TEDxCaFoscariU
Frederic Kaplan: How to build an information time machine
Frederik Kaplan (Frederic Kaplan): Kako sam sagradio informacijski vremeplov
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Zamislite da možete da surfujete po Fejzbuku... Srednjeg veka. Možda to i nije toliko daleko koliko zvuči. U zabavnom i zanimljivom govoru, istraživač i inženjer Frederik Kaplan prikazuje Venecijanski vremeplov, projekat kojim se digitalizuje 80 km knjiga u cilju stvaranja istorijske i geografske simulacije života u Veneciji tokom 1000 godina. (Snimljeno na TEDxCaFoscariU.)
Frederic Kaplan - Digital humanities researcher
Frederic Kaplan seeks to digitize vast archives of historical information to make maps that move -- through time. Full bio
Frederic Kaplan seeks to digitize vast archives of historical information to make maps that move -- through time. Full bio
Double-click the English transcript below to play the video.
00:12
This is an image of the planet Earth.
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Ovo je slika planete Zemlje.
00:15
It looks very much like the Apollo pictures
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Veoma podseća na poznate
00:18
that are very well known.
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slike zemlje iz Apola.
00:19
There is something different;
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Postoji razlika -
00:21
you can click on it,
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možete da kliknete na nju,
00:23
and if you click on it,
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i ako to učinite,
00:24
you can zoom in on almost any place on the Earth.
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možete da uvećate skoro svako
mesto na Zemlji.
mesto na Zemlji.
00:27
For instance, this is a bird's-eye view
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Na primer, ovo je pogled
iz ptičje perspektive
iz ptičje perspektive
00:29
of the EPFL campus.
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kampusa Švajcarskog federalnog
tehničkog instituta u Lozani (EPFL).
tehničkog instituta u Lozani (EPFL).
00:32
In many cases, you can also see
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U mnogim slučajevima,
možete da vidite
možete da vidite
00:34
how a building looks from a nearby street.
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i kako neka zgrada izgleda
iz obližnje ulice.
iz obližnje ulice.
00:38
This is pretty amazing.
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Prilično je zapanjujuće.
00:39
But there's something missing in this wonderful tour:
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Nešto nedostaje u ovom
čudesnom obilasku:
čudesnom obilasku:
00:43
It's time.
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vreme.
00:45
i'm not really sure when this picture was taken.
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Nisam baš siguran kada je
ova slika uslikana.
ova slika uslikana.
00:48
I'm not even sure it was taken
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Nisam čak siguran
ni da li je uslikana
ni da li je uslikana
00:49
at the same moment as the bird's-eye view.
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u istom trenutku kao i
onaj prikaz iz ptičije perspektive.
onaj prikaz iz ptičije perspektive.
00:55
In my lab, we develop tools
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U mojoj laboratoriji, razvili smo alate
00:57
to travel not only in space
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za putovanje ne samo kroz prostor
00:59
but also through time.
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nego i vreme.
01:02
The kind of question we're asking is
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Pitanje koje postavljamo je:
01:04
Is it possible to build something
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da li je moguće napraviti nešto
01:05
like Google Maps of the past?
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poput Guglovih mapa prošlosti?
01:07
Can I add a slider on top of Google Maps
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Mogu li da dodam slajder
iznad Guglovih mapa
iznad Guglovih mapa
01:11
and just change the year,
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i samo promenim godinu
01:12
seeing how it was 100 years before,
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kako bih video kako je bilo pre 100
01:14
1,000 years before?
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ili 1000 godina?
01:16
Is that possible?
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Da li je to moguće?
01:18
Can I reconstruct social networks of the past?
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Mogu li da rekonstruišem
društvene mreže prošlosti?
društvene mreže prošlosti?
01:20
Can I make a Facebook of the Middle Ages?
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Mogu li da napravim
Fejzbuk srednjeg veka?
Fejzbuk srednjeg veka?
01:23
So, can I build time machines?
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Mogu li da napravim vremeplov?
01:27
Maybe we can just say, "No, it's not possible."
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Moglo bi se reći da je to nemoguće.
01:30
Or, maybe, we can think of it from an information point of view.
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Ili, možda, možemo to sagledati
sa informatičke tačke gledišta.
sa informatičke tačke gledišta.
01:33
This is what I call the information mushroom.
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Ovo ja nazivam informatičkom pečurkom.
01:37
Vertically, you have the time.
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Vertikalno je vreme
01:38
and horizontally, the amount of digital information available.
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a horizontalno količina
dostupnih informacija.
dostupnih informacija.
01:41
Obviously, in the last 10 years, we have much information.
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Očito je u poslednjih 10 godina
puno informacija.
puno informacija.
01:44
And obviously the more we go in the past, the less information we have.
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I što dalje idemo u prošlost
to je informacija manje.
to je informacija manje.
01:48
If we want to build something like Google Maps of the past,
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Ako bi se pravilo nešto
poput Guglovih mapa
poput Guglovih mapa
01:50
or Facebook of the past,
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ili Fejzbuka prošlosti,
01:52
we need to enlarge this space,
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taj prostor bi trebalo povećati,
01:53
we need to make that like a rectangle.
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napraviti nešto poput četvorougla.
01:55
How do we do that?
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Kako to uraditi?
01:57
One way is digitization.
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Jedan od načina je digitalizacija.
01:59
There's a lot of material available --
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Postoji mnogo dostupnih materijala -
02:01
newspaper, printed books, thousands of printed books.
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novine, štampane knjige,
hiljade štampanih knjiga.
hiljade štampanih knjiga.
02:07
I can digitize all these.
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Sve ih mogu digitalizovati.
02:09
I can extract information from these.
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Mogu izvući informacije iz svega.
02:11
Of course, the more you go in the past,
the less information you will have.
the less information you will have.
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Naravno, što se više ide u prošlost,
manje će biti informacija.
manje će biti informacija.
02:15
So, it might not be enough.
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Možda ih ne bude dovoljno.
02:18
So, I can do what historians do.
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Mogu probati ono što istoričari rade.
02:20
I can extrapolate.
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Mogu da pretpostavim nešto.
02:22
This is what we call, in computer science, simulation.
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To se u informatici zove simulacija.
02:26
If I take a log book,
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Ako uzmem neki dnevnik,
02:28
I can consider, it's not just a log book
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mogao bih pomisliti da to nije samo dnevnik
02:30
of a Venetian captain going to a particular journey.
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venecijanskog kapetana koji je
na konkretnom putovanju.
na konkretnom putovanju.
02:33
I can consider it is actually a log book
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Mogao bih pomisliti da je to reprezentativni
02:35
which is representative of
many journeys of that period.
many journeys of that period.
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dnevnik brojnih putovanja tog vremena.
02:37
I'm extrapolating.
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Ja to pretpostavljam.
02:40
If I have a painting of a facade,
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Ako imam sliku fasade
02:42
I can consider it's not just that particular building,
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mogao bih pomisliti da to nije
samo određena zgrada,
samo određena zgrada,
02:44
but probably it also shares the same grammar
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već verovatno takođe deli iste osobine
02:48
of buildings where we lost any information.
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zgrada o kojima smo izgubili
mnoge informacije.
mnoge informacije.
02:52
So if we want to construct a time machine,
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Ako bismo hteli
da napravimo vremeplov,
da napravimo vremeplov,
02:55
we need two things.
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potrebne su dve stvari.
02:57
We need very large archives,
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Potrebne su nam velike arhive
02:59
and we need excellent specialists.
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i vrsni stručnjaci.
03:02
The Venice Time Machine,
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Venecijanski vremeplov,
03:03
the project I'm going to talk to you about,
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projekat o kojem ću vam govoriti,
03:05
is a joint project between the EPFL
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zajednički je projekat EPFL-a
03:08
and the University of Venice Ca'Foscari.
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i Venecijanskog univerziteta Ka'Foskari.
03:11
There's something very peculiar about Venice,
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Venecija je posebna po tome što
03:13
that its administration has been
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je njena administracija
03:16
very, very bureaucratic.
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vrlo, vrlo ažurna.
03:18
They've been keeping track of everything,
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Beleženo je sve,
03:20
almost like Google today.
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skoro kao što to Gugl danas radi.
03:23
At the Archivio di Stato,
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U Državnom arhivu
03:25
you have 80 kilometers of archives
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postoji 80 km dokumenata
03:27
documenting every aspect
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koji beleže svaki aspekt
03:29
of the life of Venice over
more than 1,000 years.
more than 1,000 years.
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života u Veneciji tokom
više od 1000 godina.
više od 1000 godina.
03:31
You have every boat that goes out,
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Svaki brod koji isplovi,
03:33
every boat that comes in.
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svaki brod koji uplovi.
03:34
You have every change that was made in the city.
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Svaka promena koja se desi gradu.
03:37
This is all there.
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Sve je tamo.
03:40
We are setting up a 10-year digitization program
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Odredili smo 10 godina
za program digitalizacije,
za program digitalizacije,
03:44
which has the objective of transforming
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čiji je cilj pretvaranje
03:46
this immense archive
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tog džinovskog arhiva
03:47
into a giant information system.
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u ogroman informacijski sistem.
03:49
The type of objective we want to reach
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Cilj koji želimo da postignemo
03:51
is 450 books a day that can be digitized.
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je da se svakog dana
digitalizuje 450 knjiga.
digitalizuje 450 knjiga.
03:56
Of course, when you digitize, that's not enough,
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Naravno, to nije dovoljno,
03:58
because these documents,
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jer je većina tih dokumenata
04:00
most of them are in Latin, in Tuscan,
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na latinskom, toskanskom
04:02
in Venetian dialect,
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ili venecijanskom dijalektu,
04:04
so you need to transcribe them,
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tako da ih treba prepisati,
04:05
to translate them in some cases,
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u nekim slučajevima i prevesti,
04:07
to index them,
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indeksirati,
04:08
and this is obviously not easy.
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što očigledno nije lako.
04:10
In particular, traditional optical
character recognition method
character recognition method
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Konkretno, tradicionalna metoda
optičkog prepoznavanja znakova
optičkog prepoznavanja znakova
04:14
that can be used for printed manuscripts,
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koja se koristi za štampana dokumenta,
04:16
they do not work well on the handwritten document.
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nije upotrebljiva na rukopisima.
04:20
So the solution is actually to take inspiration
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Inspiracija za rešenje
tog problema može se
tog problema može se
04:22
from another domain: speech recognition.
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naći u drugoj oblasti:
prepoznavanje govora.
prepoznavanje govora.
04:25
This is a domain of something
that seems impossible,
that seems impossible,
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To je oblast koja se čini nemogućom,
04:27
which can actually be done,
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ali je zapravo moguća
04:29
simply by putting additional constraints.
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ako se dodatno ograniči.
04:31
If you have a very good model
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Ako postoji vrlo dobar model
04:33
of a language which is used,
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nekog jezika,
04:35
if you have a very good model of a document,
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ako postoji vrlo dobar
model nekog dokumenta,
model nekog dokumenta,
04:37
how well they are structured.
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dobro strukturiranog.
04:38
And these are administrative documents.
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Ti dokumenti su administrativne prirode.
04:39
They are well structured in many cases.
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U većini slučajeva
su dobro strukturirani.
su dobro strukturirani.
04:42
If you divide this huge archive into smaller subsets
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Ako se ogroman arhiv
podeli na manje delove,
podeli na manje delove,
04:45
where a smaller subset
actually shares similar features,
actually shares similar features,
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od kojih svaki ima slične osobine,
04:48
then there's a chance of success.
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onda se može uspeti.
04:54
If we reach that stage, then there's something else:
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Ako se dođe do te faze,
pojavi se sledeća stvar:
pojavi se sledeća stvar:
04:57
we can extract from this document events.
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iz takvih dokumenata
mogu se izvući događaji.
mogu se izvući događaji.
05:00
Actually probably 10 billion events
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U stvari, verovatno 10 milijardi događaja
05:03
can be extracted from this archive.
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se može izvući iz arhiva.
05:04
And this giant information system
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Taj ogromni informacijski sistem
05:06
can be searched in many ways.
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se može na razne načine pretražiti.
05:08
You can ask questions like,
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Mogu se postaviti razna pitanja:
05:09
"Who lived in this palazzo in 1323?"
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„Ko je u ovoj palati
živeo 1323. godine?“
živeo 1323. godine?“
05:12
"How much cost a sea bream at the Realto market
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„Koliko su ljuskavke koštale
05:14
in 1434?"
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na pijaci kod mosta Rialto
1434. godine?“
1434. godine?“
05:16
"What was the salary
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„Kolika je bila plata
05:18
of a glass maker in Murano
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staklara u Muranu
05:20
maybe over a decade?"
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tokom jedne decenije?“
05:21
You can ask even bigger questions
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Mogla bi se postaviti i važnija pitanja
jer bi bila semantički kodirana.
jer bi bila semantički kodirana.
05:22
because it will be semantically coded.
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05:25
And then what you can do is put that in space,
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To se potom može staviti u prostor,
05:27
because much of this information is spatial.
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jer je većina tih informacija prostorna.
05:29
And from that, you can do things like
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Iz tog prikaza moglo bi se
05:31
reconstructing this extraordinary journey
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rekonstruisati čudesno putovanje
05:33
of that city that managed to
have a sustainable development
have a sustainable development
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tog grada koji je uspeo da održi svoj razvoj
05:37
over a thousand years,
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preko hiljadu godina,
05:39
managing to have all the time
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uspevši da sve vreme
05:41
a form of equilibrium with its environment.
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bude u ravnoteži sa svojim okruženjem.
05:43
You can reconstruct that journey,
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To putovanje se može rekonstruisati,
05:45
visualize it in many different ways.
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vizualizovati na različite načine.
05:48
But of course, you cannot understand
Venice if you just look at the city.
Venice if you just look at the city.
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Naravno, Venecija se ne može razumeti
ako se samo baci pogled na grad.
ako se samo baci pogled na grad.
05:50
You have to put it in a larger European context.
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Ona se mora staviti u mnogo širi
evropski kontekst.
evropski kontekst.
05:53
So the idea is also to document all the things
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Dakle, treba da se dokumentuju sve stvari
05:56
that worked at the European level.
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na evropskom nivou.
05:58
We can reconstruct also the journey
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Moglo bi se rekonstruisati putovanje
06:00
of the Venetian maritime empire,
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venecijanske pomorske imperije,
06:02
how it progressively controlled the Adriatic Sea,
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kako je u kontinuitetu
kontrolisala Jadransko more,
kontrolisala Jadransko more,
06:05
how it became the most powerful medieval empire
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kako je postala najmoćnija
srednjovekovna imperija
srednjovekovna imperija
06:09
of its time,
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svog vremena,
06:10
controlling most of the sea routes
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koja je kontrolisala
većinu morskih puteva
većinu morskih puteva
06:13
from the east to the south.
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od istoka do juga.
06:17
But you can even do other things,
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Moglo bi se još nešto uraditi,
06:19
because in these maritime routes,
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jer na tim morskim putevima
06:21
there are regular patterns.
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postoje ustaljeni šabloni.
06:23
You can go one step beyond
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Moglo bi se otići korak dalje
06:26
and actually create a simulation system,
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i stvoriti simulacioni sistem,
06:28
create a Mediterranean simulator
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Sredozemni simulator,
06:31
which is capable actually of reconstructing
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koji bi rekonstruisao
06:33
even the information we are missing,
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čak i informacije koje nedostaju.
06:36
which would enable us to have
questions you could ask
questions you could ask
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To bi nam omogućilo da saznamo
06:39
like if you were using a route planner.
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da li se koristio plan puta.
06:42
"If I am in Corfu in June 1323
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„Ako sam na Krfu 1323. godine
06:45
and want to go to Constantinople,
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i ako bih hteo da idem do Carigrada,
06:47
where can I take a boat?"
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gde bih mogao da se ukrcam na brod?“
06:49
Probably we can answer this question
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Odgovor na ovo pitanje bismo verovatno
06:51
with one or two or three days' precision.
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dobili s preciznošću od oko dva do tri dana.
06:55
"How much will it cost?"
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„Koliko bi to koštalo?“
06:57
"What are the chance of encountering pirates?"
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„Hoćemo li sresti pirate?“
07:00
Of course, you understand,
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Shvatate da je
07:02
the central scientific challenge
of a project like this one
of a project like this one
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ključni naučni izazov ovakvog projekta
07:05
is qualifying, quantifying and representing
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to što se na svakom koraku
javlja nepouzdanost
javlja nepouzdanost
07:09
uncertainty and inconsistency
at each step of this process.
at each step of this process.
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i protivrečnost u određivanju i
predstavljanju podataka.
predstavljanju podataka.
07:12
There are errors everywhere,
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Svuda ima grešaka:
07:15
errors in the document, it's
the wrong name of the captain,
the wrong name of the captain,
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u dokumentima, pogrešno ime kapetana,
07:17
some of the boats never actually took to sea.
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neki brodovi zapravo
nikad nisu zaplovili, itd.
nikad nisu zaplovili, itd.
07:20
There are errors in translation, interpretative biases,
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Grešaka ima u prevodu,
prevodioci mogu biti pristrasni,
prevodioci mogu biti pristrasni,
07:25
and on top of that, if you add algorithmic processes,
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i povrh svega, ako se dodaju algoritmi,
07:29
you're going to have errors in recognition,
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greške će se javiti u prepoznavanju
07:32
errors in extraction,
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i izvođenju,
07:34
so you have very, very uncertain data.
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tako da se dobiju vrlo nepouzdani podaci.
07:38
So how can we detect and
correct these inconsistencies?
correct these inconsistencies?
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Kako onda da uočimo
i ispravimo te protivrečnosti?
i ispravimo te protivrečnosti?
07:42
How can we represent that form of uncertainty?
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Kako da predstavimo nešto nepouzdano?
07:45
It's difficult. One thing you can do
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Teško.
Mogao bi se, npr.
Mogao bi se, npr.
07:47
is document each step of the process,
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zabeležiti svaki korak u tom procesu,
07:50
not only coding the historical information
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ne samo kodiranje istorijskih podataka,
07:52
but what we call the meta-historical information,
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nego i ono što nazivamo
meta-istorijskim podacima,
meta-istorijskim podacima,
07:55
how is historical knowledge constructed,
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kako se konstruišu istorijski podaci,
07:58
documenting each step.
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beleženjem svakog koraka.
08:00
That will not guarantee that we actually converge
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To ne garantuje da ćemo dobiti
08:01
toward a single story of Venice,
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jednu jedinu priču o Veneciji,
08:04
but probably we can actually reconstruct
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ali verovatno ćemo rekonstruisati
08:06
a fully documented potential story of Venice.
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u potpunosti dokumentovanu
potencijalnu priču o Veneciji.
potencijalnu priču o Veneciji.
08:09
Maybe there's not a single map.
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Možda neće postojati samo jedna mapa.
08:10
Maybe there are several maps.
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Nego nekoliko.
08:12
The system should allow for that,
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Sistem bi to trebalo da dozvoli,
08:15
because we have to deal with
a new form of uncertainty,
a new form of uncertainty,
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zbog novih nepouzdanosti,
08:17
which is really new for this type of giant databases.
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što je novina u takvim
ogromnim bazama podataka.
ogromnim bazama podataka.
08:22
And how should we communicate
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A kako da to novo istraživanje
08:24
this new research to a large audience?
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predstavimo široj javnosti?
08:28
Again, Venice is extraordinary for that.
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Venecija je izvanredna upravo zbog toga
08:31
With the millions of visitors that come every year,
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što se milioni posetilaca
u njoj sjate svake godine,
u njoj sjate svake godine,
08:33
it's actually one of the best places
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te je ona najbolje mesto
08:35
to try to invent the museum of the future.
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da se stvori takav muzej budućnosti.
08:38
Imagine, horizontally you see the reconstructed map
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Zamislite da horizontalno
vidite rekonstruisanu mapu
vidite rekonstruisanu mapu
08:41
of a given year,
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određene godine,
08:42
and vertically, you see the document
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a vertikalno dokument po kome
08:45
that served the reconstruction,
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se rekonstruisalo,
08:47
paintings, for instance.
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na primer, slike.
08:50
Imagine an immersive system that permits
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Zamislite sistem u koji biste
08:53
to go and dive and reconstruct
the Venice of a given year,
the Venice of a given year,
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zaronili i rekonstruisali
Veneciju iz neke godine,
Veneciju iz neke godine,
08:56
some experience you could share within a group.
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i da to iskustvo podelite s ostalima.
08:59
On the contrary, imagine actually that you start
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S druge strane, zamislite da krenete
09:01
from a document, a Venetian manuscript,
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od dokumenta, nekog
venecijanskog rukopisa,
venecijanskog rukopisa,
09:04
and you show, actually, what
you can construct out of it,
you can construct out of it,
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i da pokažete šta se
iz njega može napraviti,
iz njega može napraviti,
09:07
how it is decoded,
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kako se dekodira,
09:08
how the context of that document can be recreated.
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kako se oko njega stvori kontekst.
09:11
This is an image from an exhibit
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Ovo je slika s jedne izložbe
09:13
which is currently conducted in Geneva
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koja je upravo izložena u Ženevi
09:15
with that type of system.
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s upravo takvim sistemom.
09:17
So to conclude, we can say that
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Naposletku bih hteo da kažem
09:19
research in the humanities is about to undergo
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da će istraživanje u društvenim naukama
09:23
an evolution which is maybe similar
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evoluirati, isto kao što je
09:24
to what happened to life sciences 30 years ago.
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i u prirodnim naukama pre 30 godina.
09:29
It's really a question of scale.
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Radi se samo o obimu.
09:34
We see projects which are
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Stvorićemo projekte koji nadmašuju
09:37
much beyond any single research team can do,
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mogućnosti pojedinačnih istraživača,
09:41
and this is really new for the humanities,
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što je novina u društvenim naukama
09:43
which very often take the habit of working
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u kojima se obično radi
09:47
in small groups or only with a couple of researchers.
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u malim grupama
od po samo par istraživača.
od po samo par istraživača.
09:51
When you visit the Archivio di Stato,
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Kada posetite Državni arhiv
09:53
you feel this is beyond what any single team can do,
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vidite da to ne može
da uradi jedan tim,
da uradi jedan tim,
09:56
and that should be a joint and common effort.
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da je za to potreban zajednički napor.
10:00
So what we must do for this paradigm shift
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Takva paradigma treba da se preokrene
10:03
is actually foster a new generation
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i odgaji novu generaciju
10:05
of "digital humanists"
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„digitalnih humanista“
10:06
that are going to be ready for this shift.
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koji će biti spremni za taj obrt.
10:08
I thank you very much.
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Hvala.
10:10
(Applause)
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(Aplauz)
ABOUT THE SPEAKER
Frederic Kaplan - Digital humanities researcherFrederic Kaplan seeks to digitize vast archives of historical information to make maps that move -- through time.
Why you should listen
Frederic Kaplan is the Digital Humanities Chair at Ecole Polytechnique Federale de Lausanne (EPFL) and the EPFL's Digital Humanities Lab Director. Kaplan leads the lab in applying computation to humanities research. His latest project is the Venice Time Machine, a collaborative work archiving 80 kilometers of books from throughout 1000 years of Venetician history. The goal of the time machine is to create an information system which can be searched and mapped. Think of it as a Google Maps for time.
Kaplan holds a PhD in artificial intelligence from the University Paris VI. He lives in Switzerland.
Frederic Kaplan | Speaker | TED.com