Child Health Exposure Analysis Repository Data Science

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Research Areas: Health Informatics, Semantic eScience, Data Science, Web Science
Principal Investigator: Deborah L. McGuinness
Co Investigator: Kristin Bennett
Concepts: Data Management, Ontology, Health informatics, Linked Data
Description:
Child Health Exposure Analysis Repository Data Science Semantics Meeting Notes


The United States’ National Institute of Environmental Health Sciences has established an infrastructure, the Children’s Health Exposure Analysis Resource (CHEAR), to provide the extramural research community access to laboratory and statistical analyses aimed at adding or expanding the inclusion of environmental exposures in their research. The CHEAR project is a $50 million multiunit infrastructure composed of a coordinating center, a network of laboratories and a data center tasked to provide researchers access to comprehensive exposure assessment for NIH funded studies of children’s health. The CHEAR Data Repository, Analysis and Science Center (Data Center) is located at the Icahn School of Medicine at Mount Sinai in collaboration with Rensselaer Polytechnic Institute. The goal of the data center is to catalyze new scientific insight from the co-location, integration and advanced statistical and data science analysis of multimodal data sets. The data center provides the intellectual and logistical support for the validation, interpretation, curation, and maximum reuse of data generated by the laboratory network. We aim to provide access to tools and services that incorporate and extend exposure analysis on an exposome scale (i.e., to study complex environmental influences on health) by providing a strong data, knowledge, and analytic infrastructure. We are developing semantic infrastructure for support in consistent modeling, unambiguous interpretation, and enhanced integration. For the investigators that utilize CHEAR for studies of children’s environmental health using the data generated within and outside the network, the Data Center provides: 1) data repository and management; 2) statistical consultation and analysis services; 3) collaborative research support; 4) statistical and analytical methods development; and 5) data science resources, including semantic infrastructure and services powered by a family of child health exposure ontologies.



The RPI portion of the CHEAR effort is the Data Science portion of the project. Prof. McGuinness leads this effort. The focus is on the development of ontologies to support research on exposure science and child health. It also focuses on tools and infrastructure for building and maintaining a knowledge graph of related content.



Previous meeting notes

Meeting Note 02/12

https://docs.google.com/document/d/1BVfsL6sjAEUxJJsMAEnoIQi092Lw5O64hUJn...


Meeting Note 02/05

https://docs.google.com/document/d/1OtEROEEktrufsSx-kr20uY_VvA_vohoHMP15...