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When graduate student Sarah Reiff Conell enrolled in her first Pitt digital humanities course, it didn’t take her long to become hooked on using digital methods to solve historical problems.
A history of art and architecture PhD student in the Kenneth P. Dietrich School of Arts and Sciences, she set out to map patterns of geographic locations of cults that worshipped Christ’s holy blood in Medieval Europe. She first used an Excel spreadsheet, then moved on to Google Fusion Tables to visualize the points on the map and potential clusters. As everything came into focus, she had a “clarifying moment” as patterns emerged that had
literally been obscured by layers of paper maps and colorful push pins.
They uncovered a noticeable gap in one region with no relics of that type. “That prompts new research questions,” said Conell. “What caused this gap? Were the relics destroyed in the early modern period and erased from the historical record?”
In another project, Conell and fellow Pitt graduate student Clarisse Fava-Piz researched information in an accounting book from the 1600s that listed the sculptors working for King Louis XIV of France...
She and other data scientists and art historians were invited to analyze and visualize part of its massive permanent collection using data-driven methods.
The resulting two-day Datathon, as it was called, allowed the teams to present their findings, which are designed to help the gallery better understand its art, the breadth and scope of its collections and how they are exhibited. Conell worked with Golan Levin and Lingdong Huang from Carnegie Mellon University’s STUDIO for Creative Inquiry, along with CMU Digital Humanities Developer Matt Lincoln. Their project used a software called Inception V3 Neural Network, which was trained to look for similar features in photos.
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Source: UPJ Athletics
