Project Description
Introduction
Sources
My sources for this exhibit are pulled from the Tate Gallery, a network of art museums in the United Kingdom. Published through GitHub, I used two datasets: one marking every piece of art in the Tate's collection that was produced between 1950 and 1955, and one detailing all the artists featured in the Tate's collection. After browsing this data and noticing the patterns detailed above, I had to clean up the data to make it usable for this purpose. I started by doing simple keyword searches within the .csv files, highlighting entries that had markers of femininity and deleting those which did not. This process decreased the number of pieces under consideration from several hundred down to 44. I then separated the pieces between derivatives of woman (e.g. woman, girl, female, etc) and names of women. I used a similar process on the dataset giving information on the artists, instead using a keyword search to identify the artists that produced pieces between 1950 and 1955, and deleting all other entries. By the end of these steps, I had a much smaller dataset that highlighted only the information I was interested in analyzing, and could move on to the process of creating the exhibit itself.
Processes
As I had already decided that I was using this data to create a digital exhibit, I knew I would be using Omeka. I created the subdomain and installed Omeka into it, allowing me to begin building the site itself. I started by creating the various collections and galleries that would house the art and artist items. To sort between art and artist, I created two collections. I also created a specific gallery for this investigation, which has subsections for the art, artists, as well as this introductory page. I then created a new item for each piece of art and artist, giving each its own page with biographical information (for the artist) and details regarding its creation (for the art). The majority of the art items have an image of the piece sourced from the Tate, however a few do not, due to copyright reasons. Providing images of each piece allows users to not only appreciate the art, but also to find visual patterns in how women are depicted, and how this may correlate with the content of the titles.
I also wanted to ensure that the patterns I had noticed with artists' gender and the wording of the art's titles was apparent, and so created data visualizations highlighting these findings. Using Flourish, I created three donut charts: one shows a comprehensive breakdown of artist gender for all pieces included in the exhibit; the second depicts the gender data for art pieces using a derivative of "woman"; and the third shows artist gender for pieces naming women in the title. These graphs, which can be explored below, demonstrate quantitatively the same pattern which inspired me to create this exhibit in the first place. While in general female artists are in the minority (likely due to gender norms at the time and collection biases within the Tate), there is a higher percentage of female artists whose art actually names the female subjects it represents. Though more research ought to be done into these patterns, I would argue that this points to divides in gender perception in the 1950s. That is, male artists were more likely to view women as simply their gender, whereas female artists were more likely to describe their female subjects as people with names.
Presentation
So as to not distract from the art, I chose a fairly simple Omeka theme for the exhibit. I selected a few items which I felt represented the collection to be "featured" on the Omeka homepage, so that visitors can have a visual draw to explore the exhibit. When exploring the pieces of art, I used the gallery function instead of a list, so that users focus on the art first, rather than the artist or year; once an image is clicked on, the item page contains more detailed information about the piece. As the Tate did not provide images in the artist biographies, the artist pages are only text.
Each item is tagged with the name of the exhibit, Describing Femininity, as well as the name of the artist. As a result, clicking on the artist tag associated either with the person or their art will bring the user to a page that includes both the biographical item as well as the items for all their work. If a user wants to investigate the work of a specific artist, then, they are able to find all associated items on the same page, rather than searching through the entire gallery.
I chose not to embed the Flourish graphs, but rather to include them as images with their own item page, as given the simplicity of the data, I did not feel that an interactive graph was necessary. Placing the graphs in a carousel allows the user to move through them at their own pace, without taking up a large amount of the introductory page.
Significance
In presenting these art pieces and artist data in this manner, viewers gain the opportunity to engage in both a visual and quantitative analysis of the datasets. By engaging with the art pieces as images, users are able to both appreciate the visual quality of the art while also taking note of trends in how women are depicted. This includes both the medium used, the style of the art (realist vs abstract), and the appearance of the woman. These factors are due to many things, including trends in art in the 1950s and the curation desires and biases at the Tate, and can all become visible through image analysis. Additionally, the inclusion of a quantitative analysis aspect allows users to gain an idea of the influence of gender on the depictions and descriptions of women, which is significant for art history and women's studies. Using a DH approach allows these two methods (visaul and quantitative) to be used in tandem, allowing for a richer experience and investigation of the data. Sites such as Omeka in particular are uniquely positioned to do this sort of DH work, and allow for public engagement with these research questions and outcomes.