Development of the Texas A&M Superfund Research Program Computational Platform for Data Integration, Visualization, and Analysis | Chapter individual record
abstract

The National Institute of Environmental Health Sciences (NIEHS) Superfund Research Program (SRP) aims to support university-based multidisciplinary research on human health and environmental issues related to hazardous substances and pollutants. The Texas A&M Superfund Research Program comprehensively evaluates the complexities of hazardous chemical mixtures and their potential adverse health impacts due to exposure through a number of multi-disciplinary projects and cores. One of the essential components of the Texas A&M Superfund Research Center is the Data Science Core, which serves as the basis for translating the data produced by the multi-disciplinary research projects into useful knowledge for the community via data collection, quality control, analysis, and model generation. In this work, we demonstrate the Texas A&M Superfund Research Program computational platform, which houses and integrates large-scale, diverse datasets generated across the Center, provides basic visualization service to facilitate interpretation, monitors data quality, and finally implements a variety of state-of-the-art statistical analysis for model/tool development. The platform is aimed to facilitate effective integration and collaboration across the Center and acts as an enabler for the dissemination of comprehensive ad-hoc tools and models developed to address the environmental and health effects of chemical mixture exposure during environmental emergency-related contamination events.

author list (cited authors)
Miikherjee, R., Onel, M., Beykal, B., Szafran, A. T., Stossi, F., Mancini, M. A., ... Pistikopoulos, E. N.
publication date
2019
publisher
Elsevier Publisher
keywords
  • Collaborative Networks
  • Data Analytics
  • Data Integration
  • Statistical Analysis