Harvard Andean Working Group: Considering Data Collected From Archaeological Objects — And How We Need to Understand Its Nature to Make Sense of Analyses

This talk examines the hidden assumptions embedded in digital humanities data. Although data-driven methods such as machine learning and statistical analysis are increasingly common, the data itself is shaped by human decisions, biases, gaps, and long-standing collection practices. Meaningful analysis requires careful attention to data histories, quality, and limitations—yet these issues are often overlooked. Using archaeological case studies, the talk proposes a framework for understanding how data characteristics shape analytical outcomes and calls for more rigorous engagement with the foundations of our datasets.

For additional information about the speaker and lecture, please see the attached poster.

This event is presented in collaboration with The Harvard Andean Working Group