Visual interactive support for selecting scenarios from time-series ensembles

摘要

Stochastic programming approaches to solve the scenario reduction problem have become invaluable in the analysis and behavior prediction of dynamic systems. However, such techniques often fail to take advantage of the user's own expertise about the problem domain. This work provides visual interactive support to assist users in solving the scenario reduction problem with time-series data. We employ a series of time-based visualization techniques linked together to perform the task. By adapting a multidimensional projection algorithm to handle temporal data, we can graphically present the evolution of the ensemble. We also propose to use cumulative bump charts to visually compare the ranks of distances between the ensemble time series and a baseline series. To evaluate our approach, we developed a prototype application and conducted observation studies with volunteer users of varying backgrounds and levels of expertise. Our results indicate that a graphical approach to scenario reduction may result in a good subset of scenarios and provides a valuable tool for data exploration in this context. The users liked the interaction mechanisms provided and judged the task to be easy to perform with the tools provided.