A Layered Approach to Lightweight Toolchaining in Visual Analytics

The ongoing proliferation and differentiation of Visual Analytics to various application domains and usage scenarios has also resulted in a fragmentation of the software landscape for data analysis. Highly specialized tools are available that focus on one particular analysis task in one particular application domain. The interoperability of these tools, which are often research prototypes without support or proper documentation, is hardly ever considered outside of the toolset they were originally intended to work with. To nevertheless use and reuse them in other settings and together with other tools, so as to realize novel analysis procedures by using them in concert, we propose an approach for loosely coupling individual visual analytics tools together into toolchains. Our approach differs from existing such mechanisms by being lightweight in realizing a pairwise coupling between tools without a central broker, and by being layered into different aspects of such a coupling: the usage flow, the data flow, and the control flow. We present a model of this approach and showcase its usefulness with three different usage examples, each focusing on one of the layers.