Angus Graeme Forbes

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In this paper we present a new technique and prototype graph visualization system, stereoscopic highlighting, to help answer accessibility and adjacency queries when interacting with a node-link diagram. Our technique utilizes stereoscopic depth to highlight regions of interest in a 2D graph by projecting these parts onto a plane closer to the viewpoint of(More)
Thanks to advances in non-invasive technologies such as functional Magnetic Resonance Imaging (fMRI) and Diffusion Tensor Imaging (DTI), highly-detailed maps of brain structure and function can now be collected. In this context, brain connectomics have emerged as a fast growing field that aims at understanding these comprehensive maps of brain connectivity(More)
Visualizing and analyzing the relationships between taxonomic entities represented in multiple input classifications is both challenging and required due to recurrent new discoveries and inferences of taxa and their phylogenetic relationships. Despite the availability of numerous visualization techniques, the large size of hierarchical classifications and(More)
We describe the lessons learned from three recent Immersive Analytics projects which take place at the Electronic Visualization Lab. These successful collaborative projects use the CAVE2 immersive hybrid environment. All three projects visualize multifaceted scientific data and benefit from interdisciplinary collaborations with experts across application(More)
This paper describes the development of an electro-acoustic composition, titled v!t!d, which positions the act of translation as the focal point of the creative process. The work is a collaboration between a saxophonist, a composer, and two multimedia artists. We begin with a saxophone improvisation which is translated into a composition featuring solo(More)
While a number of information visualization software frameworks exist, creating new visualizations, especially those that involve novel visualization metaphors, interaction techniques, data analysis strategies, and specialized rendering algorithms, is still often a difficult process. To facilitate the creation of novel visualizations we present a new(More)
BACKGROUND Molecular and systems biologists are tasked with the comprehension and analysis of incredibly complex networks of biochemical interactions, called pathways, that occur within a cell. Through interviews with domain experts, we identified four common tasks that require an understanding of the causality within pathways, that is, the downstream and(More)
BACKGROUND Molecular activation pathways are inherently complex, and understanding relations across many biochemical reactions and reaction types is difficult. Visualizing and analyzing a pathway is a challenge due to the network size and the diversity of relations between proteins and molecules. RESULTS In this paper, we introduce PathwayMatrix, a(More)
A common strategy for encoding multidimensional data for visual analysis is to use dimensionality reduction techniques that project data with a very large number of objects and dimensions from higher dimensions onto a lower-dimensional space. In visual analytics tasks, the density of the multidimensional clusters can strongly affect how these clusters are(More)
We present a novel visualization system that automatically classifies social network data in order to support a user’s directed social queries and, furthermore, that allows the user to quickly verify the accuracy of the classifications. We model a user’s friends’ interests in particular topics through the creation of a crowd-sourced knowledge base comprised(More)