WordAreas

From CopyCult

Table of contents

In a nutshell

How the keywords we use to describe the artists, networks, artworks are situated geographically. The page keywords on genderartnet (http://genderartnet.constantvzw.be/keywords/) gives an example of the possible uses of this concept.

This visualization helps to articulate questions like:

  • Where do originate the artists working on a specific theme? And where is their current place of work?
  • What can we learn from this trajectory and the theme they are busy with? For which keyword do we see the artists living the fartest from their place of birth?
  • Where are the works related to a certain topic located? Are they concentrated in a certain area? Does it differ from another similar topic? Are they located in places very close to works that are very differently "keyworded"?
  • Which keywords "bring" the artists towards Europe? Which keywords "make them leave" Europe?
  • How networks and groups can be compared in terms of extent? Which are the ones that operate locally and which ones operate globally? And which keywords are related to them?
  • Which themes have local importance and which ones are globally adopted?
  • How a global theme is related to local ones?

If temporal information is added to the entries, these forms could be animated along a timeline.

An example

Placement

5 artists have been associated with the keyword violence. By placing the artists on a map using the coordinates of their cities of residence, we obtain the following image:

Image:Screenshot-genderArtNetKeywordOrdered-1.png

From dots to shapes

Now, when we connect the dots, we produce the following shape:

Image:Screenshot-genderArtNetKeywordOrdered-2.png

Overview

This shape gives an idea of how the keyword violence is spread. We can therefore quickly compare the different keywords shape to shape:

Image:Screenshot-genderArtNetKeywordOrdered-3.png

Cities of residence / cities of origin

We can also compare the same keywords when we produce its shape using the artists cities of residence's coordinates and the artists cities of origin's coordinates. In the following screenshot, the map overlaps the shape produced by the cities of residence (red shape) and the shape produced by the cities of origin (white shape).

Image:Screenshot-genderArtNetKeywordOrdered-4.png

Individual trajectories

Individual trajectories (from city of origin to city of residence) take the form of a curve.

Image:Screenshot-genderArtNetKeywordOrdered-5.png

By using a projection that places Europe at the center of the map, we can observe the movements inwards/outwards (artists arriving or leaving Europe).

Questions, further developments

At the moment, the forms don't differentiate between a city that is the city of origin of many artists for a given keyword and a city that is the city of origin of only one artist. It doesn't show the concentration of people coming from one place. This could be solved by adding another dimension (the number of artist per city) and making a 3D representation.(examples will follow).

The shapes give an easy way to compare each other and give an idea of how a keyword is spread geographically. But the surface it contains doesn't imply that every artist who lives inside this area is associated with this keyword. It is more comparable to a constellation of stars which are forms that give a way to identify a selection of stars together than a country where everything inside the borders belongs to the country. The meaning of these shapes is relational, it makes sense when compared to others.

Keywords in themselves don't really mean anything. The keyword body, for example, can be used to describe practices, artists and artworks that barely have anything in common. But if we look at the entries that are associated with the keyword body and the keywords genome and medicine, we can narrow and precise our understanding of these entries and their connections will be more meaningful. And we can differentiate them better from the entries that are described with the keywords body, pleasures and performance. This possibility to create clusters (http://en.wikipedia.org/wiki/Data_clustering) would help narrow and filter the meaning of the keywords.


Online discussion

Ines: Is in our project a "key" or "legend" contemplated? The legends on the brown based mapping Nicolas has uploaded are not all clear, traces and dots working with the same colours confuse me (i.e. red traces=cities of residence or red dots= cities of residence?) ... not all traces (black? pink?) have a legends.

Nicolas: At the moment, there are three colors:

- white for the forms related to the cities of origin (shapes connecting cities and dots for the cities of the artists)

- red for the forms related to the cities of residence (shapes connecting cities and dots for the cities of the artists)

- black for the line showing the trajectory between the city of origin and the city of residence of individual artists.

If I understand what you say, the legend should differentiate the meaning of the dots and the shapes for each color?