Beth Fischer | Teaching with Data in the Academic Museum
Channel: MSU Digital Humanities
Date: 24/04/2020

Beth Fischer | Williams College

Presentation description:

This presentation addresses ways to work with students on digital projects from within a teaching museum, and especially the use of digital projects to critique and amend museum data sets. This museum has a mission of helping students critique both works of art and the structures that define, categorize, and create value around particular works or types of work. However, the existing museum database and its data both prioritize western post-Renaissance expectations of artist identity, artwork origin, and periodization. Data on works that do not fit this structure is often left out of the record entirely, or categories are twisted to make things fit.

This problem faces many museums, and it becomes a particular issue as we use museum resources to work with students on digital projects. The missing data and missing content in many fields lead students to prioritize works that match existing expectations of art, with known creators and familiar culture or period identifications. The result goes directly against the work we have done in the museum through other types of programming, and often leads students to believe that they have an “objective” measure that confirms their expectations.

In the presentation, I present brief case studies of how we are building student project opportunities that use data while trying to avoid reifying the structural problems that underlie this sort of historical data set. These include new interfaces for visual exploration, projects for working with mapping and machine learning, and processes for adding student research data into the existing data. 

For more information about the 2020 Global DH Symposium visit msuglobaldh.org.