
406
987000
2000
da mi se čini da se i dizajn bavi rešavanjem problema
16:44
and providing elegant solutions,
407
989000
3000
i pronalaženjem elegantnih rešenja.
16:47
and information design is about
408
992000
2000
A dizajn informacija
16:49
solving information problems.
409
994000
2000
bavi se rešavanjem problema informacija.
16:51
It feels like we have a lot of information problems
410
996000
2000
A čini se da imamo mnogo problema sa informacijama
16:53
in our society at the moment,
411
998000
2000
u našem društvu,
16:55
from the overload and the saturation
412
1000000
2000
koji je posledica preopterećenosti i zasićenja
16:57
to the breakdown of trust and reliability
413
1002000
2000
ili gubitka poverenja i pouzdanosti
16:59
and runaway skepticism and lack of transparency,
414
1004000
2000
i porasta skepticizma i nedostatka transparetnosti,
17:01
or even just interestingness.
415
1006000
2000
ili čak zainteresovanosti.
17:03
I mean, I find information just too interesting.
416
1008000
2000
Hoću da kažem, za mene su informacije isuviše zanimljive.
17:05
It has a magnetic quality that draws me in.
417
1010000
3000
Poseduju prvilačnost kojoj lako podležem.
17:09
So, visualizing information
418
1014000
2000
Vizualizacija informacija
17:11
can give us a very quick solution to those kinds of problems.
419
1016000
3000
nam daje veoma brzo rešenje ovakvih problema.
17:14
Even when the information is terrible,
420
1019000
2000
A i onda kada su informacije užasne,
17:16
the visual can be quite beautiful.
421
1021000
3000
njihova vizuelna komponenta može biti veoma lepa.
17:19
Often we can get clarity
422
1024000
3000
I često nešto možemo razjasniti
17:22
or the answer to a simple question very quickly,
423
1027000
2000
nešto ili pronaći odgovore na pitanja veoma brzo,
17:24
like this one,
424
1029000
2000
kao što je ovo,
17:26
the recent Icelandic volcano.
425
1031000
3000
nedavna erupcija vulkana na Islandu.
17:29
Which was emitting the most CO2?
426
1034000
2000
Šta ispušta najviše ugljen dioksida?
17:31
Was it the planes or the volcano,
427
1036000
2000
Da li su to avioni ili vulkan,
17:33
the grounded planes or the volcano?
428
1038000
2000
prizemljeni avioni ili vulkani?
17:35
So we can have a look.
429
1040000
2000
Pogledaćemo.
17:37
We look at the data and we see:
430
1042000
2000
Gledamo podatke i vidimo
17:39
Yep, the volcano emitted 150,000 tons;
431
1044000
2000
jeste, vulkan je ispustio 150000 tona;
17:41
the grounded planes would have emitted
432
1046000
2000
prizemljeni avioni bi ispustili
17:43
345,000 if they were in the sky.
433
1048000
3000
345000 da su bili u vazduhu.
17:46
So essentially, we had our first carbon-neutral volcano.
434
1051000
3000
Pa tako, zapravo, ovo je prvi vulkan sa neutralnom emisijom ugljenika.
17:49
(Laughter)
435
1054000
2000
(Smeh)
17:51
(Applause)
436
1056000
9000
(Aplauz)
18:00
And that is beautiful. Thank you.
437
1065000
3000
I to je ono što je lepo. Hvala vam.
18:03
(Applause)
438
1068000
8000
(Aplauz)
ABOUT THE SPEAKER
David McCandless - Data journalistDavid McCandless draws beautiful conclusions from complex datasets -- thus revealing unexpected insights into our world.
Why you should listen
David McCandless makes infographics -- simple, elegant ways to see information that might be too complex or too big, small, abstract or scattered to otherwise be grasped. In his new book, Information Is Beautiful (in the US, it's being called The Visual Miscellaneum), McCandless and his cadre of info designers take a spin through the world of visualized data, from hard stats on politics and climate to daffy but no less important trends in pop music.
McCandless' genius is not so much in finding jazzy new ways to show data -- the actual graphics aren't the real innovation here -- as in finding fresh ways to combine datasets to let them ping and prod each other. Reporting the number of drug deaths in the UK every year is interesting; but mapping that data onto the number of drug deaths reported by the UK press, broken down by drug, is utterly fascinating (more deaths by marijuana were reported than in fact occurred, by a factor of 484%). McCandless contributes a monthly big-think graphic to the Guardian's Data Blog, and makes viral graphics for his blog Information Is Beautiful.
David McCandless | Speaker | TED.com