Interactive Visual Analysis Promotes Exploration of Long-Term Ecological Data
Long-term ecological data are crucial in helping ecologists understand ecosystem function and environmental change. Nevertheless, this kind of data is often difficult to analyze because they are usually large, multivariate, and spatiotemporal. Although existing analysis tools such as statistical methods provide rigorous tests of pre-conceived hypotheses, they have limited capacity to provide a holistic overview of the data and to enable ecologists to explore data iteratively. Interactive visual analysis of data, when combined with the existing tools, is especially appealing for long-term ecological data because it offers the potential to allow ecologists to explore data directly, formulate and refine hypotheses quickly, and discuss their findings with others, prior to further statistical analysis. This working group focuses on information visualization (InfoVis) (display of abstract data, which don't have natural mappings to 2D or 3D space, such as counts of insects, cone production, or vegetation cover) rather than scientific visualization (SciVis) (rendering volumes or surfaces realistically, such as rendering of multiple layers of trees in a forest from LiDAR data). This working group will explore how interactive visual analysis of ecological data may help ecologists formulate hypotheses and structure analyses of long-term ecological data. We will demonstrate our web-based interactive visual analysis tool of several long-term data sets such as of moths [Miller], cone production [Franklin], and vegetation cover [Halpern, Pabst]. During the session, we will invite participants to experiment with the visualizations and give feedback regarding improvements to the tool. More information on the proposed working group can be found at: http://web.engr.oregonstate.edu/~pham/asm2012-visual-analysis/