Environmental Science Subproject
From Minas
Team
- Craig Tweedie (Lead, ES)
- Vladik Kreinovich (CS)
Goal
To address the challenge of optimizing data streams and sensor arrays in ecological and environmental networks through case studies targeting improved characterization of environmental phenomena and processes.
Summary
In light of dramatic environmental change that is affecting the sustainability of ecosystem goods and services globally, there is an urgent need to predict the future state of the Earth System and understand how humans will need to adapt. This urgency is driving paramount programmatic and operational changes in the ecological and environmental sciences. Increasingly, the environmental sciences are: (1) Shifting towards more data-driven science, where researchers need to trust the integrity of data collected by other researchers and multidisciplinary scientific networks to answer ‘BIG’ picture questions; (2) There is an increased utilization of advanced field-based instrument technologies; and subsequently, (3) The need for optimizing data streams, instituting quality assurance procedures, and managing, archiving and integrating large volumes of multivariate data from field-based and other instrument platforms (e.g., satellite) has increased dramatically. Clearly, significant advances in the environmental sciences will be made through interdisciplinary collaborations with the computer science and computational mathematics, adapting and reusing CI from established efforts in other disciplines such as the geosciences, and training a new generation of CI-savvy environmental scientist.
