SETS: A Set-Based Architecture for Scalable, Extensible, and Transformable Knowledge Structures

SETS is an interdisciplinary research project exploring new computational approaches to studying complex historical sources. The project aims to develop an alternative to conventional AI methods by using set-based knowledge structures to represent, connect, and interpret information from archival documents. This approach seeks to preserve the complexity, ambiguity, and multiple interpretations of historical evidence, enabling humanities scholars to explore relationships, formulate research questions, and generate new knowledge.

Within the project, DensityDesign Lab is responsible for the design of visual representations and interactive interfaces that make these complex knowledge structures accessible to humanities researchers. Through a scholar-centred, iterative design process, the lab investigates how visualization and interaction can support the exploration, interpretation, and questioning of historical data, and how interface design itself can contribute to the production of knowledge.