Critical to the success of the CHEAR Network is the development and management of a comprehensive data repository to facilitate maximum analysis, sharing, and interoperability of exposure data with data generated within and outside the network with the overall goal of accelerating children's environmental health research across the community; The goal of the Data Repository and Management Core is to store and manage data and facilitate activities to be completed by the Statistical Analysis and Methods Development Resource and Data Science Resource of the Data Center. Thus, the Core is designed to maximize data sharing and reuse of the large volume and heterogeneous types of data being collected. The Core will work with the Resource components of the Data Center to ensure appropriate data and metadata standards are employed. The CHEAR Data Center will establish and maintain a data repository and data management infrastructure to support collection, curation, display, storage, retrieval, integration, interoperability, and reuse of data produced by the CHEAR Laboratory Network. Mount Sinai, and our team specifically, have extensive experience at the intersection of computational and data science and translational biomedical research for the national community. We also have extensive experience with occupational health data sets. We manage significant data-rich resources for basic and translational science researchers at Mount Sinai and their colleagues at institutions across the world. We also work closely with clinicians who need data and data science expertise to improve healthcare delivery. Our information technology professionals are specialized in healthcare and scientific research, which enables a productive, interdisciplinary environment to accelerate scientific discovery. We maintain all of these services with high availability through industry standard processes and technologies including development server sandboxes for prototyping and pre-production staging servers for new testing new software.
A well-designed epidemiologic study of children's health will be able to address the hypotheses the study is funded to investigate, but by accessing the resources of the CHEAR Data Center, studies will be able to exceed what they are funded to do and potentially accomplish research that was previously thought infeasible or too costly. Through the use of the CHEAR Data Center, investigators will be able to increase their productivity and advance the scientific community's ability to examine the environment on an exposome scale. Pooling multiple datasets in the Data Center repository in a cohesive and integrated manner will be made possible through the language standards we develop.
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