The use of computers in Art history is related to the mid-1960s when the art historian Jules Prown used Yale University’s computer lab to understand the relationship between the social and economic factors and the sitter’s preferences in portraiture of John Singleton Copley’s. After a few years, computers and digital tools became part of Art history research. This essay addresses the use of computer tools to analyze big data in art history. Now, computers allow art history to explore large data and share their analyses in museums with the public. This extraordinary change wouldn’t have happened without the effort of Prown.  

Prown was the first Art historian to use computers and statistics to analyze 240 Copley’s sitters, comparing different elements such as age, gender, wealth, gender, religion, age, and size of the canvas[1]. Many scholars were conservative about using computers in art history research, including the department chair of Yale University, who advised him to delete the computer analysis from his book because the computer analysis may affect his tenure promotion.

I found this article very interesting as the use of computers at that time was very limited. However, Brown decided to use it to save time and offer accurate results in his analysis. This chapter allowed me to compare the use of computer analyses between the mid-1960s and now. I could see how computer tools developed in the last 60 years. I understood that the computer would make incredible changes in the Art history field, which we are witnessing today.

On the other hand, Matthew Battles and Michael’s article shows how the digital humanities enable art historians to analyze big data[2]. One of the most significant challenges historians and art historians faced in the past was how to work with big data. In the past, museum curators were mainly focused on presenting and preserving the data. These tools allowed art historians to understand the relationships between different museum collections. It also allowed the museum to present numerous collections of digital images, and the victories now can be seen in these. images and compare them. For example, the Harvard Art Museums created the Lightbox Gallery, an exhibition offering an interface where museum visitors can use the screen to interact with the collection.  

Technology allowed museum visitors to engage more with the collections. These tools allowed the visitors to explore the collections themselves.  For example, these tools enable visitors to locate object maps, explore the metadata associated with the objects; and know how art objects are labeled. These tools increased the idea of the museum as a place of learning and inspiration. Many teachers now mainly depend on museums as a tool for learning. Students will be more engaged with the information they get from the museums.  The analysis of big data benefits the audiences to have a better understanding of museum collections.

Reading this week allowed me to understand data analysis in art history and the different tools art historians use to analyze and study data. Of course, data analysis is one of the topics I was worried about early in the semester because, for me, it seems complicated, but thanks to the reading, I was able to understand the topic and how I can apply what I have learned in my future digital history project. I was also inspired by Jules Prown through out-of-the-box and used computers; now, the art history field mainly depends on digital tools. This a lesson for me as a scholar to think, listen to my own voice, and do what I believe is right.

[1] Jules Prown. “The Art Historian and the Computer.” Art as Evidence: Writings on Art and Material Culture(New Haven, CT: Yale University Press, 2001).

[2] Matthew Battles and Michael Maizels, “Collections and/of Data: Art History and the Art Museum in the DH Mode,” Debates in the Digital Humanities 2016, eds. Matthew K. Gold and Lauren F. Klein

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