A Visual History of Human Knowledge Manuel Lima TED Talks

Over the past 10 years,

I’ve been researching the way
people organize and visualize information.

And I’ve noticed an interesting shift.

For a long period of time,

we believed in a natural ranking order
in the world around us,

also known as the great chain of being,
or “Scala naturae” in Latin,

a top-down structure that normally starts
with God at the very top,

followed by angels, noblemen,

common people, animals, and so on.

This idea was actually based
on Aristotle’s ontology,

which classified all things known to man
in a set of opposing categories,

like the ones you see behind me.

But over time, interestingly enough,

this concept adopted
the branching schema of a tree

in what became known
as the Porphyrian tree,

also considered to be
the oldest tree of knowledge.

The branching scheme
of the tree was, in fact,

such a powerful metaphor
for conveying information

that it became, over time,
an important communication tool

to map a variety of systems of knowledge.

We can see trees being used
to map morality,

with the popular tree of virtues
and tree of vices,

as you can see here, with these beautiful
illustrations from medieval Europe.

We can see trees being used
to map consanguinity,

the various blood ties between people.

We can also see trees being used
to map genealogy,

perhaps the most famous archetype
of the tree diagram.

I think many of you in the audience
have probably seen family trees.

Many of you probably even have
your own family trees drawn in such a way.

We can see trees even mapping
systems of law,

the various decrees and rulings
of kings and rulers.

And finally, of course,
also a very popular scientific metaphor,

we can see trees being used
to map all species known to man.

And trees ultimately became
such a powerful visual metaphor

because in many ways,
they really embody this human desire

for order, for balance,
for unity, for symmetry.

However, nowadays we are really facing
new complex, intricate challenges

that cannot be understood by simply
employing a simple tree diagram.

And a new metaphor is currently emerging,

and it’s currently replacing the tree

in visualizing various
systems of knowledge.

It’s really providing us with a new lens
to understand the world around us.

And this new metaphor
is the metaphor of the network.

And we can see this shift
from trees into networks

in many domains of knowledge.

We can see this shift in the way
we try to understand the brain.

While before, we used
to think of the brain

as a modular, centralized organ,

where a given area was responsible
for a set of actions and behaviors,

the more we know about the brain,

the more we think of it
as a large music symphony,

played by hundreds
and thousands of instruments.

This is a beautiful snapshot
created by the Blue Brain Project,

where you can see 10,000 neurons
and 30 million connections.

And this is only mapping 10 percent
of a mammalian neocortex.

We can also see this shift in the way
we try to conceive of human knowledge.

These are some remarkable trees
of knowledge, or trees of science,

by Spanish scholar Ramon Llull.

And Llull was actually the precursor,

the very first one who created
the metaphor of science as a tree,

a metaphor we use
every single day, when we say,

“Biology is a branch of science,”

when we say,

“Genetics is a branch of science.”

But perhaps the most beautiful of all
trees of knowledge, at least for me,

was created for the French encyclopedia
by Diderot and d’Alembert in 1751.

This was really the bastion
of the French Enlightenment,

and this gorgeous illustration
was featured as a table of contents

for the encyclopedia.

And it actually maps out
all domains of knowledge

as separate branches of a tree.

But knowledge is much more
intricate than this.

These are two maps of Wikipedia
showing the inter-linkage of articles –

related to history on the left,
and mathematics on the right.

And I think by looking at these maps

and other ones that have been
created of Wikipedia –

arguably one of the largest rhizomatic
structures ever created by man –

we can really understand
how human knowledge is much more intricate

and interdependent, just like a network.

We can also see this interesting shift

in the way we map
social ties between people.

This is the typical organization chart.

I’m assuming many of you have seen
a similar chart as well,

in your own corporations, or others.

It’s a top-down structure

that normally starts
with the CEO at the very top,

and where you can drill down all the way
to the individual workmen on the bottom.

But humans sometimes are, well, actually,
all humans are unique in their own way,

and sometimes you really don’t play well
under this really rigid structure.

I think the Internet is really changing
this paradigm quite a lot.

This is a fantastic map
of online social collaboration

between Perl developers.

Perl is a famous programming language,

and here, you can see
how different programmers

are actually exchanging files,
and working together on a given project.

And here, you can notice that this is
a completely decentralized process –

there’s no leader in this organization,

it’s a network.

We can also see this interesting shift
when we look at terrorism.

One of the main challenges
of understanding terrorism nowadays

is that we are dealing with
decentralized, independent cells,

where there’s no leader
leading the whole process.

And here, you can actually see
how visualization is being used.

The diagram that you see behind me

shows all the terrorists involved
in the Madrid attack in 2004.

And what they did here is,
they actually segmented the network

into three different years,

represented by the vertical layers
that you see behind me.

And the blue lines tie together

the people that were present
in that network year after year.

So even though there’s no leader per se,

these people are probably the most
influential ones in that organization,

the ones that know more about the past,

and the future plans and goals
of this particular cell.

We can also see this shift
from trees into networks

in the way we classify
and organize species.

The image on the right
is the only illustration

that Darwin included
in “The Origin of Species,”

which Darwin called the “Tree of Life.”

There’s actually a letter
from Darwin to the publisher,

expanding on the importance
of this particular diagram.

It was critical for Darwin’s
theory of evolution.

But recently, scientists discovered
that overlaying this tree of life

is a dense network of bacteria,

and these bacteria
are actually tying together

species that were completely
separated before,

to what scientists are now calling
not the tree of life,

but the web of life, the network of life.

And finally, we can really
see this shift, again,

when we look at ecosystems
around our planet.

No more do we have these simplified
predator-versus-prey diagrams

we have all learned at school.

This is a much more accurate
depiction of an ecosystem.

This is a diagram created
by Professor David Lavigne,

mapping close to 100 species
that interact with the codfish

off the coast of Newfoundland in Canada.

And I think here, we can really understand
the intricate and interdependent nature

of most ecosystems
that abound on our planet.

But even though recent,
this metaphor of the network,

is really already adopting
various shapes and forms,

and it’s almost becoming
a growing visual taxonomy.

It’s almost becoming
the syntax of a new language.

And this is one aspect
that truly fascinates me.

And these are actually
15 different typologies

I’ve been collecting over time,

and it really shows the immense
visual diversity of this new metaphor.

And here is an example.

On the very top band,
you have radial convergence,

a visualization model that has become
really popular over the last five years.

At the top left, the very first project
is a gene network,

followed by a network
of IP addresses – machines, servers –

followed by a network of Facebook friends.

You probably couldn’t find
more disparate topics,

yet they are using the same metaphor,
the same visual model,

to map the never-ending complexities
of its own subject.

And here are a few more examples
of the many I’ve been collecting,

of this growing visual
taxonomy of networks.

But networks are not just
a scientific metaphor.

As designers, researchers, and scientists
try to map a variety of complex systems,

they are in many ways influencing
traditional art fields,

like painting and sculpture,

and influencing many different artists.

And perhaps because networks have
this huge aesthetical force to them –

they’re immensely gorgeous –

they are really becoming a cultural meme,

and driving a new art movement,
which I’ve called “networkism.”

And we can see this influence
in this movement in a variety of ways.

This is just one of many examples,

where you can see this influence
from science into art.

The example on your left side
is IP-mapping,

a computer-generated map of IP addresses;
again – servers, machines.

And on your right side,

you have “Transient Structures
and Unstable Networks” by Sharon Molloy,

using oil and enamel on canvas.

And here are a few more
paintings by Sharon Molloy,

some gorgeous, intricate paintings.

And here’s another example
of that interesting cross-pollination

between science and art.

On your left side,
you have “Operation Smile.”

It is a computer-generated map
of a social network.

And on your right side,
you have “Field 4,” by Emma McNally,

using only graphite on paper.

Emma McNally is one of the main
leaders of this movement,

and she creates these striking,
imaginary landscapes,

where you can really notice the influence
from traditional network visualization.

But networkism doesn’t happen
only in two dimensions.

This is perhaps
one of my favorite projects

of this new movement.

And I think the title really
says it all – it’s called:

“Galaxies Forming Along Filaments,

Like Droplets Along the Strands
of a Spider’s Web.”

And I just find this particular project
to be immensely powerful.

It was created by Tomás Saraceno,

and he occupies these large spaces,

creates these massive installations
using only elastic ropes.

As you actually navigate that space
and bounce along those elastic ropes,

the entire network kind of shifts,
almost like a real organic network would.

And here’s yet another example

of networkism taken
to a whole different level.

This was created
by Japanese artist Chiharu Shiota

in a piece called “In Silence.”

And Chiharu, like Tomás Saraceno,
fills these rooms with this dense network,

this dense web of elastic ropes
and black wool and thread,

sometimes including objects,
as you can see here,

sometimes even including people,
in many of her installations.

But networks are also
not just a new trend,

and it’s too easy for us
to dismiss it as such.

Networks really embody
notions of decentralization,

of interconnectedness, of interdependence.

And this new way of thinking is critical

for us to solve many of the complex
problems we are facing nowadays,

from decoding the human brain,

to understanding
the vast universe out there.

On your left side, you have a snapshot
of a neural network of a mouse –

very similar to our own
at this particular scale.

And on your right side, you have
the Millennium Simulation.

It was the largest
and most realistic simulation

of the growth of cosmic structure.

It was able to recreate the history
of 20 million galaxies

in approximately 25 terabytes of output.

And coincidentally or not,

I just find this particular comparison

between the smallest scale
of knowledge – the brain –

and the largest scale of knowledge –
the universe itself –

to be really quite striking
and fascinating.

Because as Bruce Mau once said,

“When everything is connected
to everything else,

for better or for worse,
everything matters.”

Thank you so much.

(Applause)

在过去的 10 年里,

我一直在研究
人们组织和可视化信息的方式。

我注意到一个有趣的转变。

长期以来,

我们相信
我们周围世界的自然排序顺序,

也称为存在的大链,
或拉丁语中的“Scala naturae”,

一种自上而下的结构,通常
以上帝开头 最高,

其次是天使、贵族、

平民、动物等等。

这个想法实际上是
基于亚里士多德的本体论,

它将人类已知的所有事物分类
在一组相反的类别中,

就像你在我身后看到的那些。

但随着时间的推移,有趣的是,

这个概念采用
了树的分支模式,


称为 Porphyrian 树,

也被认为是
最古老的知识树。

事实上,树的分支方案是传达信息

的有力隐喻

以至于随着时间的推移,它成为

映射各种知识系统的重要交流工具。

我们可以看到树木被
用来绘制道德地图,

还有流行的
美德树和恶习树,

正如你在这里看到的,这些
来自中世纪欧洲的精美插图。

我们可以看到树木被
用来描绘血缘

关系,人们之间的各种血缘关系。

我们还可以看到
用于绘制家谱的树,

这可能
是树图最著名的原型。

我想在座的很多
人可能都看过家谱。

你们中的许多人甚至可能有
自己的家谱以这种方式绘制。

我们可以看到树木甚至绘制
法律系统,国王和统治者

的各种法令和
裁决。

最后,当然,这
也是一个非常流行的科学比喻,

我们可以看到树木被
用来绘制人类已知的所有物种的地图。

树木最终成为了
如此强大的视觉隐喻,

因为在许多方面,
它们真正体现了人类

对秩序、平衡
、统一和对称的渴望。

然而,如今我们确实面临着
新的复杂、错综复杂的挑战

,这些挑战无法
通过简单的树形图来理解。

目前正在出现一个新的隐喻

,它正在取代树,

以可视化
各种知识系统。

它确实为我们提供了一个新的视角
来了解我们周围的世界。

而这个新
的隐喻就是网络的隐喻。

我们可以在许多知识领域看到这种
从树到网络的转变

我们可以在尝试理解大脑的方式上看到这种转变

以前,
我们认为大脑

是一个模块化的集中式器官

,特定区域
负责一系列动作和行为

,我们对大脑了解

得越多,就越认为它
是一首大型音乐交响乐 ,


成百上千的乐器演奏。

这是
蓝脑计划创建的精美快照

,您可以在其中看到 10,000 个神经元
和 3000 万个连接。

这只是映射
了哺乳动物新皮层的 10%。

我们还可以看到
我们尝试构想人类知识的方式的这种转变。

这些

是西班牙学者拉蒙·鲁尔(Ramon Llull)的一些非凡的知识树或科学树。

Llull 实际上是先驱者,

是第一个
将科学比喻为树的人,

我们
每天都在使用这个比喻,当我们说

“生物学是科学的一个分支”

时,当我们说

“遗传学是 科学的分支。”


至少对我来说,也许所有知识树中最美丽的一棵

是狄德罗和达朗贝尔在 1751 年为法国百科全书创作的。

这确实
是法国启蒙运动的堡垒

,这张华丽的
插图被用作一张桌子

百科全书的内容。

它实际上将
所有知识领域映射

为树的单独分支。

但知识
远比这复杂得多。

这是 Wikipedia 的两张地图,
显示了文章之间的相互联系

——左边是历史
,右边是数学。

而且我认为通过查看这些地图

以及
维基百科创建的其他地图——

可以说是人类创造的最大的根茎
结构之一——

我们可以真正
理解人类知识是如何更加复杂

和相互依赖的,就像一个网络 .

我们还可以

在绘制
人与人之间的社会关系的方式中看到这种有趣的转变。

这是典型的组织结构图。

我假设你们中的许多人也曾

在自己的公司或其他公司中看到过类似的图表。

这是一个自上而下的结构

,通常从
最高层的 CEO 开始

,您可以一直向下钻取
到最底层的单个工人。

但是人类有时,嗯,实际上,
所有的人都有自己独特的方式

,有时你
在这种非常僵化的结构下真的玩得不好。

我认为互联网确实
在很大程度上改变了这种范式。

这是

Perl 开发人员之间在线社交协作的精彩地图。

Perl 是一种著名的编程语言

,在这里,您可以
看到不同的程序员

如何实际交换文件,
并在给定项目上一起工作。

在这里,你可以注意到这是
一个完全去中心化的过程——

这个组织中没有领导者,

它是一个网络。 当我们审视恐怖主义时,

我们也可以看到这种有趣的转变
。 当今理解恐怖主义

的主要挑战之一

是我们正在处理
分散的、独立的小组,

在那里没有领导者
领导整个过程。

在这里,您实际上可以看到
如何使用可视化。

你在我身后看到的图表

显示了
参与 2004 年马德里袭击的所有恐怖分子。

他们在这里所做的是,
他们实际上将网络

划分为三个不同的年份,


你在我身后看到的垂直层表示。

蓝线将

年复一年出现在该网络中的人们联系在一起。

因此,即使本身没有领导者,

这些人也可能
是该组织中最有影响力的人,他们

更了解过去,

以及这个特定小组的未来计划和
目标。

在我们对物种进行分类和组织的方式中,我们还可以看到这种从树木到网络的转变

右图

达尔文
在《物种起源》

中收录的唯一插图,达尔文称之为“生命之树”。

实际上有
一封达尔文写给出版商的信,

阐述
了这个特殊图表的重要性。

这对达尔文的
进化论至关重要。

但最近,科学家们发现
,覆盖在这棵生命之树上的

是一个密集的细菌网络

,这些
细菌实际上

将之前完全分离的物种联系在一起

,科学家们现在所说的
不是生命之树,

而是生命之网, 生活的网络。

最后,当我们观察地球周围的生态系统时,我们可以
再次真正看到这种转变

我们不再有这些

我们在学校都学过的简化的捕食者与猎物的图表。

这是
对生态系统的更准确描述。

这是
由大卫·拉维尼教授

绘制的图表,绘制了近 100 种
与加拿大纽芬兰海岸鳕鱼相互作用的物种

我认为在这里,我们可以真正
理解地球上大多数生态系统错综复杂且相互依存的本质

但即使是最近,
网络的这种隐喻

,实际上已经采用了
各种形状和形式,

并且几乎成为
一种不断增长的视觉分类法。

它几乎正在
成为一种新语言的语法。


是真正让我着迷的一个方面。

这些实际上是我一直在收集的
15 种不同的类型

,它确实展示
了这个新隐喻的巨大视觉多样性。

这是一个例子。

在最上面的波段,
你有径向收敛,


是一种在过去五年中非常流行的可视化模型。

在左上角,第一个项目
是基因网络,

然后
是 IP 地址网络——机器、服务器——

然后是 Facebook 朋友网络。

您可能找不到
更多不同的主题,

但它们使用相同的隐喻
、相同的视觉模型

来描绘其主题永无止境的复杂
性。

这里还有
一些我一直在收集的例子,

关于这种不断增长
的网络视觉分类。

但网络不仅仅是
一个科学隐喻。

当设计师、研究人员和科学家
试图绘制各种复杂的系统时,

他们在许多方面影响着
传统艺术领域,

如绘画和雕塑,

并影响着许多不同的艺术家。

也许是因为网络
对他们来说具有巨大的审美力量——

它们非常华丽——

它们确实正在成为一种文化模因,

并推动了一场新的艺术运动
,我称之为“网络主义”。

我们可以
通过多种方式在这场运动中看到这种影响。

这只是众多例子之一

,您可以在其中看到这种
从科学到艺术的影响。

左侧的示例
是 IP 映射

,即计算机生成的 IP 地址映射;
再次 - 服务器,机器。

在你的右边,

你有莎朗莫洛伊的“瞬态结构
和不稳定网络”,

在画布上使用油画和珐琅。

这里还有一些
莎朗·莫洛伊(Sharon Molloy)的画作,

一些华丽而复杂的画作。

这是科学与艺术
之间有趣的异花授粉的另一个例子

在你的左边,
你有“微笑行动”。

它是由计算机生成
的社交网络地图。

在您的右侧,
您有 Emma McNally 的“Field 4”,

仅在纸上使用石墨。

艾玛麦克纳利是这一运动的主要
领导者之一

,她创造了这些引人注目的、
想象的景观,

在那里你可以真正注意到
传统网络可视化的影响。

但网络主义不仅仅发生
在两个维度上。

这也许
是这个新运动中我最喜欢的项目

之一。

我认为这个标题真的
说明了一切——它被称为:

“沿着细丝形成的星系,

就像沿着蜘蛛网的链状液滴一样
。”

我只是发现这个特定的
项目非常强大。

它是由 Tomás Saraceno 创造的

,他占据了这些大空间,只使用弹性绳索

创造了这些巨大的装置

当你实际导航那个空间
并沿着那些弹性绳索弹跳时

,整个网络会发生变化,
几乎就像一个真正的有机网络一样。

这是另一个

完全不同层次的网络主义示例。

这是
由日本艺术家 Chiharu Shiota

在名为“In Silence”的作品中创作的。

Chiharu 和 Tomás Saraceno 一样,在
这些房间里布满了这个密集的网络,

这个由弹性绳索
和黑色羊毛和线组成的密集网络,

有时包括物体,
正如你在这里看到的,

有时甚至包括人,
在她的许多装置中。

但网络也
不仅仅是一种新趋势

,我们很
容易忽视它。

网络真正体现
了去中心化

、相互联系、相互依赖的概念。

这种新的思维方式

对于我们解决
当今面临的许多复杂问题至关重要,

从解码人脑

到理解
那里的浩瀚宇宙。

在你的左边,你有
一个老鼠神经网络的快照——

在这个特定的规模上与我们自己的非常相似。

在您的右侧,您
拥有千年模拟。

这是对宇宙结构生长的最大
、最真实的

模拟。

它能够

在大约 25 TB 的输出中重现 2000 万个星系的历史。

不管巧合与否,

我只是发现

最小
的知识范围——大脑——

和最大的知识范围
——宇宙本身

——之间的这种特殊比较真的非常引人注目
和迷人。

因为正如 Bruce Mau 曾经说过的那样,

“当一切都与其他一切联系在一起时

,无论好坏,
一切都很重要。”

太感谢了。

(掌声)