Christian Huemer studied art
history at the University
of Vienna,
the Sorbonne in Paris,
and the Graduate Center in CUNY.
The focus of his scholarship
has been the history of art
markets,
central European modernism,
and more recently,
digital humanities.
After curatorial internships
at the Guggenheim Museum
and the Museum of Modern Art
in New York,
he spent several years
as an independent author,
a curator, and an educator,
including a position
in administration
at the Belvedere in Vienna.
The many exhibitions
and publications in which he has
been involved include topics
ranging from Klimt, Boeckl,
Charles Sedelmeyer, Courbet
in Vienna, impressionism,
the art market in Vienna,
and modernism.
His book on the World Heritage
Site Salzkammergut in Austria
was published in 2006.
Since 2008, Huemer has been
the head of the Project
for the Study of Collecting
and Provenance
at the Getty Research Institute.
With his position at the GRI,
he has been involved
with several international
research projects,
and I mention just two,
German Sales, 1930 to 1945:
Art Works, Art Markets,
and Cultural Policies,
a book which is in press now,
I understand,
called Market and Might:
The Business of Art in the Third
Reich.
The other project is the Rise
of the London Art Market:
British Sales, 1780 to 1800.
And this will be seen in a book
form, also forthcoming, called
London and the Emergence
of the European Art Market.
He works in collaboration
with leaders in the field
of digital humanities,
concerned with exploring how
larger data
sets from the Provenance Index
can be used to visualize
relationships, patterns,
and trends.
Christian.
[APPLAUSE]
Thank you, Therese,
for this kind invitation.
Thanks also to all
the organizers
of this conference for inviting
me.
I should basically say that I'm
not talking about a completely
new project.
Some of it is actually quite
old.
But what we tried
with this project
that I will explain in a second
is basically using old data
in a new and hopefully
innovative way.
Krzysztof Pomian once noted,
and it still holds for art
markets studies done
within the discipline of art
history
today, that quote,
"The gaze of the historian
is directed
towards extraordinary events.
Historians resemble collectors.
Both gather only
rare and curious objects,
disregarding whatever looked
banal, everyday, normal.
History is
an idiographic discipline,
having as its object
that which does not repeat
itself."
Quote end.
There could hardly be anything
more banal, everyday,
and repetitive
than the average business
operations of an auction house
or an art gallery.
Although reception studies have
shifted the attention
from the heroic artistic
producer to the sometimes even
anonymous consumer of art,
the great majority of studies
nevertheless focuses
on exceptional events
and masterpieces.
Over the last two decades,
we have seen an increasing
number of monographic essays
on agents mediating
between both sides.
Yet
all through the 19th century,
rhetoric of the artist
as a heroic individual
has simply been carried over
to case studies
on unconventional collectors
and dealers.
This is not to point fingers,
of course.
That's what we can do
and what art historians have
been trained to do.
The digital humanities, however,
propose a different approach
that is often characterized
as distant reading,
using large amounts
of information
for the analysis of patronage
trends.
Attempts to introduce
quantitative methods
into the study of historical art
markets and cultural consumption
have often been hampered
by the lack of suitable data.
So what I would like to suggest
today is using a database that
has been out there for decades
in a slightly different way.
I'm talking about the Getty
Provenance Index.
And I show you here, actually,
the landing page
where you can access the data
that we provide.
The Getty Provenance Index
is actually a collection
of databases offering
free online access to source
material for research
on the history of collecting
and art markets and, obviously,
also provenance research.
This truly unique data set
currently contains 1.5 million
records transcribed from widely
dispersed source documents,
such as archival inventories,
sale catalogs, and dealer stock
books.
A pioneering project
in the digital humanities,
the Provenance Index
was created more than 30 years
ago.
And in an arena where projects
appear and disappear almost
overnight, this groundbreaking
initiative has maintained
its relevance and viability
for decades.
This slide just shows you
the different types of source
material that we provide access
to and also how much of it
you may find in there.
So overall, it's about 1.5
million database records.
You have archival inventories.
These are mostly
Dutch and Italian inventories
from the 17th and 18th century.
The biggest pile by now
is auction catalogs, sales
catalogs, also focused very much
on 18th and early 19th century.
We have recently added
and continue to work
with the National Gallery
in London
on 18th-century British sales
material.
And a very big chunk
was recently added a year ago
from a collaboration with about
36 institutions in Germany,
Austria, and Switzerland
to capture all preserved auction
catalogs of the Nazi era
of basically 1930 to '45.
Currently, we are also trying
to beef up this dealer stock
books pile.
The Getty Research Institute has
recently acquired the Knoedler
Gallery archive,
and we are in the process
of transcribing the stock books.
Parts of them are already
online.
So this data pool is really
kind of developed and expanded
constantly.
Of course, if you deal with such
an old database, old and new
in the same sense,
you have some legacy issues,
and you always carry the history
with you.
I mean, in the first place,
it's great that it is so old
because that's why it is so big.
On the other side,
decisions that have been made
decades ago are, of course,
still reflected in the data
architecture, in the data model,
and so on.
So the initiative really goes
back even into the '70s when
a curator from the Paintings
Department, Burton Fredericksen,
decided to do two indices,
one on Italian paintings
found in 19th century
British auction catalogs
and an index to paintings
in American and British museums.
So he was, as a paintings
curator, obviously interested
in paintings.
And it really came out
of the museum initially,
and it was published in book
publications, not online
of course.
In the '80s, it became known
as the Getty Provenance Index.
And in '85, it was moved out
of the museum
to an institute that was back
then called the Art History
Information Program.
I think quite
innovative in the sense
that people tried to bring
together computer sciences
and art history
already in the '80s.
Then very early on, also, these
indices were computerized
in the mid-'80s.
And then it became clear that
you cannot develop this database
alone, not even with
the resources of the Getty.
You have to form partnership,
international collaborations,
to build up the data pool.
And this was really forced
or increased since the '90s.
And you see
in the mid-'90s, published
a data CD-ROM.
And since 1996 all the data
is online.
In 2004, there was a relaunch
because the idea was basically
that the data should not
be produced
without a scholarly context.
So every database project
to this day has a research
project with it that kind
of leads to programming
and traditional--
or rather traditional book
publications.
And I should add, the future
here is to completely rethink,
redesign, and remodel
the Provenance Index.
I have no idea when that will be
finished, but we are tackling
it.
I should bring you one example
that is kind of striking--
and some of you
may have seen it-- what
the Provenance Index was
originally designed for.
This is a painting by Rubens
that is today in the J. Paul
Getty Museum.
It was acquired
in the early 1990s
at an auction, and the auction
catalog on the right side
actually did only know
the provenance back
to the mid-19th century.
So what one could then obviously
try is to do some research
in the Provenance Index.
And here, luckily,
is another interesting piece
of information--
on the face of the painting
the number 146.
And one could assume that this
is a kind of inventory number
or something.
So it's always worth a try.
You go to Search Inventories,
Descriptions.
You type in what you know.
You know Rubens, and you assume
this is an inventory number.
And so luckily, in this case,
there was only one record
in the database where Rubens
and this number 146 matched up.
And so it came
from a Spanish inventory that
was entered input earlier,
preserved in Madrid.
But through this, one
of the earliest owners was
actually found,
which was this Marques
of Carpio, who also was actually
ambassador of Rome--
Spanish ambassador in Rome
for a while.
So this type of research
is basically what the Provenance
Index was created for--
establishing the chain
of ownership
for major masterpieces
possibly in museum's
collections.
And in the Provenance Index,
you can also then actually get
the full provenance as it is
known so far for this picture.
But the idea, then, came up
that possibly this big data set
could be used for something
else, while it is cool, really,
to get such a website.
And of course, the bigger
the data pool, the more likely
it is that you make discoveries
like the Rubens example.
But does this really transform
the way we do art history?
Of course, I mean, we can do it
from home, armchair art
historians, your choice.
You don't have to run
through archives
and see whether you find
the inventory number
146 with Rubens together.
But besides that, there may be
something else you can do
with those larger data sets.
In 2008, there was a fantastic
exhibition at MoMA, Design
and the Elastic Mind,
which had really
an entire section on data
visualization.
But it did strike me that it was
mostly done
for artistic or scientific
purposes.
So they are beautiful.
But the question is also, what
do we learn from them?
This is a piece by Aaron Koblin,
and it's about flight patterns
throughout America over 24
hours, so day and night.
And you have here some
for the East Coast,
and here some for the West
Coast, and it is animated.
I just didn't embed the video
here.
And it's quite striking.
But that brought up
the question, couldn't we
do such a thing with the data
in the Provenance Index,
because basically, we also have
records in there that have
places and times and so on.
So our database is also a lot
about mobility of paintings,
mobility of artists, and so on.
Of course, I couldn't do that
alone, and it tends to be
the case that those projects are
collaborations.
And we actually met a while ago
at the Getty
to think what we could do
with a subset of the Provenance
Index.
Here was Lev Manovich, still
at UC San Diego.
Today, he is at CUNY
at the Graduate Center.
It turned out that he's not so
much really
interested in our data
because he's more into working
with large image data
sets rather than
textual and numerical data.
Piotr Adamczyk was back then
at the Metropolitan Museum
analyzing the metadata
of the collection,
whether he could see here
some relationships that help
curators finding new ideas
for exhibitions and so on.
And he is now with the Google
Art Project and was never seen
again.
It's funny.
[LAUGHTER]
And here the real collaborator
on this project so far
was Maximilian Schich.
He is also no longer a postdoc
in Boston, but he is now
a professor at UT Dallas.
And he has recently published
a piece in Science
with comparable data
in a way which was
about the migration of artists,
where he uses data,
biographical data,
from the Allgemeines
Kunstlerlexikon
and the AAT from the Getty.
By just using the birth
and death dates, he could kind
of, on a large scale,
show artistic migration
throughout time.
We used a subset
from the database here.
And to experiment
with these possibilities,
we took about 230,000 records
from the Provenance Index
covering the period 1801 to 1820
from the Sales database.
These were 130,000 records
from British
and 65,000 from French sales,
40,000 from Dutch,
and 30,000 from Belgian sales.
This subset of data is actually
quite complete.
It includes virtually all
auctions from the 20-year period
for which a catalog has survived
and which contains painting
lots.
It is also rather clean,
since in the early days
of the Provenance Index
this information was prepared
for print publication, which,
compared to today's
online database,
does not allow
for easy corrections
and additions.
And that was, for me, as an art
historian, new.
I did not put the research
question first.
We actually looked into the data
model, the data architecture,
and we're looking
for connection-ships,
relationships
between different data points.
So we kind of hoped
that the question would reveal
itself at a certain point
in the analysis.
But what revealed itself for me
right away, I always had thought
that the Provenance Index is
mostly about art works.
But interestingly, it was mostly
about social information,
or at least to a large extent,
social information that has
never really been analyzed,
at least not in the aggregate.
So in a first rather simple line
graph, and I'm now talking
about this, we captured
the annual sales dynamic
both in the four
separate markets
of Britain-blue, France-red,
the Netherlands-orange,
and Belgium-cyan,
as well as the sum total.
It's the dotted grey.
The x-axis indicates time
in years, while the y-axis gives
the total number
of annual painting sales
at auction.
Initially, from about 1801
to 1808, the total number
of transactions
seems to fluctuate around 10,000
per year.
Yet around 1810, we see
a massive spike and the number
of annual sales almost doubles,
subsequently falling back
below 1809 levels.
While British sales dominates
the market most of the time,
France catches up in the years
after 1816.
The significantly higher volume
of transactions around 1810
is actually noticeable
on all national marketplaces.
Even such a simple graph
identifies new questions
and areas for further research.
What are the reasons
for these bubbles?
How might it be related
to contemporary economic and
political shifts?
So the point here is that just
visualizing things in such
an easy way,
you get more research questions,
or more research to be done.
The next view of this data
to the right provides insight
into Europe's market
integration.
Looking at monthly sales
fractions
where we sum up January sales
1801 to 1820,
then February sales
of the same period,
reveals a clear cyclic pattern.
The hour positions of the chart
correspond to the 12 months
of the year, while the radius
gives the mean percentage
of transactions
in a particular month aggregated
over 20 years.
The spring is dominated
by British sales,
with most transactions taking
place in May.
France also shows life
in auction activity in spring.
But the most important season
seems to be fall, with a peak
in November.
The smaller markets, Dutch
and Belgian, occupied a summer
when almost nothing is happening
on the other two marketplaces.
The figure is interesting as it
indicates a clear market cycle
with the bulk of total sales,
dotted line, transpiring
between March and April,
while the national markets are
seemingly adapted to each other
by being slightly
staggered in time
like the sections
of a folding fan.
The absurd seasonal behavior may
have allowed key agents
in the art market
to be active internationally,
traveling to all key sales
events
without having to be in more
than one place at the same time.
The heat maps below combined
information represented
in the previous two charts.
Every line in these mattresses
corresponds to a year from 1801
to 1820, while the columns
indicate months from January
to December.
The color in the cell
stands for the amount of sales
from low numbers
in yellow and high numbers
in red.
White indicates a month where
zero sales are on record, as
for example, in August 1805
right before the Battle
of Trafalgar.
We are here in a time of war,
the Napoleonic Wars.
The metrics
with all transactions combined
confirm spring as the hottest
season
throughout the 20-year period,
which is largely
due to the strength
of British sales.
The French pattern demonstrates
that auction activity was rather
weak up until 1808.
Dutch and Belgian sales gives
a much more irregular picture,
which suggests
some big, possibly estate, sales
but no continuous auction
season.
Of course, you can also chart
consumer preferences in terms
of artist nationalities
and artist names.
Here, the art historians would
say that doesn't come
as a surprise
that the market was really
flooded by Dutch pictures.
But I think what's interesting
in terms of market integration
or globalization
is the uniformity of taste
throughout these countries.
And it's the same, actually,
for artist names.
Teniers is very
prevalent in most
of these countries.
But it always represents just
the information and beliefs
in auction catalogs.
So Teniers comes up 5,000 times,
so I would assume we see also
a lot of fakes
here in these auction catalogs.
And that's why it would be very
interesting to analyze
in this quantitative way
the so-called attribution
modifier, which we have
in the database,
by, after, and so on,
and a big number of attribution
modifiers.
But the data lends itself
to visualizations focusing
on cross-border traffic
and international agents.
Economist Neil de Marchi
recently pointed out
that the financial market
linking crucial centers
such as Amsterdam, London,
and Paris
has been studied in depth.
But comparable research
into the, quote, "mechanisms
of the painting trade
and the extent to which it was
integrated across those centers
has barely begun."
Quote end.
Major centers
of the secondary art market
in the period
were London, Paris, Amsterdam,
Antwerp, et cetera.
Based on 230,000 records,
this network diagram maps agents
such as buyers, sellers,
auctioneers, and experts
who were
active at multiple places
in Europe between 1801 and 1820.
Circle represent individuals
and squares represent places.
Node and link color
indicate the prevalence
of selling
is blue, broker in gray,
and buying orange.
And Christie's, for example,
appears gray--
it's here-- because it buys
as much as it sells.
The size of the circles
and squares, as well as
the thickness of the lines
connecting them,
is
dependent on the total activity
and number of transactions
over the 20-year time frame.
This view is particularly
useful for showing us which
individuals connected
multiple marketplaces,
and we recognized
some prominent names,
such as Jean-Baptiste-Pierre
Lebrun, Alexandre-Joseph
Paillet, William Buchanan,
and John Smith, et cetera.
Visualizations also help us
in recognizing flaws
in the data.
We find, for example, Paillet
and Alexandre-Joseph Paillet,
Lebrun and Jean-Baptiste-Pierre
Lebrun, which suggests that some
of the names
have not yet been disambiguated.
The relative position
of an agent in the field
is especially telling.
While Lebrun seems to buy
in Paris
and sell to London, but also
to Rotterdam, Paillet, a much
bigger broker, appears more
drawn to Belgium.
In an interactive
representation,
we could immediately pull out
individual agents--
some are much less known
than those I have just
mentioned--
and study their behavior over
time.
When it comes to markets,
art historians tend to favor
a microhistorical approach,
devoting monographs
to a few international dealers
and extrapolating
from their behavior.
So here you would just pick out
the few well-knowns that were
international, and then you
would say the entire market was
international.
But if you basically go back
to the entire picture
that we have here,
most of the buyers and sellers
were actually only working
locally at this time.
And I would go
to another representation
of this data, where we basically
leave out, more or less,
the places.
And I know that we art
historians immediately think
about mapping, but somehow I
thought
that the social relationships
may be even more revealing.
So let us introduce
a so-called spring-embedded
layout algorithm.
Instead of laying the network
vaguely over a map,
as seen before, this algorithm
assumes that links between nodes
behave physically like springs.
In this case, the length
of the link between two nodes
is calculated by the number
of transactions.
The more business activity
between a buyer and a seller,
the closer they get.
The entire social network
is built on the basis
of business activity.
Instead of using number
of transactions, which
is basically the number of art
works exchanged for money,
we could also have constructed
the social relationships
according to the amount of money
exchanged.
But it's much more difficult
because then you have to deal
with currency conversions
throughout Europe
in the early 19th century, which
is doable,
but it's just a little bit more
complicated than using
the number of transactions
for calculating
the social relationships.
By constructing
such buyer-seller networks
for each year
of the 20-year period,
we are in a much better position
to analyze international market
integration.
As a matter of fact,
the situation is changing all
the time.
The market is much more
dynamic and volatile
than usually assumed.
For 1808, we notice
a clear separation here
between the Continental
and the British art market.
There's not a single link
crossing over.
One year later, we have already
a few connections.
And in 1816, the market seems
to be quite integrated.
These changes year by year
are, of course, better
represented in a video, which I
would like to show you here
in a second.
This is just the first graph.
And it's a little bit hard
to read.
Basically, we have pulled
the networks apart--
this, again, Great Britain, this
is France,
and this is Netherlands
and Belgium over here--
and put them vaguely
in their geographic positions.
But of course, this is not
the main points,
and we have to leave out
the labels so that it will be
readable.
Can you please start the movie?
And I would like you to focus
on, perhaps, on this one point
here because there is one agent
who kind of stays here
over about the whole period
connecting all these markets.
And we're now in 1810.
And he changes color.
Sometimes he's red.
Sometimes he's blue.
I now have lost him.
[LAUGHTER]
But believe me,
he is there somewhere.
That's why I'm saying it's
a little hard to read here.
I have it also as a slide,
this section.
This guy here was Pierre-Joseph
Lafontaine.
Overall he appears as a broker,
so he's gray.
But in the video,
he changes color over time,
which means he buys and sells
in cycles.
In general, we find
many small buyers in red
and a few big sellers blue.
The market expands over these 20
years.
There is little persistence.
Many agents come and go, rise
and vanish like stars
on the sky.
And surprisingly, in the video
is this one, a dealer who really
stays.
My point here
is that Pierre-Joseph Lafontaine
is known by art history.
He is mentioned in a few lines
and has been
in other important art
historian's work.
But he has never gotten
a monograph so far.
So I think you can find
new topics by using
those things.
We always actually found that,
or it helped us at least,
to shape the conference topic
for our conference
with the National Gallery
in London, London
and the Emergence of a European
Art Market,
because the market integration
is such an interesting topic,
I think came out really
from that.
But it's very important for us,
and I just come to a conclusion
right away is we really want
to redesign the Provenance
Index,
or rethink the Provenance
Index because clearly
these visualizations are not
completely satisfying as
long as they remain
static images.
And even the video is just
a step toward something
more dynamic and interactive.
What we are aiming for
is exploratory research tools
rather than infographics,
graphics that are used
for communication only,
as we see in news media today.
We need an elastic user
interface that allows
for a number of different views
onto the data,
possibly something
along the lines of Stanford
University's
Visualizing the Republic
of Letters.
While that database is much
smaller and less complex
than the Provenance Index,
containing information on 55,000
letters exchanged between 6,400
individuals in the 18th century,
their interface is much more
advanced.
Users are able to choose
from a selection of views
over here.
They can also determine
the period of investigation--
you have a time slider here--
by moving it back and forth.
If you are only
interested in Voltaire's
network, for example,
you filter out all
the other components.
Good user interface design,
Ben Schneiderman reminds us,
provides you first
with an overview,
then you should be able to zoom
in and filter out until you
eventually get to the details
you were looking for.
What sounds very simple
is hardly ever followed
in the design of larger art
historical databases.
Usually you type a word,
something very specific,
into a search box,
not knowing whether such a query
is even supported by the data.
Basically, you need to know what
the thing is called you are
looking for.
Also, the relationships
between different data points
are usually completely hidden
to the user.
I like to compare the advantages
of a visual interface
with the open-stack library.
While you may have a book
with a specific author and title
in mind, only if you stand
in front of the shelves
will you be able to see
connections to other writing.
A whole new universe may open up
in front of your eyes.
So I would rather say this is
serving the data than really
kind of doing a precise query.
To conclude,
"The job of digital tools,"
Michael Witmore explained,
"is to draw our attention
to evidence impossible or hard
to see during normal reading,
prompting us to ask
new questions about our texts.
This ability to redirect
attention and pose new questions
is the strong suit
of certain kinds
of digital humanities research."
Today, large data sets,
in conjunction
with new visualization software,
allow for a distant reading
of cultural consumption
that may either complement
or contradict
the predominant case-study
approach in art history.
Shifting our gaze
from exceptional events
to large mass effects
may raise a number
of new questions
about the field
of cultural production,
questions we were previously
unable to ask.
Thank you.
[APPLAUSE]
