Core B Data Management and Analysis (DMAC)

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ABSTRACT The unifying theme/goal of this P42 Superfund application is to develop a problem-focused (environmental lung injury secondary to heavy metal exposure), solution-oriented (biomarker discovery and therapeutic target identification in humans; mitigation/remediation in the air and soil) and integrated (bringing together biomedical scientists, engineers, ecologists, and social scientists) research plan. In order to achieve this goal, the UAB-SRP is comprised of five research projects and five Cores. These research projects have inherently complex data management and data analysis needs, in addition to the rigorous study design and data collection methodologies required by biomedical and human studies. The Data Management and Analysis Core (DMAC) provides centralized data management support for the research projects of the UAB-SRP and biostatistics support as well as data integration and collaborative research. The DMAC supports the UAB-SRP by providing database management that is in compliance with NIH regulations and innovative statistical support via seamless consultation. Through collaboration and consultation, the DMAC will provide UAB-SRP investigators with assistance and direction in their experimental design, data collection, data management, and interim and final statistical data analyses. The DMAC will lead the effort to design a biomedical and basic science research database with a user-friendly interface for data entry, data retrieval, and patient or sample tracking following the FAIR guiding principles for scientific data management and stewardship as well as data integration. We will also develop procedures to ensure data quality, integrity, confidentiality, and data sharing. The DMAC will be integrated into the UAB-SRP research projects, including the trainees, from study inception through data collection, data management, data integration, and analysis. Their close partnership with the Project Leaders at UAB will help ensure the research projects have proper biostatistics and data management support, are using appropriate and novel methods, and the study findings are correctly interpreted in scientific publications.