Data Management and Analytics Core (DMAC)
Statement of Purpose
The Data Management and Analytics Core (DMAC) provides integrated data, biostatistics and informatics services and promotes collaboration across CLEAR programs through:
1) Communication across CLEAR's projects and cores
2) Management of complex data and use of analytical approaches designed to reduce bias/ confounding to ensure high-quality data and study integrity; and
3) Coordinating data sharing and interoperability by integrating geographical and health outcome data using Geographical Information Systems (GIS) to localize VOCs and promote synergistic scientific interactions.
The Work of DMAC
Exposure to volatile organic compounds (VOCs) is an important determinant of maternal-offspring health, with implications for preterm birth and associated adverse health outcomes. VOCs contaminate shallow soils and groundwater of post-industrial cities at Superfund, residential, commercial, and industrial properties, leading to exposures via vapor intrusion. The Center for Leadership in Environmental Awareness and Research (CLEAR) is dedicated to understanding and mitigating this serious environmental health problem. The Data Management and Analysis Core (DMAC) provides unified and integrated data and biostatistics/informatics services, while promoting scientific synergy across the CLEAR projects and cores; we achieve these goals by interfacing with the CLEAR cores to advance the two environmental science and engineering research projects (E1 and E2) and three biomedical research projects (B1B3).
The DMAC leverages over 25 years of experience serving as the Data Coordinating Center for multisite projects, including our flexible, centralized data management infrastructure that builds on standard operating procedures, our seamless collaboration with research scientists in designing cost- and time-efficient studies and having data collection based on "FAIR" guiding principles (Findable, Accessible, Interoperable, and Reusable), and our biostatistics and informatics expertise in analyzing complex data using cutting edge analytical methods in public health research. DMAC will ensure the success of CLEAR research projects by: 1) Customizing a web-accessible, centralized, and secured data management system to capture complex data to ensure data quality and timely data integration to foster data sharing and interoperability and 2) Catalyzing CLEAR growth by working with project and core leaders to develop new hypotheses about VOC exposures and adverse health effects based on integrated data analysis and by collaborating with the Research Experience and Training Coordination Core to train the next generation of environmental scientists in the principles of data collection and management.
DMAC Leadership
 | Mei Lu Ph.D. Director, Data Coordinating Center, Henry Ford Health System Co-Investigator, CLEAR |