Data science, the study of obtaining value from data, is a fast‑emerging and distinctive field. It is driven by experts in several domains, computer scientists and statisticians who create and use increasingly sophisticated languages, tools, and methodologies that enable data‑driven decision making and problem solving. This diverse set of applications and tools, driven by domain‑oriented challenges of our increasingly data‑centric world, can often be translated and adapted for use in other fields, such as astronomy and astrophysics, economics, public policy, and cancer research.
In a way that is distinctive to the University of Chicago’s rigorous academic culture, researchers across the University not only develop new tools and techniques in their respective domains, they also consider the theoretical underpinnings of each new approach. This creates a natural ecosystem in which applications are developed across fields while simultaneously establishing a strong theoretical foundation for data science as a discipline, resulting in an accurate and theoretically sound basis for developing and translating existing and new applications.