Redivis

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Redivis is an online data platform designed to streamline the storage, distribution, and analysis of research data. It offers a high-performance, web-based interface that enables researchers to work with diverse datasets, including large-scale and high-risk data, without the need for extensive infrastructure investments. By integrating data hosting with analytical tools, Redivis facilitates collaborative and reproducible research, aligning with FAIR data practices to ensure data is findable, accessible, interoperable, and reusable. Key Features and Functionality: - Dataset Discovery: Researchers can easily discover and preview available datasets, viewing metadata and summary statistics to assess relevance. - Integrated Analysis Tools: The platform supports analyses using SQL, Python, R, Stata, and SAS, alongside a no-code graphical interface, enabling flexible data manipulation and visualization. - Collaboration and Reproducibility: Real-time collaboration features allow researchers to share work seamlessly, with automatic version control ensuring reproducibility and compliance with data sharing requirements. - Secure Data Hosting: Redivis is designed to host high-risk data, utilizing HIPAA and FedRAMP certified Google Cloud infrastructure, and has undergone thorough security audits, including SOC2 Type 2. - Flexible Access Controls: Administrators can configure access systems to distribute restricted datasets through automatic authentications, custom forms, group status, and direct sharing. Primary Value and Problem Solved: Redivis addresses the challenges researchers face in managing and analyzing large and sensitive datasets by providing an integrated platform that combines secure data hosting with powerful analytical tools. It eliminates the need for complex infrastructure setups, reduces the time required for data processing, and enhances collaboration among researchers. By aligning with FAIR data practices, Redivis ensures that data is not only accessible but also reusable, promoting transparency and reproducibility in research. This comprehensive approach empowers researchers to focus on deriving insights from their data, accelerating the pace of scientific discovery.