Technological advances in hardware, storage, and software have significantly increased scientists’ ability to find new ways of generating and using data, thus creating new possibilities for conducting research to address the complex challenges of environmental contamination and ecological risk assessment. Conducting scientific research through high-resolution data acquisition, data mining, and visualization enables scientists to better understand the transient nature of aquatic data and pollutant movement across various boundaries.
However, data-intensive science requires significant collaboration between environmental and computer scientists. This collaboration is becoming increasingly critical in finding better and more effective ways to research, discover and solve problems. The research conducted by this Subproject will facilitate such collaboration and support CREST CAChE researchers to better detect and understand the sources, transport, transformation and ecosystem responses to contaminants, pollutants and other natural stressors in the aquatic systems of south Florida.
Using a data-intensive approach, CREST CAChE researchers in Subproject 3 will be able to:
Our team develops methods to enable data mining and synthesis across large, complex data sets. This allows us to conduct holistic effects-assessments for understanding South Florida’s fragile aquatic ecosystem and to convey environmental impacts to policy and decision makers.
Shu-Ching Chen, Co-Lead: multimedia data mining, analytics
Marcus Cooke, Co-Lead: biomonitoring genotoxin exposure
Jose Eirin-Lopez: genetic and epigenetic adaptation
Quentin Felty: estrogen-mimicking endocrine disruptors
Rudolph Jaffe: environmental organic geochemistry
Assefa Melesse: eco-hydrological and geospatial modeling
Gary Rand: ecotoxicology and risk assessment
Shahin Vassigh: data visualization and education