Slycat™ is a web-based system for analysis of large, high-dimensional data, developed to provide a collaborative platform for remote analysis of data ensembles. An ensemble is a collection of data sets, typically produced through a series of related simulation runs. More generally, an ensemble is a set of samples, each consisting of the same set of variables, over a shared high-dimensional space describing a particular problem domain. Ensemble analysis is a form of meta-analysis that looks at the combined behaviors and features of a group of simulations in an effort to understand and describe the underlying domain space. For instance, sensitivity analysis uses ensembles to examine how simulation input parameters and simulation results are correlated. By looking at groups of runs as a whole, higher level patterns can be seen despite variations in the individual runs.
The Slycat™ system integrates data management, scalable analysis, and visualization via commodity web clients using a multi-tiered hierarchy of computation and data storage. Analysis models are computed local or on the Slycat™ server, and model artifacts are stored in a project database. These artifacts are the basis for visualizations that are delivered to users’ desktops through ordinary web browsers. Slycat™ currently provides two types of analysis: canonical correlation analysis (CCA) to model relationships between inputs and output metrics, and time series analysis featuring clustering and comparative visualization of waveforms.