Bildbiografien – Active Archives, the final project for my bachelor’s degree, grew out of a personal dream of mine. It took its inspiration from an existing collaboration between the Museum of Modern Art (MoMA) and Google Arts + Culture, where over 20,000 exhibits were digitized and made accessible to the public. I took the core of that project for MoMA and developed it beyond the initial parameters into a full-featured and interactive research tool for the digital humanities and the public. Bildbiografien is a digital humanities research tool. It employs machine learning and computer learning algorithms in order to re-contextualize the biography and “provenance stations” of a particular piece of art; i.e. its relationship to other art works and institutions across time and space. 

The goal of the project was to aid art historians, curators, and archivists in their work, to spur and cross-pollinate fresh ideas, and make the experience of interacting with the digitized exhibits more engaging. The interface is a clean and unified body of surveys for discovering artists, following threads of inquiry, previewing options, virtually traveling from museum to museum, and visualizing the context of past exhibitions. As more information from the past becomes digitized, and more of the future is born digital, the need for similar tools will only continue to grow.