TED2015
Manuel Lima: A visual history of human knowledge
Filmed:
Readability: 5.4
1,916,809 views
How does knowledge grow? Sometimes it begins with one insight and grows into many branches; other times it grows as a complex and interconnected network. Infographics expert Manuel Lima explores the thousand-year history of mapping data -- from languages to dynasties -- using trees and networks of information. It's a fascinating history of visualizations, and a look into humanity's urge to map what we know.
Manuel Lima - Data visualization researcher
Manuel Lima studies how information can be organized -- into elegant and beautiful diagrams that illustrate the many unexpected twists of big data. Full bio
Manuel Lima studies how information can be organized -- into elegant and beautiful diagrams that illustrate the many unexpected twists of big data. Full bio
Double-click the English transcript below to play the video.
00:13
Over the past 10 years,
0
1126
1295
00:14
I've been researching the way
people organize and visualize information.
people organize and visualize information.
1
2445
4569
00:19
And I've noticed an interesting shift.
2
7786
2039
00:22
For a long period of time,
3
10166
1720
00:23
we believed in a natural ranking order
in the world around us,
in the world around us,
4
11910
4428
00:28
also known as the great chain of being,
or "Scala naturae" in Latin,
or "Scala naturae" in Latin,
5
16362
4745
00:33
a top-down structure that normally starts
with God at the very top,
with God at the very top,
6
21131
4175
00:37
followed by angels, noblemen,
7
25330
2405
00:39
common people, animals, and so on.
8
27759
3013
00:43
This idea was actually based
on Aristotle's ontology,
on Aristotle's ontology,
9
31999
4275
00:48
which classified all things known to man
in a set of opposing categories,
in a set of opposing categories,
10
36298
4444
00:52
like the ones you see behind me.
11
40766
1722
00:56
But over time, interestingly enough,
12
44687
2747
00:59
this concept adopted
the branching schema of a tree
the branching schema of a tree
13
47458
4146
01:03
in what became known
as the Porphyrian tree,
as the Porphyrian tree,
14
51628
2873
01:06
also considered to be
the oldest tree of knowledge.
the oldest tree of knowledge.
15
54525
3642
01:11
The branching scheme
of the tree was, in fact,
of the tree was, in fact,
16
59238
2174
01:13
such a powerful metaphor
for conveying information
for conveying information
17
61436
2949
01:16
that it became, over time,
an important communication tool
an important communication tool
18
64409
3270
01:19
to map a variety of systems of knowledge.
19
67703
2274
01:22
We can see trees being used
to map morality,
to map morality,
20
70648
3083
01:25
with the popular tree of virtues
and tree of vices,
and tree of vices,
21
73755
2849
01:28
as you can see here, with these beautiful
illustrations from medieval Europe.
illustrations from medieval Europe.
22
76628
3792
01:32
We can see trees being used
to map consanguinity,
to map consanguinity,
23
80825
3088
01:35
the various blood ties between people.
24
83937
2244
01:39
We can also see trees being used
to map genealogy,
to map genealogy,
25
87110
3096
01:42
perhaps the most famous archetype
of the tree diagram.
of the tree diagram.
26
90230
2810
01:45
I think many of you in the audience
have probably seen family trees.
have probably seen family trees.
27
93064
3316
01:48
Many of you probably even have
your own family trees drawn in such a way.
your own family trees drawn in such a way.
28
96404
3705
01:53
We can see trees even mapping
systems of law,
systems of law,
29
101158
2911
01:56
the various decrees and rulings
of kings and rulers.
of kings and rulers.
30
104093
3851
02:01
And finally, of course,
also a very popular scientific metaphor,
also a very popular scientific metaphor,
31
109785
3758
02:05
we can see trees being used
to map all species known to man.
to map all species known to man.
32
113567
3560
02:11
And trees ultimately became
such a powerful visual metaphor
such a powerful visual metaphor
33
119177
3906
02:15
because in many ways,
they really embody this human desire
they really embody this human desire
34
123107
2868
02:17
for order, for balance,
for unity, for symmetry.
for unity, for symmetry.
35
125999
3036
02:21
However, nowadays we are really facing
new complex, intricate challenges
new complex, intricate challenges
36
129999
4323
02:26
that cannot be understood by simply
employing a simple tree diagram.
employing a simple tree diagram.
37
134346
4190
02:32
And a new metaphor is currently emerging,
38
140037
3242
02:35
and it's currently replacing the tree
39
143303
2150
02:37
in visualizing various
systems of knowledge.
systems of knowledge.
40
145477
2563
02:40
It's really providing us with a new lens
to understand the world around us.
to understand the world around us.
41
148064
4252
02:45
And this new metaphor
is the metaphor of the network.
is the metaphor of the network.
42
153495
3199
02:49
And we can see this shift
from trees into networks
from trees into networks
43
157511
3311
02:52
in many domains of knowledge.
44
160846
1640
02:54
We can see this shift in the way
we try to understand the brain.
we try to understand the brain.
45
162510
4189
03:00
While before, we used
to think of the brain
to think of the brain
46
168453
2038
03:02
as a modular, centralized organ,
47
170515
1991
03:04
where a given area was responsible
for a set of actions and behaviors,
for a set of actions and behaviors,
48
172530
4038
03:08
the more we know about the brain,
49
176592
1739
03:10
the more we think of it
as a large music symphony,
as a large music symphony,
50
178355
3286
03:13
played by hundreds
and thousands of instruments.
and thousands of instruments.
51
181665
2610
03:16
This is a beautiful snapshot
created by the Blue Brain Project,
created by the Blue Brain Project,
52
184299
3676
03:19
where you can see 10,000 neurons
and 30 million connections.
and 30 million connections.
53
187999
4063
03:24
And this is only mapping 10 percent
of a mammalian neocortex.
of a mammalian neocortex.
54
192736
3888
03:30
We can also see this shift in the way
we try to conceive of human knowledge.
we try to conceive of human knowledge.
55
198815
4160
03:36
These are some remarkable trees
of knowledge, or trees of science,
of knowledge, or trees of science,
56
204062
3148
03:39
by Spanish scholar Ramon Llull.
57
207234
2221
03:41
And Llull was actually the precursor,
58
209999
1810
03:43
the very first one who created
the metaphor of science as a tree,
the metaphor of science as a tree,
59
211833
3714
03:47
a metaphor we use
every single day, when we say,
every single day, when we say,
60
215571
2968
03:50
"Biology is a branch of science,"
61
218563
1665
03:52
when we say,
62
220252
1153
03:53
"Genetics is a branch of science."
63
221429
1933
03:56
But perhaps the most beautiful of all
trees of knowledge, at least for me,
trees of knowledge, at least for me,
64
224283
3595
03:59
was created for the French encyclopedia
by Diderot and d'Alembert in 1751.
by Diderot and d'Alembert in 1751.
65
227902
4452
04:04
This was really the bastion
of the French Enlightenment,
of the French Enlightenment,
66
232378
2635
04:07
and this gorgeous illustration
was featured as a table of contents
was featured as a table of contents
67
235037
3825
04:10
for the encyclopedia.
68
238886
1571
04:12
And it actually maps out
all domains of knowledge
all domains of knowledge
69
240481
4187
04:16
as separate branches of a tree.
70
244692
2118
04:19
But knowledge is much more
intricate than this.
intricate than this.
71
247866
2333
04:22
These are two maps of Wikipedia
showing the inter-linkage of articles --
showing the inter-linkage of articles --
72
250794
4640
04:27
related to history on the left,
and mathematics on the right.
and mathematics on the right.
73
255458
3890
04:31
And I think by looking at these maps
74
259966
1739
04:33
and other ones that have been
created of Wikipedia --
created of Wikipedia --
75
261729
2544
04:36
arguably one of the largest rhizomatic
structures ever created by man --
structures ever created by man --
76
264297
3392
04:39
we can really understand
how human knowledge is much more intricate
how human knowledge is much more intricate
77
267713
3822
04:43
and interdependent, just like a network.
78
271559
2436
04:47
We can also see this interesting shift
79
275455
2163
04:49
in the way we map
social ties between people.
social ties between people.
80
277642
2700
04:53
This is the typical organization chart.
81
281524
2295
04:55
I'm assuming many of you have seen
a similar chart as well,
a similar chart as well,
82
283843
2794
04:58
in your own corporations, or others.
83
286661
1746
05:00
It's a top-down structure
84
288431
1485
05:01
that normally starts
with the CEO at the very top,
with the CEO at the very top,
85
289940
2861
05:04
and where you can drill down all the way
to the individual workmen on the bottom.
to the individual workmen on the bottom.
86
292825
3960
05:09
But humans sometimes are, well, actually,
all humans are unique in their own way,
all humans are unique in their own way,
87
297634
4848
05:14
and sometimes you really don't play well
under this really rigid structure.
under this really rigid structure.
88
302506
4698
05:20
I think the Internet is really changing
this paradigm quite a lot.
this paradigm quite a lot.
89
308711
3110
05:23
This is a fantastic map
of online social collaboration
of online social collaboration
90
311845
3365
05:27
between Perl developers.
91
315234
1629
05:28
Perl is a famous programming language,
92
316887
2088
05:30
and here, you can see
how different programmers
how different programmers
93
318999
2723
05:33
are actually exchanging files,
and working together on a given project.
and working together on a given project.
94
321746
3827
05:37
And here, you can notice that this is
a completely decentralized process --
a completely decentralized process --
95
325597
4178
05:41
there's no leader in this organization,
96
329799
2156
05:43
it's a network.
97
331979
1157
05:46
We can also see this interesting shift
when we look at terrorism.
when we look at terrorism.
98
334337
4705
05:51
One of the main challenges
of understanding terrorism nowadays
of understanding terrorism nowadays
99
339613
3104
05:54
is that we are dealing with
decentralized, independent cells,
decentralized, independent cells,
100
342741
3730
05:58
where there's no leader
leading the whole process.
leading the whole process.
101
346495
2822
06:02
And here, you can actually see
how visualization is being used.
how visualization is being used.
102
350518
3298
06:05
The diagram that you see behind me
103
353840
1657
06:07
shows all the terrorists involved
in the Madrid attack in 2004.
in the Madrid attack in 2004.
104
355521
3818
06:11
And what they did here is,
they actually segmented the network
they actually segmented the network
105
359942
2927
06:14
into three different years,
106
362893
1499
06:16
represented by the vertical layers
that you see behind me.
that you see behind me.
107
364416
3042
06:19
And the blue lines tie together
108
367482
1969
06:21
the people that were present
in that network year after year.
in that network year after year.
109
369475
3618
06:25
So even though there's no leader per se,
110
373117
2028
06:27
these people are probably the most
influential ones in that organization,
influential ones in that organization,
111
375169
3635
06:30
the ones that know more about the past,
112
378828
2008
06:32
and the future plans and goals
of this particular cell.
of this particular cell.
113
380860
2877
06:37
We can also see this shift
from trees into networks
from trees into networks
114
385232
3006
06:40
in the way we classify
and organize species.
and organize species.
115
388262
2991
06:45
The image on the right
is the only illustration
is the only illustration
116
393245
2829
06:48
that Darwin included
in "The Origin of Species,"
in "The Origin of Species,"
117
396098
3112
06:51
which Darwin called the "Tree of Life."
118
399234
2261
06:54
There's actually a letter
from Darwin to the publisher,
from Darwin to the publisher,
119
402098
2885
06:57
expanding on the importance
of this particular diagram.
of this particular diagram.
120
405007
2656
06:59
It was critical for Darwin's
theory of evolution.
theory of evolution.
121
407687
2642
07:03
But recently, scientists discovered
that overlaying this tree of life
that overlaying this tree of life
122
411408
3567
07:06
is a dense network of bacteria,
123
414999
2435
07:09
and these bacteria
are actually tying together
are actually tying together
124
417458
2161
07:11
species that were completely
separated before,
separated before,
125
419643
2172
07:13
to what scientists are now calling
not the tree of life,
not the tree of life,
126
421839
3080
07:16
but the web of life, the network of life.
127
424943
2856
07:21
And finally, we can really
see this shift, again,
see this shift, again,
128
429489
2514
07:24
when we look at ecosystems
around our planet.
around our planet.
129
432027
2424
07:27
No more do we have these simplified
predator-versus-prey diagrams
predator-versus-prey diagrams
130
435599
3166
07:30
we have all learned at school.
131
438789
1447
07:33
This is a much more accurate
depiction of an ecosystem.
depiction of an ecosystem.
132
441201
2989
07:36
This is a diagram created
by Professor David Lavigne,
by Professor David Lavigne,
133
444214
2904
07:39
mapping close to 100 species
that interact with the codfish
that interact with the codfish
134
447142
3500
07:42
off the coast of Newfoundland in Canada.
135
450666
2951
07:46
And I think here, we can really understand
the intricate and interdependent nature
the intricate and interdependent nature
136
454244
3937
07:50
of most ecosystems
that abound on our planet.
that abound on our planet.
137
458205
2523
07:54
But even though recent,
this metaphor of the network,
this metaphor of the network,
138
462442
3644
07:58
is really already adopting
various shapes and forms,
various shapes and forms,
139
466110
3103
08:01
and it's almost becoming
a growing visual taxonomy.
a growing visual taxonomy.
140
469237
2463
08:03
It's almost becoming
the syntax of a new language.
the syntax of a new language.
141
471724
2647
08:06
And this is one aspect
that truly fascinates me.
that truly fascinates me.
142
474395
2633
08:09
And these are actually
15 different typologies
15 different typologies
143
477678
2533
08:12
I've been collecting over time,
144
480235
2135
08:14
and it really shows the immense
visual diversity of this new metaphor.
visual diversity of this new metaphor.
145
482394
4022
08:19
And here is an example.
146
487001
1222
08:20
On the very top band,
you have radial convergence,
you have radial convergence,
147
488818
3933
08:24
a visualization model that has become
really popular over the last five years.
really popular over the last five years.
148
492775
3939
08:29
At the top left, the very first project
is a gene network,
is a gene network,
149
497198
4354
08:33
followed by a network
of IP addresses -- machines, servers --
of IP addresses -- machines, servers --
150
501576
4009
08:37
followed by a network of Facebook friends.
151
505609
2972
08:41
You probably couldn't find
more disparate topics,
more disparate topics,
152
509240
2508
08:43
yet they are using the same metaphor,
the same visual model,
the same visual model,
153
511772
3794
08:47
to map the never-ending complexities
of its own subject.
of its own subject.
154
515590
3606
08:52
And here are a few more examples
of the many I've been collecting,
of the many I've been collecting,
155
520545
3124
08:55
of this growing visual
taxonomy of networks.
taxonomy of networks.
156
523693
2738
09:00
But networks are not just
a scientific metaphor.
a scientific metaphor.
157
528248
2865
09:04
As designers, researchers, and scientists
try to map a variety of complex systems,
try to map a variety of complex systems,
158
532192
5541
09:09
they are in many ways influencing
traditional art fields,
traditional art fields,
159
537757
2813
09:12
like painting and sculpture,
160
540594
1402
09:14
and influencing many different artists.
161
542020
1993
09:16
And perhaps because networks have
this huge aesthetical force to them --
this huge aesthetical force to them --
162
544718
4042
09:20
they're immensely gorgeous --
163
548784
1958
09:22
they are really becoming a cultural meme,
164
550766
2056
09:24
and driving a new art movement,
which I've called "networkism."
which I've called "networkism."
165
552846
4325
09:30
And we can see this influence
in this movement in a variety of ways.
in this movement in a variety of ways.
166
558544
3208
09:33
This is just one of many examples,
167
561776
1793
09:35
where you can see this influence
from science into art.
from science into art.
168
563593
2725
09:38
The example on your left side
is IP-mapping,
is IP-mapping,
169
566342
2871
09:41
a computer-generated map of IP addresses;
again -- servers, machines.
again -- servers, machines.
170
569237
3659
09:45
And on your right side,
171
573253
1205
09:46
you have "Transient Structures
and Unstable Networks" by Sharon Molloy,
and Unstable Networks" by Sharon Molloy,
172
574482
4618
09:51
using oil and enamel on canvas.
173
579124
2094
09:53
And here are a few more
paintings by Sharon Molloy,
paintings by Sharon Molloy,
174
581870
3105
09:56
some gorgeous, intricate paintings.
175
584999
1932
10:00
And here's another example
of that interesting cross-pollination
of that interesting cross-pollination
176
588375
3306
10:03
between science and art.
177
591705
1404
10:05
On your left side,
you have "Operation Smile."
you have "Operation Smile."
178
593475
2665
10:08
It is a computer-generated map
of a social network.
of a social network.
179
596164
2889
10:11
And on your right side,
you have "Field 4," by Emma McNally,
you have "Field 4," by Emma McNally,
180
599077
3726
10:14
using only graphite on paper.
181
602827
2086
10:17
Emma McNally is one of the main
leaders of this movement,
leaders of this movement,
182
605374
3517
10:20
and she creates these striking,
imaginary landscapes,
imaginary landscapes,
183
608915
2569
10:23
where you can really notice the influence
from traditional network visualization.
from traditional network visualization.
184
611508
4665
10:30
But networkism doesn't happen
only in two dimensions.
only in two dimensions.
185
618324
3007
10:33
This is perhaps
one of my favorite projects
one of my favorite projects
186
621355
2278
10:35
of this new movement.
187
623657
1405
10:37
And I think the title really
says it all -- it's called:
says it all -- it's called:
188
625086
2634
10:39
"Galaxies Forming Along Filaments,
189
627744
2167
10:41
Like Droplets Along the Strands
of a Spider's Web."
of a Spider's Web."
190
629935
3332
10:46
And I just find this particular project
to be immensely powerful.
to be immensely powerful.
191
634616
3080
10:49
It was created by Tomás Saraceno,
192
637720
1960
10:51
and he occupies these large spaces,
193
639704
2698
10:54
creates these massive installations
using only elastic ropes.
using only elastic ropes.
194
642426
3342
10:57
As you actually navigate that space
and bounce along those elastic ropes,
and bounce along those elastic ropes,
195
645792
3817
11:01
the entire network kind of shifts,
almost like a real organic network would.
almost like a real organic network would.
196
649633
4575
11:07
And here's yet another example
197
655414
2032
11:09
of networkism taken
to a whole different level.
to a whole different level.
198
657470
2389
11:12
This was created
by Japanese artist Chiharu Shiota
by Japanese artist Chiharu Shiota
199
660303
3213
11:15
in a piece called "In Silence."
200
663540
1755
11:17
And Chiharu, like Tomás Saraceno,
fills these rooms with this dense network,
fills these rooms with this dense network,
201
665834
5355
11:23
this dense web of elastic ropes
and black wool and thread,
and black wool and thread,
202
671213
3762
11:26
sometimes including objects,
as you can see here,
as you can see here,
203
674999
2759
11:29
sometimes even including people,
in many of her installations.
in many of her installations.
204
677782
3022
11:35
But networks are also
not just a new trend,
not just a new trend,
205
683374
2691
11:38
and it's too easy for us
to dismiss it as such.
to dismiss it as such.
206
686089
2364
11:41
Networks really embody
notions of decentralization,
notions of decentralization,
207
689029
3607
11:44
of interconnectedness, of interdependence.
208
692660
3134
11:48
And this new way of thinking is critical
209
696303
2476
11:50
for us to solve many of the complex
problems we are facing nowadays,
problems we are facing nowadays,
210
698803
3730
11:54
from decoding the human brain,
211
702557
1841
11:56
to understanding
the vast universe out there.
the vast universe out there.
212
704422
2403
11:59
On your left side, you have a snapshot
of a neural network of a mouse --
of a neural network of a mouse --
213
707746
4489
12:04
very similar to our own
at this particular scale.
at this particular scale.
214
712259
2420
12:07
And on your right side, you have
the Millennium Simulation.
the Millennium Simulation.
215
715500
2966
12:10
It was the largest
and most realistic simulation
and most realistic simulation
216
718490
2748
12:13
of the growth of cosmic structure.
217
721262
1790
12:15
It was able to recreate the history
of 20 million galaxies
of 20 million galaxies
218
723490
4516
12:20
in approximately 25 terabytes of output.
219
728030
3090
12:24
And coincidentally or not,
220
732081
1413
12:25
I just find this particular comparison
221
733518
1873
12:27
between the smallest scale
of knowledge -- the brain --
of knowledge -- the brain --
222
735415
2703
12:30
and the largest scale of knowledge --
the universe itself --
the universe itself --
223
738142
2829
12:32
to be really quite striking
and fascinating.
and fascinating.
224
740995
2277
12:35
Because as Bruce Mau once said,
225
743807
2634
12:38
"When everything is connected
to everything else,
to everything else,
226
746465
2412
12:40
for better or for worse,
everything matters."
everything matters."
227
748901
2397
12:43
Thank you so much.
228
751322
1151
12:44
(Applause)
229
752497
3802
ABOUT THE SPEAKER
Manuel Lima - Data visualization researcherManuel Lima studies how information can be organized -- into elegant and beautiful diagrams that illustrate the many unexpected twists of big data.
Why you should listen
Data expert Manuel Lima approaches intimidatingly dry stacks of bits with the eye of a designer. His website, VisualComplexity, is an encyclopedic and visually stunning catalog of the myriad paths artists take to illuminate the shadowy corners of stockpiled information, whether it’s a taxonomy of rap names or tracking oil money.
Lima’s passion for data has also driven him to become a historian. In The Book of Trees, he digs to the 12th-century roots of the tree diagram, one of humanity’s most powerful and ancient tools for visually representing knowledge.
More profile about the speakerLima’s passion for data has also driven him to become a historian. In The Book of Trees, he digs to the 12th-century roots of the tree diagram, one of humanity’s most powerful and ancient tools for visually representing knowledge.
Manuel Lima | Speaker | TED.com