Bob Baddeley

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A central challenge in visual analytics is the creation of accessible, widely distributable analysis applications that bring the benefits of visual discovery to as broad a user base as possible. Moreover, to support the role of visualization in the knowledge creation process, it is advantageous to allow users to describe the reasoning strategies they employ(More)
The ability to support creation and parallel analysis of competing scenarios is perhaps the greatest single challenge for today's intelligence analysis systems. Dempster-Shafer theory provides an evidentiary reasoning methodology for scenario construction and analysis that offers potential advantages when compared to other approaches such as Bayesian nets(More)
We present a visualization environment called the Scalable Reasoning System (SRS) that provides a suite of tools for the collection, analysis, and dissemination of reasoning products. This environment is designed to function across multiple platforms, bringing the display of visual information and the capture of reasoning associated with that information to(More)
We present the design and implementation of InfoStar, an adaptive visual analytics platform for mobile devices such as PDAs, laptops, Tablet PCs and mobile phones. InfoStar extends the reach of visual analytics technology beyond the traditional desktop paradigm to provide ubiquitous access to interactive visualizations of information spaces. These(More)
Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are(More)
Two approaches have recently emerged where the similarity between two genes or gene products is obtained by comparing Gene Ontology (GO) annotations associated with the genes or gene products. One approach captures GO-based similarity in terms of hierarchical relations within each gene subontology, while the other relies on associative relations across the(More)
Most current approaches to automatic pathway generation are based on a reverse engineering approach in which pathway plausibility is solely derived from gene expression data and not independently validated. Alternative approaches use prior biological knowledge to validate automatically inferred pathways, but the prior knowledge is usually not sufficiently(More)