Guy Melançon

Graph visualization and navigation in information visualization: A survey

This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as Web browsing, state-transition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs is often a crucial part of an application. Information visualization has specific requirements, which means that this survey approaches the results of traditional graph drawing from a different perspective.

Multiscale visualization of small world networks

Many networks under study in information visualization are small world networks. These networks first appeared in the study of social networks and were shown to be relevant models in other application domains such as software reverse engineering and biology. Furthermore, many of these networks actually have a multiscale nature: they can be viewed as a network of groups that are themselves small world networks. We describe a metric that has been designed in order to identify the weakest edges in a small world network leading to an easy and low cost filtering procedure that breaks up a graph into smaller and highly connected components. We show how this metric can be exploited through an interactive navigation of the network based on semantic zooming. Once the network is decomposed into a hierarchy of sub-networks, a user can easily find groups and subgroups of actors and understand their dynamics.

Software components capture using graph clustering

We describe a simple, fast computing and easy to implement method for finding relatively good clusterings of software systems. Our method relies on the ability to compute the strength of an edge in a graph by applying a straightforward metric defined in terms of the neighborhoods of its end vertices. The metric is used to identify the weak edges of the graph, which are momentarily deleted to break it into several components. We study the quality metric MQ introduced by S. Mancoridis et al. (1998) and exhibit mathematical properties that make it a good measure for clustering quality. Letting the threshold weakness of edges vary defines a path, i.e. a sequence of clusterings in the solution space (of all possible clustering of the graph). This path is described in terms of a curve linking MQ to the weakness of the edges in the graph.

BUBBLE TREE DRAWING ALGORITHM

In this paper, we present an algorithm, called Bubble Tree, for the drawing of general rooted trees. A large variety of algorithms already exists in this field. However, the goal of this algorithm is to obtain a better drawing which makes a trade off between the angular resolution and the length of the edges. We show that the Bubble Tree drawing algorithm provides a planar drawing with at most one bend per edge in linear running time.

Tree Visualisation and Navigation Clues for Information Visualisation

Information visualisation often requires good navigation aids on large trees, which represent the underlying abstract information. Using trees for information visualisation requires novel user interface techniques, visual clues, and navigational aids. This paper describes a visual clue: using the so‐called Strahler numbers, a map is provided that indicates which parts of the tree are interesting. A second idea is that of “folding” away subtrees that are too “different” in some sense, thereby reducing the visual complexity of the tree. Examples are given demonstrating these techniques, and what the further challenges in this area are.

Density functions for visual attributes and effective partitioning in graph visualization

Two tasks in graph visualization require partitioning: the assignment of visual attributes and divisive clustering. Often, we would like to assign a color or other visual attributes to a node or edge that indicates an associated value. In an application involving divisive clustering, we would like to partition the graph into subsets of graph elements based on metric values in such a way that all subsets are evenly populated. Assuming a uniform distribution of metric values during either partitioning or coloring can have undesired effects such as empty clusters or only one level of emphasis for the entire graph. Probability density functions derived from statistics about a metric can help systems succeed at these tasks.

Latour - a tree visualisation system

This paper presents some of the most important features of a tree visualisation system called Latour, developed for the purposes of information visualisation. This system includes a number of interesting and unique characteristics, for example the provision for visual cues based on complexity metrics on graphs, which represent general principles that, in our view, graph based information visualisation systems should generally offer.

DAG drawing from an information visualization perspective

When dealing with a graph, any visualization strategy must rely on a layout procedure at least to initiate the process. Because the visualization process evolves within an interactive environment the choice of this layout procedure is critical and will often be based on efficiency. This paper compares two popular layout strategies, one based on the extraction of a spanning tree, the other based on edge crossing minimization of directed acyclic graphs. The comparison is made based on a large number of experimental evidence gathered through random graph generation. The main conclusion of these experiments is that, contrary to the popular belief, usage of edge crossing minimization algorithms may be extremely useful and advantageous, even under the heavy requirements of information visualization.

Tool for metabolic and regulatory pathways visual analysis

The research activity in bio-informatics has now reached a new phase, called post-genomics. It aims at the description of gene products as part of global processes in cells. In this research area, the various tasks to be conducted by biologists call for methods inspired from knowledge extraction and representation, and from information visualization. We describe a system devoted to the visualization of metabolic pathways. This set of biological reactions describe product transformations in the cell. The analysis of various pathway visualization tools led us to qualitative assertions. First, it is essential that the visualization environment preserves the drawing conventions borrowed from biology. Second, it seems important to offer an environment in which the user can navigate while preserving cognitive continuity. Our system focuses on these interactive and navigational issues. It offers mechanisms such as interactive color mapping and semantic zooming of pathways through various levels of details. Our tool also aims at helping biologists in the analysis of experimental results measuring gene expression in various biological processes. Although our efforts have focused on the visualization of metabolic pathways, our system should help to visualize, analyze and discover other types of biological pathways (e.g. regulatory pathways).

Une approche MDS hybride pour l'exploration visuelle interactive

The paper presents a novel technique for the exploration of an information space where elements are associated with a taxonomy and where each element has an associated attribute vector. A hybrid MDS method is at the core of the method. The underlying algorithm embeds elements in the 2D plane, trying to place similar elements close to one another. The dynamic character of the algorithm makes it a well suited tool for interactive exploration. Our first results presented here confirm our approach as a tool relevant for finding merging opportunities between companies based on various economic characteristics.