The Project

sneakpeak

Who does an artwork belong to? To the artist, the culture it originates from, the public or the collector who bought it?

When a work of art is bought at a high price, it must be a very good work or not? Everyone should be able to see it, get inspired, experience it. But often when it becomes private property after the purchase this isn’t the case: maybe it will land in a storage as an investment good waiting for its next sale.
An art work which is traded for money must be reduced to its only comparable value: the material one. An ideal value can be only developed if people see it, when it’s exhibited – the artist doesn’t gain recognition if no one sees there work.
Museums and other public cultural institutions can hardly compete with the market prices. For every exhibited piece there is also an insurance that grows the more prominent (read: expensive) an artwork is. Therefore these institutions are dependent on sponsors and collectors who give works of art as loans. When an art work develops a high price on the art market,  market value rises, but possibilities to show it publicly goes down.

The Art Retriever – Stock Market of pure Imagination retrieves art works from there hidden existence as investment goods and makes them publicly available again: regardless of its sort of ownership – maybe it was just bought las week for a few millions by a private collector. Copyrights which were made to regulate selling arrangements on the art market aren’t considered in this process.

This work is an online data visualisation processed in real time as well criticism on the institutional perception of art. Art is property, hence it must be owned by somebody. And who are the artists? Producers of objects of value. There are online data bases like artfacts.net and mutualart.com which offer not only auction results, but also graphs of an artist’s productivity, a prognosis of their art works values in the upcoming years and sales indexes.

On these online platforms you can see the best artists (neatly ranked by an all-over index). The more data there is about one artist (sale values, amount of purchases, amount of exhibitions, international recognition index, productivity,..) the more space it occupies also on The Art Retriever: All available data of a work make up its visualization: words and numbers appear and form the image of this art work on the screen. Most expensive Works (e.g. Picasso, Warhol, Richter) are nearly unrestrictedly visible, while one hit wonders or artists which aren’t that successful in general will be hardly visible and hidden behind their data.

 

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New Screenshots of The Art Retriever

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The Opening

On June 6th there was the opening of the TIMO OUT 0.2 exhibition at the Ars Electronica Center in Linz.

 

 

it works!

IMG_20140602_185249 IMG_20140602_185434

YEAH, it works!

On Monday, June 6th we were working on the setup (most of all on the stable connection to the network) and around 4pm it was working for the first time! The problem with being ready 3 days before the opening (https://www.facebook.com/events/737889532920505/?ref_dashboard_filter=upcoming) ist, that there is more than enought time now for perfectionsim and I can’t let go until thursday.. My new work space is now between the facade and the wall (pictures follow) which will be okay for the next days.

IMG_20140522_215537

 

 

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The Info Screen

mockData_infoscreen

The content of this image will be displayed on a small screen next to the visualisation. It always show the data of the visualised artist’s work.

It has two functions:

First of all, it shows details of the artist and their works, like every name tag in an exhibition does.
But furthermore it contains stock market information of the artist in question.
The two graphs show sales, investment and performance information.

– this image btw shows mock data.

The WordCram Library

To make my visualization I am using the WordCram library, written by Dan Bernier. Maybe you already know the word cram plugin Wordle, Bernier made it available for processing, equipped with a lot of useful functions. The process of creating a WordCram is easy: create it, show it the text you want it to use (local file, directly from the web or words created manually), tell it some specifics (color, font, which form the word cloud should be,..) and then create it: the words can either appear frame by frame with:


if(wordcram.hasMore()){

wordcram.drawNext();

}

or all at once:

wordcram.drawAll();

 

Last year while working on the project for the first time I wasn’t able to make all the words, that make up the picture frame by frame, the drawNext() didn’t work. My problem was the following:

My method was drawing white words on a black canvas and overlaying the image with the blend mode MULTIPLY. MULTIPLY only shows the picture over a surface lighter than black. This was perfect for showing all words at once. But when it came to showing the words after one another it was like this: 1 white word, then the picture blended over it, then another white word and the image again. In this process the image was blended over the first word 2 times, and then 3 and so on. So the image was overlaying itself on preexisting words.

Finally, I contacted Dan Bernier directly to help me find a solution. He answered a few hours later and came up with this idea:


import wordcram.*;

PImage pic;
WordCram wc;
PGraphics buffer;

void setup() {
pic = loadImage(“stairs.jpg”);
pic.resize(800, 0);
size(pic.width, pic.height);

buffer = createGraphics(pic.width, pic.height);

wc = new WordCram(this).
withCustomCanvas(buffer).
fromWebPage(“http://nytimes.com”).
withColors(#bbbbbb).
withFonts(“Bebas”);
}

void draw() {
background(pic);
if (wc.hasMore()) {
wc.drawNext();
}
blend(buffer, 0, 0, width, height, 0, 0, width, height, SUBTRACT);
}

This was the output: (if you run it in Processing you can see that the words appear frame by frame).

blog

I transformed the code a bit:


import wordcram.*;

PImage pic;
WordCram wc;
PGraphics buffer;

void setup() {
pic = loadImage(“stairs.jpg”);
pic.resize(800, 0);
size(pic.width, pic.height);

buffer = createGraphics(pic.width, pic.height);

buffer.beginDraw();
buffer.background(0);
wc = new WordCram(this).
withCustomCanvas(buffer).
fromWebPage(“http://nytimes.com”).
withColors(#FFFFFF).
withFonts(“Bebas”);
buffer.endDraw();
}

void draw() {
background(pic);
if (wc.hasMore()) {
wc.drawNext();
}
blend(buffer, 0, 0, width, height, 0, 0, width, height, MULTIPLY);
}

And I reached exactly what I wanted:

blog2

Maybe you wonder how I made the video in this post without figuring this problem out earlier; well it was fake and just rendered without the overlaying picture (which I added in after effects). Now the visualization works automatically and I just need to make it as smooth as in the video and try to recreate the word overlaying effects.

More from Dan Bernier:

http://invisibleblocks.com/
https://twitter.com/danbernier

And the WordCram documentation:

http://wordcram.googlecode.com/svn/javadoc/wordcram/package-summary.html

 

Visualisation of the Top100

Jasper_Johns

When I first tried to run the new Processing Sketch which I coded for the exhibition at AEC it didn’t die but showed me more or less the Top 100 artists according to the main website I’m retrieving the data from. I didn’t work on an improved visualisation yet, but therefore Nr. 60, Jasper Johns came out really well.

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