Who Is Represented in the Tate Collection?
Introduction
I wanted to look into the backgrounds of artists that are represented in the Tate art collection for my midterm project. I focused on gender, birth decade and country of birth. Using available data from the Tate I made two interactive visualisations in Flourish to spot patterns in the collection’s artist demographics. The first graph shows how many male artists and female artists were born in decades. The second graph lists the ten countries that appear often as artists’ birthplaces. Together these visualisations help show how artist representation changes across generations and across countries.
Sources
I used the `artist_data.csv` file from the Tate Collection’s public GitHub repository. That file contains data on 3,532 artists. It lists artist names, birth years, gender and places of birth. Before I made the visualisations I had to clean the data and put it into a form that could be plotted. For the graph I grouped artists by birth decade and counted how many artists of each gender were in each decade. For the graph I changed country names to American English merged duplicate country labels and chose the ten countries with the most artists. I removed records that were missing or unclear. The Tate repository shows a snapshot that was last updated in October 2014.
Processes
I used data cleaning and aggregation steps to arrange the artist information into tables that could be visualised. For the graph I put birth years into decade buckets and counted how many artists fell into each bucket. I then uploaded those counts to Flourish. Made a stacked column chart to compare male artist numbers and female artist numbers over time. For the graph I grouped artists by country of birth ranked those countries by how many artists they had and kept only the top ten. I used a bar chart in Flourish because it makes it easy to see the differences between countries. Both visualisations let viewers explore the data easily than a big spreadsheet.
Presentation
I built my project around two Flourish visualisations that show different aspects of the same dataset. The stacked column chart uses colours for male artists and female artists so viewers can compare the numbers of artists across decades. The horizontal bar chart lists countries from the highest to the number of artists so geographic differences stand out. I chose titles, clear labels and tidy chart layouts so that viewers can understand the results without digging into the raw dataset. I put the visualisations directly into my midterm webpage on my Reclaim Hosting subdomain so visitors can play with the graphs while reading the analysis.
Significance
These visualisations uncover patterns in which artists are represented in the Tate dataset. The first graph shows that male artists outnumber artists in the chosen birth decades although the gender split changes over time. The second graph shows that the United Kingdom has the number of artists by birthplace followed by the United States and several European countries. These facts raise questions about gender representation in major art institutions.
The dataset does not explain why these patterns exist. Missing data, historical collecting habits and the way artist records are labelled may affect the numbers. Also an artist’s birth decade does not say when that artist’s work entered the collection and an artist’s country of birth does not always match the artist’s nationality.
This project is linked to Digital Arts and Humanities because it shows how computer tools can analyse historical information. By turning museum records into visualisations we can spot patterns ask new questions, about representation and make large datasets easier for the public to use.