
The ITM Data Commons is a collection of datasets that are complementary to the biological and clinical data
usually used in biomedical research. These data mostly come from federal, publicly available sources. Examples
of variables in these datasets include: population size, employment and income, crime/safety, community
resources (e.g., healthcare facilities, schools, parks, transportation, roads), weather, air quality, housing,
industry, businesses, and health status and behaviors. The ITM Data Commons makes it easier for scientists to
access these data and link them with biological and clinical data, allowing scientists to incorporate them into
their research and explore how these variables may help explain biological and clinical variability in the
development and progression of disease as well as the response to preventive and therapeutic interventions. In
so doing, we hope to foster more rigorous clinical translation that leads to improved health outcomes for all.
This project is supported by the National Center for Advancing Translational Sciences (NCATS) of the National
Institutes of Health (NIH) through Grant Numbers UL1TR002389, KL2TR002387, and TL1TR00238 that fund the
Institute for Translational Medicine (ITM).