Core B: Data Management

PROJECT SUMMARY/ABSTRACT – Core B (Data Management Core) Data and derived knowledge are valuable by-products of scientific investigations and are crucial in verifying and reproducing study outcomes. Prioritizing the development of comprehensive data management infrastructure is of utmost importance in today's scientific research environment, given that efficiently handled and readily

available data can enable the validation and replication processes. Managing sensitive information requires rigorous data integrity and strict security. The Data Management Core aims to design a secure, scalable, and redundant data storage and transfer infrastructure to serve as the central knowledge vault for all research

projects and cores to promote data integrity throughout the data lifecycle, including data collection, data storage, statistical analysis and interpretation, and data transmission and dissemination. During Aim 1, we will establish a robust data management system for intuitive and secure data storage derived from Research Projects 1-5 and

Cores C, D, and E. We will implement several levels of security to control access to the data located behind Galveston National Lab, individual cores, and projects' vaults. The system will include data dictionaries, standardized templates, project-specific and core-specific storage rules, and dashboards. In Aim 2, we will

implement data quality and security control mechanisms for all components of the data management system for external data sharing and results presentation. The established system will monitor data accuracy and completeness and ensure the system operates according to established procedures and data standards required

by the REVAMPP Network Coordination and Data Sharing Center. In Aim 3, we will provide data analysis and bioinformatics support for robust and unbiased results. Experienced data scientists will analyze study designs, provide independent statistical analysis of the derived data, and set up steps for automatic data QC monitoring

collection and preservation of generated metadata for each individual file. During this Aim, we will also promote data integrity for product development following ALCOA Plus principles for assuring data quality and integrity. The Aims will be accomplished by a highly experienced data science team working together for more than a

decade on industrial and academic projects handling highly nationally sensitive data generated by Nuclear Power Plants as private contractors, as well as routine processing of Petabytes of clinical health records data worldwide on behalf of UTMB. Core B will be managed by an expert in bioinformatics, data engineering, and data mining

focused on raising translational data standards by developing and promoting multi-omics projects and leading and teaching clinical data science.