Project Title:
Invisible Women: Gender Representation in the Art World
Project Title: Invisible Women: Gender Representation in the Art World
Role: Data Analyst and Visualisation Specialist
Project Description: This project aimed to highlight the gender disparities in the art world by analysing data on gender representation from the Warwick Art Collection and employment earnings across various industries. The objective was to create visualisations that bring attention to the underrepresentation and wage gaps experienced by women in the arts.
Key Responsibilities:
Data Collection and Preparation:
Collected gender representation data from the Warwick Art Collection and employment earnings data from the U.S. Department of Labor.
Categorised the data into fourteen industries to provide a comprehensive overview of gender disparities.
Coding and Visualisation:
R Programming:
Used R for data visualisation, employing the
magick
package to organise and display photographs of artworks.Example code snippet for visualising artwork data:
library(magick)
library(grDevices)
setwd("~/Documents/portfolio/faculty_of_art_collection/")
par(mfrow = c(5, 10), mar = c(0, 0, 0, 0))
for (n in 1:15) { picture_path <- paste0(getwd(), '/', n, '.jpeg') picture <- image_read(picture_path) plot(picture) }
Tableau and RawGraphs:
Utilised Tableau to create bar charts and line charts to visualise employment earnings and gender representation data.
Used RawGraphs to create additional visualisations, ensuring the clarity and impact of the data presentation.
Example visualisation included the distribution of median earnings across different industries, highlighting the wage gaps between men and women.
Visual Design Choices:
Selected bright blue for female data and a less bright grey for male data to highlight gender disparities and break down stereotypes.
Focused on creating accessible and visually appealing charts to engage a broader audience and effectively communicate the issues of gender inequality .
Project Outcomes:
Created impactful visualisations that effectively highlighted the gender disparities in the art world and across various industries.
Raised awareness about the underrepresentation and wage gaps experienced by women, contributing to the discourse on gender equality.
Provided visual tools for advocacy and educational purposes, supporting efforts to address gender biases in professional environments.
Skills and Tools:
Data Collection and Analysis: R, Excel
Data Visualisation: Tableau, RawGraphs, magick package in R
Visual Design: Adobe Photoshop