Hacking the Humanities Midterm Project

Sources

The dataset I utilized had artists from around the world that were born between 1950 – 1969. The main thing that these artists have in common is that their works have been displayed in any one of the four Tate art galleries. The spreadsheet contained information such as name, gender, date of birth and death, place of birth and death, dates, and a link to Tate’s website where a brief biography of the artist can be found in addition to images of their artworks.

Processes

After obtaining the dataset I used Open Refine to clean and sort the data. With over 400 entries I had to filter out a good portion of the data. Firstly, I shrank the dataset that I used and changed the dates to be numeric values so that it would be more manageable. There was a column labeled “dates” which displayed the years that the artist was alive. Many of the artists are living to this day so many cells in the column were blank. As a result, I deleted it all together. The dates of birth and death were also their own columns so I thought it was not necessary to also have a “dates” column. I also deleted another column of arbitrary information which contained the artist’s ID code, assigned by the Tate gallery mostly likely for organization purposes.

Processes

I used the ArcGIS software to create a legible data visualization of the dataset of Tate artists. The visualization, as seen above, is an interactive map with GIS locations of the artist’s place of birth, represented by the flags. The color of the flags corresponds with the artist’s gender, which can also be seen in the legend in the menu in the top left. Under each of the locations is the artist’s last name and then first name. If you zoom in and click on a flag, a pop up appears with the statistics of each individual artist. Some artists do not have a date or place of death so that field is left blank. The search bar in the top right can be used to find a specific birthplace as well. I then embedded the ArcGIS map into this website for easy access.

Significance and Results: What insights can be gained by applying your chosen digital approach to the data? How does it relate to Digital Arts & Humanities as opposed to data science generally?

By making a visual representation of this data you can envision how modern and contemporary art is spread out through the world. One is also able to notice patterns from the map, such as the large concentration of artists in the United Kingdom. This is due to the fact that Tate institution is the UK’s national collection of British art. When taking that into consideration, one may wonder how they were able to obtain artwork from so many different parts of the globe. Was it bought, gifted, or even stolen? These observations would otherwise be very difficult to picture with only raw data and may even be overlooked. That can be considered a large drawback to data sciences. The data is hard to decipher and make sense of without some type of software, making it not very accessible. Digital Arts and Humanities aims to take that data and make it available to the masses in a user friendly manner.

One pitfall of my project is that everything is not localized to the embedded image. I wish I was able to use an image of an artist’s work as a pop up for each of the pins so that you wouldn’t have to go to a different website to view it. I also attempted to create a 3D globe as opposed to a 2D map to make it more engaging but was not able to successfully figure it out. Besides that I think my map accurately represents the given data in an effective way.