The Center for Data Intensive Science (CDIS) at the University of Chicago is a research center developing the discipline of translational data science and applying to advance biology, medicine, and environmental research.

We view translational data science as a discipline that applies data science principles, techniques and technologies to problems in other fields with the hope of not just solving a particular problem but also of having a broader impact, such as having a broader human or societal impact, or improving our fundamental understanding of data science.

Translational data science requires interdisciplinary innovation in i) computing science; ii) machine learning and and statistical models; and iii) the underlying discipline we are studying, such as cancer, PTSD, the environment, etc.

The growing volume of data available necessitates advances in the sophistication of these methods. Our work centers around developing large scale instruments called data commons that integrate large scale datasets with computing infrastructure and commonly used software services, tools and applications. Through this approach, we can more effectively use data at scale to study and pursue scientific inquiry in the areas of biology, medicine, healthcare, and the environment.

We have developed serveral data commons, including: