Paul Mutton

Visualization of semantic metadata and ontologies

Implicit information embedded in semantic Web graphs, such as topography, clusters, and disconnected subgraphs is difficult to extract from text files. Visualizations of the graphs can reveal some of these features, but existing systems for visualizing metadata focus on aspects other than understanding the greater structure. We present a tool for generating visualizations of ontologies and metadata by using a modified spring embedder to achieve an automatic layout. Through a case study using a mid-sized ontology, we show that interesting information about the data relationships can be extracted through our visualization of the physical graph structure.

Inferring and visualizing social networks on Internet relay chat

Internet relay chat is a system that allows groups of people to collaborate and chat from anywhere in the world. Clearly defined by several RFC documents, it is arguably the most standard real-time chat system currently in use. This work describes a method of inferring the social network of a group of IRC users in a channel. An IRC bot is used to monitor a channel and perform a heuristic analysis of events to create a mathematical approximation of the social network. From this, the bot can produce a visualization of the inferred social network on demand. These visualizations reveal the structure of the social network, highlighting connectivity, clustering and strengths of relationships between users. Animated output allows viewers to see the evolution of the social network over time. Some novel ideas for future work are discussed, showing other useful applications of this system.

Drawing graphs in Euler diagrams

We describe a method for drawing graph-enhanced Euler diagrams using a three stage method. The first stage is to lay out the underlying Euler diagram using a multicriteria optimizing system. The second stage is to find suitable locations for nodes in the zones of the Euler diagram using a force based method. The third stage is to minimize edge crossings and total edge length by swapping the location of nodes that are in the same zone with a multicriteria hill climbing method. We show a working version of the software that draws spider diagrams. Spider diagrams represent logical expressions by superimposing graphs upon an Euler diagram. This application requires an extra step in the drawing process because the embedded graphs only convey information about the connectedness of nodes and so a spanning tree must be chosen for each maximally connected component. Similar notations to Euler diagrams enhanced with graphs are common in many applications and our method is generalizable to drawing Hypergraphs represented in the subset standard, or to drawing Higraphs where edges are restricted to connecting with only atomic nodes.

Dynamic Euler Diagram Drawing

In this paper we describe a method to lay out a graph enhanced Euler diagram so that it looks similar to a previously drawn graph enhanced Euler diagram. This task is nontrivial when the underlying structures of the diagrams differ. In particular, if a structural change is made to an existing drawn diagram, our work enables the presentation of the new diagram with minor disruption to the users mental map. As the new diagram can be generated from an abstract representation, its initial embedding may be very different from that of the original. We have developed comparison measures for Euler diagrams, integrated into a multicriteria optimizer, and applied a force model for associated graphs that attempts to move nodes towards their positions in the original layout. To further enhance the usability of the system, the transition between diagrams can be animated

Spring embedder preprocessing for WWW visualization

We present a preprocessor for the spring embedder graph drawing method and show its use in speeding up the automatic layout of three-dimensional visualizations of WWW sites. Spring embedding is a widely used method for visualizing the connections in WWW maps, as it can typically produce a reasonable layout for most general graphs. However, the technique does not scale well and to improve the performance when dealing with large graphs various optimisations have been developed. Our preprocessor is a new optimization method that attempts to obtain a reasonably good initial drawing to be then used by the spring embedder. This initial drawing has edge lengths that are approximately equal along with a minimum node separation. This produces a layout that is closer to the final drawing than a random scattering of nodes and so allows fewer invocations of the spring embedder to produce an equally stable drawing.

Spring-Embedded Graphs for Semantic Visualization

In this chapter we have presented a graph drawing system for visualizing ontologies and collections of instance data on the Semantic Web. Related entities are drawn close to each other with a directed edge to symbolize the relationship, and the system is also capable of producing sensible automatic layouts of disconnected graphs. Through two case studies involving a real, deployed ontology and an aggregated set of instance data, we show how patterns about the underlying structure are more easily understood through the graph drawing than through text or other types of visual displays.

Visualizing weighted edges in graphs

We introduce a new edge length heuristic that finds a graph layout where the edge lengths are proportional to the weights on the graph edges. The heuristic can be used in combination with the spring embedder to produce a compromise between a drawing with an accurate presentation of edge length and a drawing with good general comprehensibility. We describe our preliminary investigations in combining the two methods so that a user can tune their preference and demonstrate the effectiveness of the system on both randomly generated graphs and graphs representing Web page similarity data.

Demonstration of a Preprocessor for the Spring Embedder

Spring embedding is a widely used method for producing automated layouts of graphs. We present a preprocessor that improves the performance of the classical spring embedder, which can be used in conjunction with other optimization and approximation techniques. It creates an initial graph layout with edge lengths that are approximately equal and with a minimum node separation from which the spring embedder typically needs far fewer iterations to produce a well laid out graph.