Using Layout Stitching to create deterministic Local Graph Layouts

Abstract

Dynamic graph layouts are often used to position nodes in local views of large graphs. These layouts can be optimized to minimize changes when navigating to other parts of the graph. Dynamic graph layout techniques do not, however, guarantee that a local layout is recognizable when the user visits the same area twice. In this paper we present a method to create stable and deterministic layouts of dynamic views of large graphs. It is based on a well-known panorama-stitching algorithm from the image processing domain. Given a set of overlapping photographs it creates a larger panorama that combines the original images. In analogy to that our algorithm stitches pre-computed layouts of subgraphs to form a larger, single layout. This deterministic approach makes structures and node locations persistent which creates identical visual representations of the graph. This enables the user to recognize previously encountered parts and to decide whether a certain part of a dataset has already been explored before or not.