Edgeless Graph: A New Graph-Based Information Visualization Technique

Abstract

Information visualization is the study of visual representations of abstract data in order to strengthen the human understanding of the data. Graph visualization is one of the subfields of information visualization. It is used for the visualization of structured data, i.e. for inherently related data elements. In the traditional graph visualization techniques, nodes are used to represent data elements, whereas edges are used to represent relations. In this paper, our focus is on the representation of structured data. According to us, key challenges for any graph-based visualization technique are related to edges. Some of them are planar representation, minimization of edge crossing, minimizing the number of bends, distinguish between the vertices and the edges, etc. In this paper, we propose two methods that use the same underlying idea: Assignment of unique label to each vertex of the graph and remove all the edges. Nodes are adjacent if and only if their corresponding labels are disjoint. Our proposed representations do not have edges so we do not need to consider the challenges related to edges that is the biggest advantage. The algorithm for obtaining valid labelling as well as procedures related to dynamic changes (addition/removal of edges and/or vertices) is explained in detail. The space complexities of the proposed methods are O($n^ 2$) and O($n^3$) where n denotes the number of nodes. Application of our proposed methods in the analysis of a social network site is also demonstrated. Characteristics of these methods are highlighted along with possible future modifications.