The ability to generate, share, and analyze data is fundamental to the operation of the Center for Clinical and Translational Science and Training (CCTST) and participation in wider CTSA networks. Effective fulfillment of these principles requires robust data infrastructure and well-formulated policies and procedures, but more importantly, the development of a highly participatory, informatics- and data-literate research community that embraces best practices alongside innovation. We believe that fulfillment of these data-centric objectives will allow greater discovery, inference, understanding, and translation of knowledge for improved health and wellness. To achieve these objectives, we will focus on the development and implementation of disciplinebased local learning systems to improve data aggregation, data utilization, and informatics literacy, with a focus on our own health care systems [University of Cincinnati (UC) Health and Cincinnati Children’s Hospital Medical Center]. We expect to identify, aggregate, uniformly represent, and make interoperable health care data from a variety of basic and translational science realms, clinical systems, and community sources. We also expect to broadly provide the means for all Cincinnati stakeholders to more effectively access and utilize these biomedical data, and to widely disseminate knowledge derived from such data that is relevant to improving health and health care. Finally, we expect to maximally increase literacy for understanding and using informatics approaches for all Cincinnati stakeholders, to enable our workforce and community to best utilize data for improving health and health care. The resulting programs will be accessible across our spectrum of stakeholders, and their products will be available to all community and CTSA participants. These programs will leverage existing data, technology, and people, and the programs will logically organize and build upon these components to synergistically and continually identify new data, analysis, and technology needs, and to cocreate new informatics solutions for our health care research concentrations. We will be building on our past accomplishments to strengthen this construct and address the challenges of efficient, universal access to biomedical data for knowledge engineering and application.