REDCap is a metadata-driven software tool and workflow methodology designed for rapid development and deployment of electronic data capture (EDC) tools to support clinical and translational research. It provides intuitive, reusable tools for collecting, storing, and disseminating clinical and translational research data. Key features include collaborative data access, user authentication, intuitive case report forms (CRFs), real-time data validation, data attribution, audit capabilities, protocol document storage, central data storage, data export functions, and data import functions. REDCap supports 286 translational research projects across a growing collaborative network of 27 active partner institutions. REDCap was initially developed at Vanderbilt University and now has collaborative support from a consortium of domestic and international partners. The system uses a single study metadata table referenced by presentation-level operational modules, allowing efficient development with minimal resource investment beyond creating a single data dictionary. The workflow process enables research teams to autonomously develop study-related metadata efficiently. The REDCap user interface provides an intuitive method for securely and accurately inputting data. It includes features such as data validation, data export and import tools, data comparison, data logging, file repository, and data dictionary. The architecture uses PHP and JavaScript with a MySQL database engine, allowing for modest hardware and software requirements. REDCap has been successfully deployed at Vanderbilt University and Meharry Medical College, supporting 204 projects, including 156 active and 48 in prototype status. The system has demonstrated active use in clinical research with 17,959 subjects and 722 registered end-users. The consortium approach allows for the addition of new modules, documentation, and support processes, with software and support provided at no charge to institutions. REDCap's flat-table structure is efficient for study setup and data export but may be inefficient for data storage. The metadata creation process is fast and flexible but does not encourage data naming standards. The system is cost-effective for academic research environments, offering a rapid-development and flexible informatics approach for supporting translational research. The project benefits from a consortium of academic institutions and encourages others to join the group.REDCap is a metadata-driven software tool and workflow methodology designed for rapid development and deployment of electronic data capture (EDC) tools to support clinical and translational research. It provides intuitive, reusable tools for collecting, storing, and disseminating clinical and translational research data. Key features include collaborative data access, user authentication, intuitive case report forms (CRFs), real-time data validation, data attribution, audit capabilities, protocol document storage, central data storage, data export functions, and data import functions. REDCap supports 286 translational research projects across a growing collaborative network of 27 active partner institutions. REDCap was initially developed at Vanderbilt University and now has collaborative support from a consortium of domestic and international partners. The system uses a single study metadata table referenced by presentation-level operational modules, allowing efficient development with minimal resource investment beyond creating a single data dictionary. The workflow process enables research teams to autonomously develop study-related metadata efficiently. The REDCap user interface provides an intuitive method for securely and accurately inputting data. It includes features such as data validation, data export and import tools, data comparison, data logging, file repository, and data dictionary. The architecture uses PHP and JavaScript with a MySQL database engine, allowing for modest hardware and software requirements. REDCap has been successfully deployed at Vanderbilt University and Meharry Medical College, supporting 204 projects, including 156 active and 48 in prototype status. The system has demonstrated active use in clinical research with 17,959 subjects and 722 registered end-users. The consortium approach allows for the addition of new modules, documentation, and support processes, with software and support provided at no charge to institutions. REDCap's flat-table structure is efficient for study setup and data export but may be inefficient for data storage. The metadata creation process is fast and flexible but does not encourage data naming standards. The system is cost-effective for academic research environments, offering a rapid-development and flexible informatics approach for supporting translational research. The project benefits from a consortium of academic institutions and encourages others to join the group.