Ceramics represent one of the largest data sets produced in excavations and thus have a large influence over archaeological interpretations. Archaeologists generally apply ceramic typologies to fulfill two main functions. The first is to allow specialists to communicate with each other, while the second is to answer wide-ranging questions about the past. The typologies archaeologists employ are often not consistently created and not conscientiously applied to specific archaeological questions. This dissertation undertakes a critical evaluation of typological methods to promote transparent and systematic practices in data recording and analysis. To compare these methods, I have constructed three distinct model typologies, each employing a different method. These typologies are based on a single data set of about 1,500 ceramic sherds that the UCLA Shire Archaeological Project excavated from the site of Mai Adrasha in northwestern Ethiopia during the 2015 and 2016 seasons. I argue that researchers can and should use a data set to create multiple typologies based on their research goals and questions, and that in disseminating results, they must be transparent about those questions and goals.

Previous archaeological projects conducted in Ethiopia relied heavily on ceramic analysis to identify site function, period, and culture, but have often not considered these questions directly when creating typologies. As more sites have recently been excavated in the Northern Horn of Africa, our knowledge of ceramics has increased dramatically. There is currently a need to compile this new knowledge and reevaluate previous conclusions. This dissertation aims to answer the question of what is the best way to compile these data to facilitate further study in the region. It introduces the digital data platform Northern Horn Ceramics (NHC), which allows researchers to easily record and compare data in the field, immediately share and discuss data online, and create custom typologies from raw data. It is also a powerful tool for the interpretation and analysis of large data sets. Modern archaeological projects produce more data than ever before, and archaeologists are now forced to grapple with enormous data sets. The NHC platform has the capability to store large amounts of artifactual data and, when employed in conjunction with multivariate statistical typological methods, can be particularly effective for analyzing extremely large data sets.