ABOUT THE SPEAKER
Giorgia Lupi - Information designer
Giorgia Lupi sees beauty in data. She challenges the impersonality that data communicate, designing engaging visual narratives that re-connect numbers to what they stand for: stories, people, ideas.

Why you should listen

What sets Giorgia Lupi apart is her humanistic approach to the world of data.

Her work frequently crosses the divide between digital, print and handcrafted representations of information: primarily, she draws with data. She has a passion for and obsession with data, the material she uses to tell stories, and the lens through which she sees the world.

Data are often considered to be very impersonal, boring and clinical, but Lupi's work proves the opposite. She makes sense of data with a curious mind and a heterogeneous arsenal, which ranges from digital technology to exhausting and repetitive manual labor. She believes we will ultimately unlock the full potential of data only when we embrace their nature, and make them part of our lives, which will inevitably make data more human in the process.

Trained as an architect, Lupi has always been driven by opposing forces: analysis and intuition, logic and beauty, numbers and images. True to these dichotomies, in 2011 she started both her own company and studying for a PhD. She earned her ddoctorate in design at Politecnico di Milano, where she focused on information mapping, and she is now the design director and co-founder of Accurat, a global, data-driven research, design and innovation firm with offices in Milan and New York. She relocated from Italy to New York City, where she now lives.

Thanks to her work and research, Giorgia is a prominent voice in the world of data. She has spoken at numerous events, universities and institutions around the world, including the Museum of Modern Art, the Guggenheim Museum, PopTech Conference, Eyeo Festival, Fast Company Innovation by Design, New York University, Columbia University and the New York Public Library. She has been featured in major international outlets such as the New York Times, The Guardian, the Washington Post, NPR, BBC, TIME magazine, National Geographic, Scientific American, Popular Science, Wired, Vogue, Vanity Fair, Monocle and more. Her work has been exhibited at the Design Museum, the Science Museum, and Somerset House in London; the New York Hall of Science and the Storefront for Art and Architecture in New York; at the Triennale Design Museum and the Design Week in Milan, among others.

With her company, Accurat, she has worked with major international clients including IBM, Google, Microsoft, the United Nations, the World Health Organization, the World Economic Forum, the European Union, the Louis Vuitton-Moet-Hennessy Group, Fiat Chrysler Automobiles, J.P. Morgan Asset Management, Unicredit Group and KPMG Advisory.

Giorgia is the co-author of Dear Data, an aspirational hand-drawn data visualization book that explores the more slippery details of daily life through data, revealing the patterns that inform our decisions and affect our relationships.

Her work is part of the permanent collection of the Museum of Modern Art.

More profile about the speaker
Giorgia Lupi | Speaker | TED.com
TEDNYC

Giorgia Lupi: How we can find ourselves in data

Giorgia Lupi: Como nos encontrar num banco de dados

Filmed:
1,279,894 views

Giorgia Lupi usa dados para contar histórias humanas, somando nuance aos números. Nesta palestra encantadora, ela nos conta como podemos trazer personalidade para os dados, visualizando até os detalhes mais mundanos das nossas vidas diárias e como transformar o abstrato e incontável em algo que possa ser visto, sentido e reconectado diretamente em nossas vidas.
- Information designer
Giorgia Lupi sees beauty in data. She challenges the impersonality that data communicate, designing engaging visual narratives that re-connect numbers to what they stand for: stories, people, ideas. Full bio

Double-click the English transcript below to play the video.

00:12
This is what my last week looked like.
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Assim foi a minha semana passada.
00:16
What I did,
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O que eu fiz,
00:18
who I was with,
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com quem estive,
00:20
the main sensations I had
for every waking hour ...
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os sentimentos principais
que tive em cada hora acordada.
00:24
If the feeling came as I thought of my dad
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Se o sentimento me ocorreu
ao pensar em meu pai,
00:26
who recently passed away,
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que faleceu recentemente,
00:28
or if I could have just definitely
avoided the worries and anxieties.
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ou se eu pudesse ter evitado
preocupações e ansiedades.
00:32
And if you think I'm a little obsessive,
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Se me acham um pouco obsessiva,
00:34
you're probably right.
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provavelmente estão certos.
00:36
But clearly, from this visualization,
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Claramente, nesta apresentação,
00:38
you can learn much more about me
than from this other one,
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vocês aprendem muito mais sobre mim
do que nesta próxima,
00:41
which are images you're
probably more familiar with
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provavelmente com imagens mais familiares
00:44
and which you possibly even have
on your phone right now.
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e que possivelmente vocês
têm em seus telefones.
00:47
Bar charts for the steps you walked,
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Gráficos de barras para os passos andados,
00:50
pie charts for the quality
of your sleep --
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gráficos circulares
para a qualidade de sono,
00:52
the path of your morning runs.
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o caminho das corridas matinais.
00:55
In my day job, I work with data.
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No meu trabalho, eu lido com dados.
00:57
I run a data visualization design company,
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Eu dirijo uma empresa de design
de visualização de dados
01:00
and we design and develop ways
to make information accessible
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e nós criamos e desenvolvemos
formas de tornar os dados acessíveis
01:03
through visual representations.
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através de representações visuais.
01:05
What my job has taught me over the years
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O que o meu trabalho
me ensinou através dos anos
01:08
is that to really understand data
and their true potential,
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é que para entender os dados
e seu potencial verdadeiro,
01:12
sometimes we actually
have to forget about them
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às vezes temos que nos esquecer deles
01:16
and see through them instead.
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para enxergar através deles.
01:18
Because data are always
just a tool we use to represent reality.
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Os dados são só uma ferramenta
que usamos para representar a realidade.
01:22
They're always used
as a placeholder for something else,
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São sempre usados como substitutos
de algo diferente,
01:24
but they are never the real thing.
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mas nunca são a realidade em si.
01:27
But let me step back for a moment
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Permitam-me recuar um momento
para quando eu entendi isso pessoalmente.
01:29
to when I first understood
this personally.
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01:32
In 1994, I was 13 years old.
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Em 1994, eu tinha 13 anos.
01:35
I was a teenager in Italy.
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Eu era uma adolescente na Itália.
01:37
I was too young
to be interested in politics,
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Eu era jovem demais
para me interessar por política,
01:40
but I knew that a businessman,
Silvio Berlusconi,
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mas eu sabia que um empresário,
o Silvio Berlusconi,
01:42
was running for president
for the moderate right.
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tinha se candidatado à presidência
pela direita moderada.
01:46
We lived in a very liberal town,
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Nós morávamos numa cidade bem pequena,
01:48
and my father was a politician
for the Democratic Party.
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e meu pai era político
pelo Partido Democrático.
01:51
And I remember that no one thought
that Berlusconi could get elected --
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Eu me lembro que ninguém pensava
que Berlusconi poderia ser eleito;
01:55
that was totally not an option.
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não era nem uma opção.
01:58
But it happened.
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Mas aconteceu.
01:59
And I remember the feeling very vividly.
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Eu me lembro do sentimento bem fortemente.
02:02
It was a complete surprise,
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Foi uma surpresa completa,
02:04
as my dad promised that in my town
he knew nobody who voted for him.
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já que meu pai jurava que ninguém
na minha cidade havia votado para ele.
02:10
This was the first time
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Foi a primeira vez
02:12
when the data I had gave me
a completely distorted image of reality.
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que a informação que eu recebi me deu
uma imagem distorcida da realidade.
02:17
My data sample was actually
pretty limited and skewed,
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Minha informação
era limitada e partidária,
02:20
so probably it was because of that,
I thought, I lived in a bubble,
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talvez foi por esta razão,
eu pensei, que vivia numa redoma,
02:24
and I didn't have enough chances
to see outside of it.
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e eu não tinha oportunidades
suficientes para ver fora dela.
02:28
Now, fast-forward to November 8, 2016
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Avancemos para 8 de novembro de 2016
02:31
in the United States.
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nos EUA.
02:33
The internet polls,
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As pesquisas na internet,
02:35
statistical models,
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os modelos estatísticos,
02:36
all the pundits agreeing on a possible
outcome for the presidential election.
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todos os especialistas de acordo
sobre o resultado possível da eleição.
02:41
It looked like we had
enough information this time,
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Parecia que tínhamos informações
suficientes desta vez,
02:44
and many more chances to see outside
the closed circle we lived in --
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e muito mais chances de ver fora
do círculo no qual vivíamos,
02:48
but we clearly didn't.
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mas claramente não tínhamos.
02:50
The feeling felt very familiar.
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O sentimento me era bem familiar.
02:52
I had been there before.
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Já tinha vivido aquilo antes.
02:54
I think it's fair to say
the data failed us this time --
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Acho justo dizer que os dados
foram falhos desta vez,
02:57
and pretty spectacularly.
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de forma espetacular.
02:59
We believed in data,
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Nós acreditamos em dados,
mas o que aconteceu,
03:00
but what happened,
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03:02
even with the most respected newspaper,
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até com o jornal mais respeitado,
03:05
is that the obsession to reduce everything
to two simple percentage numbers
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é que a obsessão de reduzir tudo
em dois números percentuais simples
03:09
to make a powerful headline
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para deixar as manchetes mais marcantes
03:11
made us focus on these two digits
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nos fez focar os dois dígitos, e só.
03:13
and them alone.
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03:15
In an effort to simplify the message
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Para simplificar a mensagem
03:17
and draw a beautiful,
inevitable red and blue map,
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e desenhar um mapa lindo, azul e vermelho,
03:21
we lost the point completely.
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perdemos o ponto completamente.
03:23
We somehow forgot
that there were stories --
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De alguma forma, nos esquecemos
que haviam histórias
03:25
stories of human beings
behind these numbers.
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de seres humanos por trás
daqueles números.
03:29
In a different context,
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Num contexto diferente,
mas para um ponto similar,
03:30
but to a very similar point,
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03:32
a peculiar challenge was presented
to my team by this woman.
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um desafio peculiar foi apresentado
para a minha equipe por esta mulher.
03:36
She came to us with a lot of data,
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Ela veio a nós com muitos dados,
03:38
but ultimately she wanted to tell
one of the most humane stories possible.
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mas por fim ela queria nos contar
uma das histórias mais humanas possíveis.
03:43
She's Samantha Cristoforetti.
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Ela é Samantha Crisforetti,
a primeira italiana astronauta,
03:45
She has been the first
Italian woman astronaut,
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que nos contactou antes de se lançar
03:47
and she contacted us before being launched
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03:50
on a six-month-long expedition
to the International Space Station.
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numa expedição de seis meses
para a Estação Espacial Internacional.
03:54
She told us, "I'm going to space,
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Ela nos disse: "Eu vou para o espaço,
03:56
and I want to do something meaningful
with the data of my mission
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e quero fazer algo significante
com os dados da minha missão
03:59
to reach out to people."
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para alcançar pessoas".
04:01
A mission to the
International Space Station
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Uma missão para a Estação
Espacial Internacional
04:04
comes with terabytes of data
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volta com terabytes de dados
sobre tudo o que podemos imaginar:
04:06
about anything you can possibly imagine --
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as órbitas ao redor da Terra,
a velocidade e a posição da EEI
04:08
the orbits around Earth,
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04:10
the speed and position of the ISS
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04:12
and all of the other thousands
of live streams from its sensors.
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e outras milhões de transmissões
diretas de seus sensores.
04:16
We had all of the hard data
we could think of --
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Tínhamos todos os dados imagináveis,
04:19
just like the pundits
before the election --
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assim como os especialistas
antes das eleições,
04:22
but what is the point
of all these numbers?
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mas qual a utilidade
de todos esses números?
04:25
People are not interested
in data for the sake of it,
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As pessoas não se interessam
nos dados em si,
04:27
because numbers are never the point.
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porque os números nunca são o propósito.
04:29
They're always the means to an end.
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São sempre o meio para um fim.
04:32
The story we needed to tell
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A história que tínhamos que contar
04:34
is that there is a human being
in a teeny box
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é que existe um ser humano
numa caixinha pequena
04:37
flying in space above your head,
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voando para o espaço
em cima das nossas cabeças,
04:39
and that you can actually see her
with your naked eye on a clear night.
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e que podemos vê-la a olhos nus
numa noite clara.
04:43
So we decided to use data
to create a connection
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Decidimos usar os dados
para criar uma conexão
04:46
between Samantha and all of the people
looking at her from below.
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entre Samantha e todas as pessoas
olhando para ela daqui debaixo.
04:50
We designed and developed
what we called "Friends in Space,"
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Criamos e desenvolvemos
o que chamamos de "Friends in Space",
04:53
a web application that simply
lets you say "hello" to Samantha
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um aplicativo que nos permite
dizer "oi" para a Samantha
04:58
from where you are,
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de onde estamos,
04:59
and "hello" to all the people
who are online at the same time
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e "oi" para o mundo todo,
on-line ao mesmo tempo.
05:03
from all over the world.
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05:05
And all of these "hellos"
left visible marks on the map
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Todos esses "ois" deixaram
marcas visíveis no mapa
05:09
as Samantha was flying by
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quando Samantha sobrevoava
05:11
and as she was actually
waving back every day at us
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e ela acenava para nós todos os dias
usando o Twitter na EEI.
05:14
using Twitter from the ISS.
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05:16
This made people see the mission's data
from a very different perspective.
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Assim, podíamos ver os dados da missão
de uma perspectiva bem diferente.
05:21
It all suddenly became much more
about our human nature and our curiosity,
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De repente, tudo se tratava mais
da natureza humana e de nossa curiosidade,
05:26
rather than technology.
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do que da tecnologia.
05:28
So data powered the experience,
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Assim os dados motivaram a experiência,
05:30
but stories of human beings
were the drive.
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mas as histórias de seres humanos
eram o ímpeto.
05:34
The very positive response
of its thousands of users
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As respostas positivas
de milhares de usuários
05:38
taught me a very important lesson --
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me ensinaram uma lição importante:
05:40
that working with data
means designing ways
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trabalhar com dados significa
criar caminhos
05:43
to transform the abstract
and the uncountable
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para transformar o abstrato e o incontável
05:45
into something that can be seen,
felt and directly reconnected
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em algo que pode ser visto,
sentido e reconectado diretamente
05:49
to our lives and to our behaviors,
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em nossas vidas e nosso comportamento,
05:52
something that is hard to achieve
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algo difícil de realizar
05:54
if we let the obsession for the numbers
and the technology around them
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se deixarmos a obsessão pelos números
e a tecnologia que os cerca
05:57
lead us in the process.
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conduzir o processo.
06:00
But we can do even more to connect data
to the stories they represent.
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Podemos fazer até mais para conectar
dados com as histórias que representam.
06:05
We can remove technology completely.
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Podemos remover a tecnologia por completo.
06:08
A few years ago, I met this other woman,
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Uns anos atrás, conheci outra mulher,
06:10
Stefanie Posavec --
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a Stefanie Posavec,
06:11
a London-based designer who shares with me
the passion and obsession about data.
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uma designer enraizada em Londres,
com a mesma paixão e obsessão
que eu tenho pelos dados.
06:17
We didn't know each other,
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Não nos conhecíamos, mas decidimos
fazer um experimento muito radical:
06:19
but we decided to run
a very radical experiment,
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06:22
starting a communication using only data,
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começar uma conversa usando somente dados,
06:24
no other language,
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e nenhuma outra linguagem,
06:26
and we opted for using no technology
whatsoever to share our data.
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e optamos por não usar nenhuma
tecnologia para compartilhar os dados.
06:30
In fact, our only means of communication
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Nosso único meio de comunicação
seria o bom e velho correio.
06:33
would be through
the old-fashioned post office.
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Para "Queridos Dados",
todas as semanas, por um ano,
06:36
For "Dear Data," every week for one year,
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06:39
we used our personal data
to get to know each other --
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usamos dados pessoais
para conhecermos uma a outra:
06:42
personal data around weekly
shared mundane topics,
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dados pessoais compartilhados
semanalmente sobre tópicos cotidianos,
06:46
from our feelings
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desde nossos sentimentos
a interações com nossos companheiros,
06:47
to the interactions with our partners,
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06:49
from the compliments we received
to the sounds of our surroundings.
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desde elogios que recebemos,
a sons ao nosso redor.
06:53
Personal information
that we would then manually hand draw
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Informações pessoais
que desenhamos manualmente
06:57
on a postcard-size sheet of paper
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numa folha do tamanho de um cartão postal
06:59
that we would every week
send from London to New York,
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que mandávamos semanalmente
de Londres a Nova Iorque,
07:02
where I live,
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onde eu moro,
07:03
and from New York to London,
where she lives.
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e de Nova Iorque a Londres, onde ela mora.
07:06
The front of the postcard
is the data drawing,
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Na frente do cartão postal ficava
o desenho dos dados,
07:10
and the back of the card
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e o verso do cartão continha
o endereço da outra pessoa, claro,
07:11
contains the address
of the other person, of course,
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e a legenda de como interpretar o desenho.
07:13
and the legend for how
to interpret our drawing.
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07:17
The very first week into the project,
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Na primeira semana do projeto,
07:19
we actually chose
a pretty cold and impersonal topic.
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nós escolhemos um tópico frio e impessoal.
07:22
How many times do we
check the time in a week?
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Quantas vezes olhamos
que horas eram na semana?
07:26
So here is the front of my card,
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Aqui está a frente do meu cartão,
e vemos todos os símbolos
07:28
and you can see that every little symbol
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que representam todas as vezes
que eu olhei as horas,
07:30
represents all of the times
that I checked the time,
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07:34
positioned for days
and different hours chronologically --
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marcando os dias e as horas,
cronologicamente,
07:37
nothing really complicated here.
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nada muito complicado.
07:40
But then you see in the legend
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Mas aí vemos na legenda
07:41
how I added anecdotal details
about these moments.
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como eu adicionei detalhes informais
sobre os momentos.
07:45
In fact, the different types of symbols
indicate why I was checking the time --
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De fato, os símbolos diferentes indicam
a razão de eu consultar as horas,
o que eu estava fazendo.
07:49
what was I doing?
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07:51
Was I bored? Was I hungry?
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Estava entediada? Com fome? Atrasada?
07:52
Was I late?
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07:54
Did I check it on purpose
or just casually glance at the clock?
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Consultei de propósito ou olhei
o relógio de relance casualmente?
07:57
And this is the key part --
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Esta parte é a chave:
07:59
representing the details
of my days and my personality
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representar os detalhes dos meus dias
e a minha personalidade
08:03
through my data collection.
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através da coleta de dados.
08:05
Using data as a lens or a filter
to discover and reveal, for example,
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Usar dados como uma lente ou filtro
para descobrir e revelar, por exemplo,
08:10
my never-ending anxiety for being late,
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a minha ansiedade contínua
de não me atrasar,
08:12
even though I'm absolutely always on time.
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2200
apesar de eu chegar sempre na hora.
08:16
Stefanie and I spent one year
collecting our data manually
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Stefanie e eu passamos um ano
coletando nossos dados manualmente
08:20
to force us to focus on the nuances
that computers cannot gather --
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para nos forçar a concentrar em nuances
que os computadores não recolhem,
08:24
or at least not yet --
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pelo menos, por enquanto,
08:26
using data also to explore our minds
and the words we use,
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usando dados para explorar nossas mentes
e as palavras que usamos,
08:29
and not only our activities.
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1936
e não só nossas atividades.
08:31
Like at week number three,
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1416
Na terceira semana,
08:33
where we tracked the "thank yous"
we said and were received,
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3816
monitoramos os "obrigados"
que dissemos e recebemos,
08:37
and when I realized that I thank
mostly people that I don't know.
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e então percebi que agradeço
principalmente às pessoas que não conheço.
08:41
Apparently I'm a compulsive thanker
to waitresses and waiters,
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4336
Aparentemente, sou uma agradecedora
compulsiva de garçons,
08:46
but I definitely don't thank enough
the people who are close to me.
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3160
mas não agradeço às pessoas
chegadas a mim o suficiente.
08:51
Over one year,
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Por um ano,
08:52
the process of actively noticing
and counting these types of actions
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o processo de ativamente
observar e computar nossas ações
08:56
became a ritual.
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se tornou um ritual, nos modificou.
08:58
It actually changed ourselves.
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09:00
We became much more
in tune with ourselves,
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2696
Nos tornamos mais ligadas a nós mesmas,
09:02
much more aware of our behaviors
and our surroundings.
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muito mais conscientes
do nosso comportamento e arredores.
09:06
Over one year, Stefanie and I
connected at a very deep level
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Por um ano, Stefanie e eu
nos conectamos de forma profunda
09:09
through our shared data diary,
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2016
pelos diários de dados que compartilhamos
09:11
but we could do this only because
we put ourselves in these numbers,
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mas só pudemos fazer isso porque
nos colocamos nos números,
09:16
adding the contexts
of our very personal stories to them.
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3976
inserindo os contextos
das nossas histórias a eles.
09:20
It was the only way
to make them truly meaningful
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2456
Foi a única forma de fazê-los
ter significado e nos representar.
09:22
and representative of ourselves.
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550520
2200
09:26
I am not asking you
to start drawing your personal data,
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Eu não estou lhes pedindo
para começar a escrever seus dados,
09:29
or to find a pen pal across the ocean.
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2856
ou achar um amigo de correspondência
do outro lado do oceano.
09:32
But I'm asking you to consider data --
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Mas estou lhes pedindo
para considerarem os dados,
09:35
all kind of data --
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1456
de todos os tipos,
09:36
as the beginning of the conversation
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1776
o começo de uma conversa e não o fim.
09:38
and not the end.
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1200
09:40
Because data alone
will never give us a solution.
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3176
Porque dados em si
nunca nos darão uma solução.
09:43
And this is why data failed us so badly --
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2696
É por isso que os dados falharam,
09:46
because we failed to include
the right amount of context
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3376
porque nós falhamos em incluir
a quantia certa de contexto
09:49
to represent reality --
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1456
que representasse a realidade,
09:50
a nuanced, complicated
and intricate reality.
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3200
uma realidade com nuances e complicada.
09:54
We kept looking at these two numbers,
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2456
Ficamos olhando para os números,
09:57
obsessing with them
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1496
obcecados por eles
09:58
and pretending that our world
could be reduced
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2496
e fingindo que o mundo
pudesse ser reduzido
10:01
to a couple digits and a horse race,
208
589480
2336
a um par de dígitos
e uma corrida de cavalos,
10:03
while the real stories,
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591840
1256
enquanto que histórias reais,
as que realmente importam,
10:05
the ones that really mattered,
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1456
10:06
were somewhere else.
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594600
1416
estavam em outro lugar.
10:08
What we missed looking at these stories
only through models and algorithms
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596040
4416
O que não vimos ao olhar nessas histórias
por modelos e algoritmos
10:12
is what I call "data humanism."
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2520
é o que chamo de "humanismo dos dados".
10:15
In the Renaissance humanism,
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2016
No humanismo da renascença,
intelectuais europeus trouxeram
10:17
European intellectuals
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1616
10:19
placed the human nature instead of God
at the center of their view of the world.
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4920
a natureza humana em vez de Deus
no centro da sua visão do mundo.
10:24
I believe something similar
needs to happen
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2216
Eu acredito que algo parecido
precisa acontecer
10:27
with the universe of data.
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1776
com o o universo dos dados.
10:28
Now data are apparently
treated like a God --
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2976
Agora, dados são tratados como deuses,
10:31
keeper of infallible truth
for our present and our future.
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3280
guardiões da verdade infalível
do nosso presente e futuro.
10:35
The experiences
that I shared with you today
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2896
As experiências que eu compartilhei hoje
10:38
taught me that to make data faithfully
representative of our human nature
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5016
me ensinaram que,
para que os dados representem
nossa natureza humana fielmente
e não nos enganem de novo,
10:43
and to make sure they will not
mislead us anymore,
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631800
3416
10:47
we need to start designing ways
to include empathy, imperfection
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3696
precisamos começar a criar formas
de incluir empatia, imperfeição
10:50
and human qualities
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1576
e qualidades humanas
10:52
in how we collect, process,
analyze and display them.
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3720
na forma de coletar, processar,
analisar e demonstrar os dados.
10:57
I do see a place where, ultimately,
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2976
Eu imagino um lugar onde, por fim,
11:00
instead of using data
only to become more efficient,
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3336
ao invés de usar dados
só para sermos mais eficientes,
11:03
we will all use data
to become more humane.
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2800
usaremos os dados
para nos tornarmos mais humanos.
11:06
Thank you.
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Obrigada.
11:08
(Applause)
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(Aplausos)
Translated by Denise Pelusch
Reviewed by Maricene Crus

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ABOUT THE SPEAKER
Giorgia Lupi - Information designer
Giorgia Lupi sees beauty in data. She challenges the impersonality that data communicate, designing engaging visual narratives that re-connect numbers to what they stand for: stories, people, ideas.

Why you should listen

What sets Giorgia Lupi apart is her humanistic approach to the world of data.

Her work frequently crosses the divide between digital, print and handcrafted representations of information: primarily, she draws with data. She has a passion for and obsession with data, the material she uses to tell stories, and the lens through which she sees the world.

Data are often considered to be very impersonal, boring and clinical, but Lupi's work proves the opposite. She makes sense of data with a curious mind and a heterogeneous arsenal, which ranges from digital technology to exhausting and repetitive manual labor. She believes we will ultimately unlock the full potential of data only when we embrace their nature, and make them part of our lives, which will inevitably make data more human in the process.

Trained as an architect, Lupi has always been driven by opposing forces: analysis and intuition, logic and beauty, numbers and images. True to these dichotomies, in 2011 she started both her own company and studying for a PhD. She earned her ddoctorate in design at Politecnico di Milano, where she focused on information mapping, and she is now the design director and co-founder of Accurat, a global, data-driven research, design and innovation firm with offices in Milan and New York. She relocated from Italy to New York City, where she now lives.

Thanks to her work and research, Giorgia is a prominent voice in the world of data. She has spoken at numerous events, universities and institutions around the world, including the Museum of Modern Art, the Guggenheim Museum, PopTech Conference, Eyeo Festival, Fast Company Innovation by Design, New York University, Columbia University and the New York Public Library. She has been featured in major international outlets such as the New York Times, The Guardian, the Washington Post, NPR, BBC, TIME magazine, National Geographic, Scientific American, Popular Science, Wired, Vogue, Vanity Fair, Monocle and more. Her work has been exhibited at the Design Museum, the Science Museum, and Somerset House in London; the New York Hall of Science and the Storefront for Art and Architecture in New York; at the Triennale Design Museum and the Design Week in Milan, among others.

With her company, Accurat, she has worked with major international clients including IBM, Google, Microsoft, the United Nations, the World Health Organization, the World Economic Forum, the European Union, the Louis Vuitton-Moet-Hennessy Group, Fiat Chrysler Automobiles, J.P. Morgan Asset Management, Unicredit Group and KPMG Advisory.

Giorgia is the co-author of Dear Data, an aspirational hand-drawn data visualization book that explores the more slippery details of daily life through data, revealing the patterns that inform our decisions and affect our relationships.

Her work is part of the permanent collection of the Museum of Modern Art.

More profile about the speaker
Giorgia Lupi | Speaker | TED.com