Figure 2

Conceptual overview of iVUN functionality. The central component of iVUN is the graph view of the BRN, with which all static and dynamic attributes are associated. From a modeling perspective, this graph has several layers. The dynamic attributes $v$, $x$, and $y$ are associated with the flux layer (links), state layer (nodes), and the output layer (a subset of nodes), respectively. These layers are connected, i.e., an output (e.g., $y_1$) is associated with a set of states (here, $y_1$ represents the sum of $x_1$, $x_2$, and $x_3$) and each state depends on one or more fluxes (here, $x_1$ depends on $v_1$ and $v_2$). Conversely, a flux v _j influences one or more states $x_i$, which may be part of one or more outputs $y_k$. To obtain an overview of the attribute dynamics, iVUN can map the numerical value of attributes to the color of the respective components in the BRN and animate the time dependence (illustration: top right). In addition, line plots can be used to gain further insight into the dynamic behavior and to compare time series. iVUN supports within- experiment comparison (line plots: left) and between-experiment comparison (line plot: top center) of time series. Besides the analysis of dynamics, the analysis of statistics of single attributes (bottom center) and correlations (right) is supported at different levels of granularity. In this conceptual overview, colors are used to identify the dynamic attributes in the line plots as well as the static parameters in the statistic and correlation views with the corresponding components of the graph. In the actual visual analytics tool iVUN, correspondence of elements in the different views is shown by brushing and linking as well as labeling. In this way, color can be used for encoding of other values. Screenshot of iVUN in action can be found at www.vis.uni-stuttgart.de/iVUN.