Analyzing Digital Collections

Museums in the Digital World

New technology makes museum collections available for academics and the public. People can now access museum collections anytime and anywhere. However, making these collections available for online audiences is not an easy process. Curators struggle to analyze the large number of digital collections. This process is complicated and beyond human ability. It is necessary to find tools to facilitate the curators’ missions, such as ChatGPT and machine learning. These programs save people time and effort. For example, these machines help structure information and data about museum collections.

Machine learning can identify the link between artworks. For that reason, museums, archives, and libraries initiate training programs to train their employees on using machine learning to analyze collections. For example, “Training the Archive ” is a project that aims to examine the ability of machine learning techniques to visualize and explore the links between objects and digital archives. The purpose is to make the data and information of the museum organized and accessible. This project profoundly interests me in understanding how to utilize these machines in museum collections.[1]

However, the article was unclear because it used several terminologies, I wasn’t familiar with. This article was published to help beginner users understand how to use machine learning in museums. To me, I felt that this article was written for digital humanities professionals. The field is new; new users must understand these machines’ processes. Machines always make tremendous mistakes, and curators always fix these mistakes. Online audiences rely on a museum digital collection as a self-learning tool, so we are responsible for providing accurate information to keep the museum as a place for education and inspiration.

On the other hand, curators can develop engaging programs for online visitors. This is demonstrated in the author’s writing about Chinese history in Australia. The author uses people’s images to share the history of racism in Australia when immigrants were required to have a certificate with their image to return to the country. In this project, they collected the National Archives Australia images and then digitized and comprised images. Google allowed him to use facial detection to find photos.[2] With new permitted technology, people can now gather the information they need and answer questions. This program was very engaging to me. Public historians always suffer when trying to reach online audiences. They always ask how to raise the number of our online visitors because the number is less than physical visitors. However, if the museum was able to meet online visitors’ needs, this would expand the online audience. I can tell these types of projects would attract new visitors to learn about these types of projects.

Digital humanities specialists face limitations while searching for digital collections. Since interface tools are limited, professionals would often find restrictions when analyzing digital cultural collections. The article argues that the problem with these digital collections is that they return very limited results when utilizing their search features. [3]This is not helpful for those who are trying to search digital collections for research, as researchers need to explore collections in depth to draw meaningful conclusions. The author argues that the solution is to create web platforms that are more exploratory. I agree with the author on this point that new tools to help users expand their research.

I found the reading for this week to be very selective. By combining these articles, I could build my understanding of how to find and analyze digital collections. As a beginner in the field, I have difficulty learning about the terminology in the field, but I was able to understand how machines enable curators to expand their projects. New technology answered many questions that were impossible to answer in the past. However, with the rapid development of technology, people rely a lot on these machines, and they stop using their brains. It’s good to have these machines to help you save time and effort, but they cannot replace people.

As everything becomes digital, will this affect our cultural institutions like museums and libraries?

People now rely on technology to gather their data. What can we do to engage the community with their museums?

[1] Dominik Bonisch. “The Curator’s Machine: Clustering of Museum Collection Data Through Annotation of Hidden Connection Patterns Between Artworks.” Digital Art History Journal (May 4, 2021)

[2] Tim Sherratt. “It’s all about the Stuff: Collections, Interfaces, Power and People.” Discontents (November 2011)

[3] Mitchell Whitelaw. “Generous Interfaces for Digital Cultural Collections.” Digital Humanities Quarterly, vol. 9, no. 1 (2015)