Subproject 3: Data Synthesis & Visualization

Data Analytics for Effects Assessment and Decision Making

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:

  1. Provide detailed characterization and measurement of the environmental pollutants
  2. Improve predictive abilities on effects of pollutants and address future water quality issues
  3. Explore, manipulate and visualize data; thus collaborate more effectively for risk assessment
  4. Conduct literature mining on the nature of contaminants and access relevant environmental information rapidly
  5. Communicate more effectively with decision makers and other stakeholders.

Goal

The ultimate goal of Subproject 3 is to support data-intensive research on aquatic chemistry and the environment by developing transformative and scalable methods for data mining and management, advanced computational modeling, and visualization.

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.

The Team

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

Mark Finlayson:

Mike Heithaus:

Rudolf Jaffé: environmental organic geochemistry

Tao Li:

Assefa Melesse: eco-hydrological and geospatial modeling

Gary Rand: ecotoxicology and risk assessment

Shahin Vassigh: data visualization and education