Deterministic Local Layouts through High-Dimensional Layout Stitching

In this paper we present a layout technique for dynamic views of large static graphs. It aims to minimize changes between two consecutive frames and most importantly, it is deterministic. First, a set of small layout patches is pre-computed. Then, depending on the users view focus, a subset of these patches is selected and connected to generate the final layout. In contrast to the state-of-the-art approach that operates in the 2D screen space only, we perform this process in high-dimensional space before projecting the results into the 2D plane. This gives additional degrees of freedom and consequently a smoother transition process between two consecutive frames. Whenever the user visits an area of the graph for a second time, the layout will still look the same. This enables the user to recognize areas that have already been explored and thus preserve the mental map

Deterministic local layouts through high-dimensional layout stitching

In this paper we present a layout technique for dynamic views of large static graphs. It aims to minimize changes between two consecutive frames and most importantly, it is deterministic. First, a set of small layout patches is pre-computed. Then, depending on the users view focus, a subset of these patches is selected and connected to generate the final layout. In contrast to the state-of-the-art approach that operates in the 2D screen space only, we perform this process in highdimensional space before projecting the results into the 2D plane. This gives additional degrees of freedom and consequently a smoother transition process between two consecutive frames. Whenever the user visits an area of the graph for a second time, the layout will still look the same. This enables the user to recognize areas that have already been explored and thus preserve the mental map