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Item ViewFusion: Correlating Structure and Activity Views for Execution Traces(The Eurographics Association, 2012) Trümper, Jonas; Telea, Alexandru; Döllner, Jürgen; Hamish Carr and Silvester CzannerVisualization of data on structure and related temporal activity supports the analysis of correlations between the two types of data. This is typically done by linked views. This has shortcomings with respect to efficient space usage and makes mapping the effect of user input into one view into the other view difficult. We propose here a novel, space-efficient technique that 'fuses' the two information spaces - structure and activity - in one view. We base our technique on the idea that user interaction should be simple, yet easy to understand and follow. We apply our technique, implemented in a prototype tool, for the understanding of software engineering datasets, namely static structure and execution traces of the Chromium web browser.Item Analyzing and Visualizing Multivariate Volumetric Scalar Data and Their Uncertainties(The Eurographics Association, 2012) Ma, Ji; Murphy, D.; O'Mathuna, C.; Hayes, M.; Provan, G.; Hamish Carr and Silvester CzannerData sets from the real world and most scientific simulations are known to be imperfect, often incorporating uncertainty information. Exploration and analysis of such variable data can lead to inaccurate or even incorrect results and inferences. As a powerful tool to communicate the data with users, an effective visualization system should present and inform users of the uncertainty information existing in the data. While some research has been conducted on visualizing uncertainty in spatio-temporal data and univariate data, little work has been reported on multivariate data. In addition, there are two main disadvantages in the existing uncertainty visualization methods for volumetric data. First, they rely heavily on the human perceptual system to recognize the uncertainty information, lacking the capability to depict them quantitatively. Second, they often present large amounts of diverse information in a single display, which may result in visual clutter and occlusion. In this paper, we present our hybrid framework that combines both information visualization techniques and scientific visualization techniques together to allow users to interactively specify features of interest, quantitatively explore and analyze the multivariate volumetric data and their uncertainties as well as localize features in the 3D object space. In comparison with those existing methods, we argue that our method not only allows users to quantitatively visualize the uncertainties within multivariate volumetric data, but also yields a clearer data presentation and facilitates a greater level of visual data analysis. We demonstrate the effectiveness of our framework by reporting a case study from the OpenGGCM (Open Geospace General Circulation Model) simulation in space science application domain.Item Advanced, Automatic Stream Surface Seeding and Filtering(The Eurographics Association, 2012) Edmunds, Matt; Laramee, Robert S.; Chen, Guoning; Zhang, Eugene; Max, Nelson; Hamish Carr and Silvester CzannerThe placement or seeding of stream surfaces in 3D flow fields faces a number of challenges. These challenges include perception, occlusion, and the appropriate representation of flow characteristics. A variety of streamline seeding approaches exist, little corresponding work is presented for stream surfaces. We present a novel automatic stream surface seeding and filtering algorithm. Our approach is designed to capture the characteristics of the flow utilizing illustrative techniques to alleviate occlusion and provide options for filtering. We define and prioritize a set of seeding curves at the domain boundaries from isolines computed from a derived scalar field. We detail the generation of an initial set of surfaces from the set of seeding curves, and discuss a technique for effective surface termination. We then present an algorithm that automatically seeds new interior surfaces, to represent locations not captured by the boundary seeding, at a user specified separation from the initial surface set. The results demonstrate satisfactory domain coverage and effective visualizations on a variety of simulations.