Traumatic brain injury (TBI) is a leading cause of neurological disorders and affects over 2.5 million people each year, yet no treatment has successfully translated from bench to clinic. TBI is a broad term and encompasses an extremely heterogeneous set of injuries differing by cause, severity, biomechanics, and the varied, complex secondary injury responses that collectively result in chronic disabilities. Current preclinical research circumvents the issue of TBI heterogeneity by relying on specific preclinical animal models that mimic subpopulations of patients and particular secondary injury mechanisms with each study focusing on limited, individual pathways. This proposal instead aims to tackle TBI heterogeneity by approaching TBI as a “big data” problem and aggregating and analyzing the multidimensional data collectively. A framework for data harmonization and curation will be developed, and datasets from a consortium of preclinical labs employing a variety of preclinical TBI models will be collected and curated into an open data commons (ODC-TBI). Utilizing machine learning and multidimensional analytics, the proposed research will directly leverage TBI heterogeneity in the merged dataset to identify persistent features of TBI to empower translational research. By creating a preclinical TBI ODC and applying machine learning to integrate the heterogeneity of preclinical TBI models, the project will reveal multidimensional features of TBI across heterogeneous injuries and characterize how diverse secondary injury mechanisms interact and ultimately affect injury outcome. Throughout the project's timeline, new datasets will continue to be harmonized into the ODC-TBI according to the established framework. The ODC-TBI will be the first open multicenter, multi-model repository of preclinical TBI data and will enable the application of data science to the field of TBI. Furthermore, the ODC-TBI and the methods implemented throughout the project will be openly shared to improve reproducibility of TBI research. Together with the multidimensional analysis that will provide quantitative and qualitative understanding of TBI heterogeneity, the project aims to ultimately accelerate data- driven discovery and precision medicine for TBI.