In a recent paper (soon available from IEEE TVCG), we present a systematic approach to the interactive visual analysis of heterogeneous data.  The data consists of interrelated parts that are given on spatial grids over time (e.g., the atmosphere and ocean part from a coupled climate model).  By integrating both data parts in a framework of coordinated multiple views (with linking and brushing), the joint investigation of features across the data parts is enabled.

An interface is constructed between the data parts that specifies (a) which grid cells in one part are related to grid cells in the other part, and vice versa, (b) how selections (in terms of feature extraction via brushing) are transferred between the two parts, and (c) how an update mechanism keeps the feature specification in both data parts consistent during the analysis.

We also propose strategies for visual analysis that result in an iterative refinement of features specified across both data parts. Our approach is demonstrated in the context of a complex simulation of fluid–structure interaction and a multi-run climate simulation.