Data Sets comes out of a six-year exchange between painter Daniel Kohn and scientists at the Broad Institute
of MIT and Harvard.
Through a series of conversations and residencies at the Broad, Kohn explored the conceptual framework surrounding genomics. As a result, his own visual language and artistic method transformed as he was exposed to the methods, challenges, and technologies of genome-based research.
Genomics considers a genome the complete genetic blueprint of an organism as a total system rather than focusing on single elements, such as genes. The human genome, for example, is not simply a chain of 3.2 billion chemical letters, but a dynamic system in which the parts interact, forming genes and other important functional elements that support life. In order to explore this system, scientists routinely collect extremely large amounts of data, which they analyze to find meaningful relationships and patterns. Kohns new work begins to explore a similar methodology.
During his residency, Kohn began painting on 3-by-3 grids of 8-inch square sheets of paper, which he then scanned into his computer. Not only did this work allow me to explore visually what I was learning about science, but I had also unwittingly developed a high-throughput drawing process, which seemed to produce its own form of experimental data, says Kohn.
Rather than being the end process of art making, these watercolor databases became the starting point of a visual inquiry. The serial images could be shifted, sorted, analyzed and reworked in a variety of ways. Kohn found that simply reordering the images brought out latent patterns and shapes that were surprising and sometimes richer than the originals from which they emerged.
Through this process, he began to view his work as a metaphor for the knowledge gathering that was happening around him at the Broad. In the same way that experimental results can raise more questions than they answer and lead to new hypotheses to be tested, an image or pattern in my database could be removed from its original series and serve as the seed for a new inquiry.
Kohn emphasizes that he is not trying to describe or illustrate science. Rather I am interested in the structures we deploy to see. What I am asking in the end is: how can our evolving understanding of high-dimensional and dynamic systems inform a visual language? Conversely, how does visual language structure and communicate a body of knowledge, and ultimately influence how we see?