The physical Dataset works are hand-cut collages made from found imagery, often sourced from historical art, photography, or printed media. Each piece is constructed through a fixed system of slicing and sequencing, where no part of the original material is hidden or discarded. Instead, the source images are fully preserved through meticulous fragmentation and reassembly. The result is a visual code: rhythmic, fractured, and layered with unresolved meaning. These grid-based structures echo the logic of machine learning systems, orderly yet unstable, while remaining firmly rooted in human touch, intuition, and physical labor. In contrast to the digital Dataset works, which translate this method into algorithmic form, the physical series insists on the slowness and precision of the hand.
