PROJECT SUMMARY – Data Management and Analysis Core (DMAC) The Data Management and Analysis Core (DMAC) provides state-of-the-art data management support and cutting-edge statistical and geospatial analysis assistance for the Research Projects and Cores of UNM METALS Phase 2 Center. The DMAC will be co-directed by Li Luo and Yan Lin with complementary and collaborative experience in biostatistical and geospatial analyses to manage all aspects of the Core. DMAC members include eight quantitative scientists with complementary expertise in data management and statistical and geospatial analysis for a variety of scientific domains. DMAC members have backgrounds and expertise in modern data management, biostatistical methods, geospatial analysis, Bayesian methods, causal inference, as well as analyses of data from basic science, translational research, population studies, and environmental health disparities research. The team members have collaborated for over five years on multiple environmental health projects, and have streamlined the workflow from data collection, quality control, statistical and geospatial analysis support, and methodology developments to enhance the analysis of complex metal mixtures. The DMAC will implement and provide data management support that is compliant with four foundational principles: Findability, Accessibility, Interoperability, and Reusability (FAIR). DMAC will develop and utilize a centralized data repository that connects different types of data storage systems and FAIR platforms to faciliate data sharing and integration. The data and analytical support provided by the Core will contribute to many aspects of the research process including, but not limited to, efficient study design, appropriate monitoring of data safety, enhanced data management capacity, state-of-the-art statistical and geospatial analyses, assistance in the development of study protocols and contract proposals, as well as sample size and power calculations. In addition, DMAC members will assist Research Projects and Cores in preparing summary analytical reports and manuscripts. Furthermore, DMAC will develop integrated statistical and geospatial modeling to refine the risk classification based on study participants’ comprehensive environmental exposure profile, and to understand the mechanisms of the adverse effects of toxic exposures on the health outcomes mediated through intermediate biomarkers. Core faculty will also provide educational opportunities to Center investigators and trainees through lectures, workshops, and hands-on training. The collaborative efforts of Core members will contribute not only to effectively pursuing hypothesis-driven research questions but also to developing novel research questions and methods for complex analyses of large datasets. Core members will work closely with METALS Research Projects and Cores to develop and integrate new methodologies into various research projects. The DMAC is well-positioned to promo...