About the Project:
For my midterm, I was given the option to choose a dataset out of a list 15. I decided to choose the Tate artist dataset from 1950-1969. This dataset is very interesting as Tate is a gallery founded in 1897 and is the United Kingdom’s national collection of British art, and contemporary and international modern art. The variables given were the id, name, gender, dates, yearOfBirth, yearOfDeath, location of birth and death of the artists along with a url link to their artwork, biography, and film & audio. Given these variables, I then decided that it would be most interesting to conduct a geographic analysis on the birthplace location by gender of the artists’ in the dataset. Throughout the data cleaning process, I utilized R, since this was the data visualization tool that I have used in my mathematics and statistics classes and am most familiar with. I was able to import the csv file given into R, then I created a subset of the dataset to clean for NA values and to only choose the variables of name, gender, and placeOfBirth. I did this because these were the only variables in the dataset that I was interested in. I removed NA values because I didn’t want there to be any data points to ensure that my analysis was reliable and free of inconsistencies. Since I only chose the variables I was interested in, I was able to make the dataset less cluttered and was able streamline the dataset to focus on key aspects for my geographic analysis. Next, I exported my new csv file that I created to ArcGIS. I was then able to create a new layer of the world map with the locations of all the artists and to differentiate the different points on the map to whether the artists’ were male or female. I chose the basic layer to keep the map simple to understand. I also chose the appropriate symbology of a blue bubble with a letter F for female and a red bubble with a letter M for male, as shown in the map I created on ArcGIS, embedded below. I also decided to create this blog through Installatron through WordPress on the https subdomain. When you click on the points, you can also see the name and gender of the artist.
Map:
Results:
Looking at the datapoint and interactive map created in ArcGIS, it appears that there are gender disparities in mainly Europe and United State of the artists’. In addition to this, there are significantly fewer artists from other countries, which makes sense because the dataset is for a museum in the United Kingdom. Overall, these results shed light on how gender and geography intersected influenced artistic practices and opportunities in the time period 1950-1969.
Significance:
Utilizing a geographic approach to the Tate Gallery dataset, I was able to draw insights into the spatial dynamics of gender representation of artists during the time period of 1950-1969 for the Tate Gallery. In addition to this, it allows for further understanding of how factors such as geography and gender intersect and influence artistic practices and opportunities. Most importantly, this project contributes to the field of Digital Arts & Humanities by utilizing both digital tools and methodologies to analyze artworks and historical data. This project draws insights that bridge the gap between art history, geography, and data science. To conduct further research, more data points should be looked into. Only looking at data points from one museum/gallery may not be sufficient evidence to draw an significant results.
