Visual Exploration of Alternative Taxonomies through Concepts

A graphical user interface is presented that allows users of taxonomic data to explore concept relationships between conflicting but related taxonomic classifications. Ecological analyses that use taxonomic metadata depend on accurate naming of specimens and taxa, and if the metadata involves several taxonomies, care has to be taken to match concepts between them. To perform this accurately requires expert-defined concept relationships, which are more complex yet more representative than the simple one-to-one mappings found through simple name matching, and can accommodate nomenclatural changes and differences in classification technique (cf ‘lumpers’ versus ‘splitters’). In the SEEK-Taxon (Scientific Environment for Ecological Knowledge) project we aim to help users of taxonomic datasets untangle and understand these relationships through a prototype visual interface which graphically displays these relationship structures, allowing users to comprehend such information and more accurately name their data

Exploring multiple trees through DAG representations

We present a Directed Acyclic Graph visualisation designed to allow interaction with a set of multiple classification trees, specifically to find overlaps and differences between groups of trees and individual trees. The work is motivated by the need to find a representation for multiple trees that has the space-saving property of a general graph representation and the intuitive parent-child direction cues present in individual representation of trees. Using example taxonomic data sets, we describe augmentations to the common barycenter DAG layout method that reveal shared sets of child nodes between common parents in a clearer manner. Other interactions such as displaying the multiple ancestor paths of a node when it occurs in several trees, and revealing intersecting sibling sets within the context of a single DAG representation are also discussed

A survey of multiple tree visualisation.

This paper summarises the state-of-the-art in multiple tree visualisations. It discusses the spectrum of current representation techniques used on single trees, pairs of trees and finally multiple trees, in order to identify which representations are best suited to particular tasks and to find gaps in the representation space where opportunities for future multiple tree visualisation research may exist. The application areas from where multiple tree data are derived are enumerated, and the distinct structures that multiple trees make in combination with each other and the effect on subsequent approaches to their visualisation are discussed, along with the basic high-level goals of existing multiple tree visualisations

An Investigation into Visual Graph Comparison

Information Visualisation is extensively used in single graph analysis. However, relatively little work has been done in the field of graph comparison. This work examines and compares the use of two standard graph representations in this area, the Node-Link representation and one based on the graph adjacency matrix. It considers which representation method is superior. In addition it explores whether it is best, for comparison purposes, to combine multiple graphs into single views or to juxtapose single graph representations.To run this comparison a simple tool was developed and task-based analysis done using that tool to compare multiple versions of a small, locally dense, directed multigraph based on sports data. We are able to demonstrate that it is better to combine views into a single diagram, and that even for small graphs, an analyst is not disadvantaged by the abstract nature of the matrix compared to the intuitive Node-Link diagram