Project Summary: BRIDGE Center Teaming Core There is a growing recognition that many of the most pressing challenges of our time require a coordinated transdisciplinary approach. Over the last two decades insights have been gained about what successful transdisciplinary collaboration looks like; however, creating space to apply these known successful transdisciplinary best practices is still hard to achieve. Barriers to applying transdisciplinary methods to data-intensive research remain formidable - particularly the lack of resources for training and/or cross-disciplinary capacity-building. The social aspects of a collaboration are often neglected. Additionally, much about the methods for evaluating collaboration and the multivariate effects of individual and team characteristics on collaboration efficacy are poorly understood and are active areas of research. As a consequence of these gaps in knowledge and resources, large biomedical consortia often fall short of their objectives. In our experience on dozens of such projects (and based on years of team science research literature), failure results from a lack of shared understanding about the goals coupled with ambiguous governance processes and/or misaligned incentives. Programs focusing on AI are at particular risk because of their need for innovations across multiple disciplinary boundaries to support specific AI applications. To avoid these pitfalls and advance our understanding of team science we will engage in the following aims: Aim 1. Design and implement Collaborative Agreement to foster sound governance across Bridge2AI. Here we propose to establish policy and process for effective transdisciplinary research based on best practices. Aim 2. Realize inclusive, integrative team science across the BRIDGE community and beyond. Here we propose to provide training and guidance to meet the specific needs of the BRIDGE community. Aim 3. Evaluate efficacy and impact of teaming across Bridge2AI and communicate lessons learned. Here we propose to collect data describing Bridge2AI collaborations and their effectiveness for the purpose of improving the BRIDGE community and advancing the science of team science.