Motivating Science Scenario
MOTIVATING THE SCIENCE SCENARIO
Our INSPIRE effort is focused on how to do collaborative research via on-line software tools that can facilitate the sharing of complex data, models, ideas and research papers in earth and environmental science. Our motivating science goal is predicting the “age of water and carbon in lake-catchment systems. Lakes, reservoirs and wetlands are pervasive features of all catchments including those in the CZO domain, and our attention has focused on lake-catchment issues. Of necessity, our multi-disciplinary research collaborators from around the globe require a new way of carrying out their research, sharing their data, contributing to new theories and publishing their work. The capacity for: 1) starting communities around science questions, 2) dealing with new ideas, data and models, 3) organizing members around tasks, 4) encouraging contributions, 5) fostering commitment, and 6) supporting training, are some of the elements required. These principles are guiding the design of our organic data science framework and in the evolution of model and data services in support of hypothesis-driven research.
From the Earth and environemntal science perspective the research focuses on theoretical and experimental aspects of the isotopic “age” of water in lake-catchment systems. In this context, “age” is defined as the time since the water parcel and environmental tracer entered the system as precipitation. We note that each of our communities have developed an observing system for isotope ratios of carbon, oxygen and hydrogen but with very different science questions. In this research we are building a framework using models and data for defining a unified “isoscape” for the watershed-lake system, forming a richer and more collaborative shared research strategy. Our hypothesis is that the lake-catchment isoscape provides the experimental basis for predicting flow paths, residence times and the relative age of water in space and time, and that understanding these spatiotemporal patterns will provide a deeper understanding of fundamental biogeochemical processes including carbon and nitrogen cycling within the lake-catchment system. Details of the approach can be found in Duffy (2010) and at the Organic Data Science website (http://www.organicdatascience.org/index.php/Age_of_Water:_Example).
