We describe the design and deployment of Many Eyes, a public web site where users may upload data, create interactive visualizations, and carry on discussions. The goal of the site is to support collaboration around v...
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We describe the design and deployment of Many Eyes, a public web site where users may upload data, create interactive visualizations, and carry on discussions. The goal of the site is to support collaboration around visualizations at a large scale by fostering a social style of dataanalysis in which visualizations not only serve as a discovery tool for individuals but also as a medium to spur discussion among users. To support this goal, the site includes novel mechanisms for end-user creation of visualizations and asynchronous collaboration around those visualizations. In addition to describing these technologies, we provide a preliminary report on the activity of our users.
Topological methods give concise and expressive visual representations of flow fields. The present work suggests a comparable method for the visualization of human brain diffusion MRI data. We explore existing techniq...
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Topological methods give concise and expressive visual representations of flow fields. The present work suggests a comparable method for the visualization of human brain diffusion MRI data. We explore existing techniques for the topological analysis of generic tensor fields, but find them inappropriate for diffusion MRI data. Thus, WE! propose a novel approach that considers the asymptotic behavior of a probabilistic fiber tracking method and define analogs of the basic concepts of flow topology, like critical points, basins, and faces, with interpretations in terms of brain anatomy. The resulting features are fuzzy, reflecting the uncertainty inherent in any connectivity estimate from diffusion imaging. We describe an algorithm to extract the new type of features, demonstrate its robustness under noise, and present results for two regions in a diffusion MRI dataset to illustrate that the method allows a meaningful visual analysis of probabilistic fiber tracking results.
In many domains, increased collaboration has lead to more innovation by fostering the sharing of knowledge, skills, and ideas. Shared analysis of information visualizations does not only lead to increased information ...
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In many domains, increased collaboration has lead to more innovation by fostering the sharing of knowledge, skills, and ideas. Shared analysis of information visualizations does not only lead to increased information processing power, but team members can also share, negotiate, and discuss their views and interpretations on a clataset and contribute unique perspectives on a given problem. Designing technologies to support collaboration around information visualizations poses special challenges and relatively few systems have been designed. We focus on supporting small groups collaborating around information visualizations in a co-located setting, using a shared interactive tabletop display. We introduce an analysis of challenges and requirements for the design of colocated collaborative information visualization systems. We then present a new system that facilitates hierarchical data comparison tasks for this type of collaborative work. Our system supports multi-user input, shared and individual views on the hierarchical datavisualization, flexible use of representations, and flexible workspace organization to facilitate group work around visualizations.
The Internet has become a wild place: malicious code is spread on personal computers across the world, deploying botnets ready to attack the network infrastructure. The vast number of security incidents and other anom...
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The Internet has become a wild place: malicious code is spread on personal computers across the world, deploying botnets ready to attack the network infrastructure. The vast number of security incidents and other anomalies overwhelms attempts at manual analysis, especially when monitoring service provider backbone links. We present an approach to interactive visualization with a case study indicating that interactive visualization can be applied to gain more insight into these large data sets. We superimpose a hierarchy on IP address space, and study the suitability of Treemap variants for each hierarchy level. Because viewing the whole IP hierarchy at once is not practical for most tasks, we evaluate layout stability when eliding large parts of the hierarchy, while maintaining the visibility and ordering of the data of interest.
Perfusion data are dynamic medical image data which characterize the regional blood flow in human tissue. These data bear a great potential in medical diagnosis, since diseases can be better distinguished and detected...
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Perfusion data are dynamic medical image data which characterize the regional blood flow in human tissue. These data bear a great potential in medical diagnosis, since diseases can be better distinguished and detected at an earlier stage compared to static image data. The wide-spread use of perfusion data is hampered by the lack of efficient evaluation methods. For each voxel, a time-intensity curve characterizes the enhancement of a contrast agent. Parameters derived from these curves characterize the perfusion and have to be integrated for diagnosis. The diagnostic evaluation of this multi-field data is challenging and time-consuming due to its complexity. For the visual analysis of such datasets, feature-based approaches allow to reduce the amount of data and direct the user to suspicious areas. We present an interactive visual analysis approach for the evaluation of perfusion data. For this purpose, we integrate statistical methods and interactive feature specification. Correlation analysis and Principal Component analysis (PCA) are applied for dimension reduction and to achieve a better understanding of the inter-parameter relations. Multiple, linked views facilitate the definition of features by brushing multiple dimensions. The specification result is linked to all views establishing a focus+context style of visualization in 3D. We discuss our approach with respect to clinical datasets from the three major application areas: ischemic stroke diagnosis, breast tumor diagnosis, as well as the diagnosis of the coronary heart disease (CHD). It turns out that the significance of perfusion parameters strongly depends on the individual patient, scanning parameters, and data pre-processing.
Analyzing, visualizing, and illustrating changes within time-varying volumetric data is challenging due to the dynamic changes occurring between timesteps. The changes and variations in computational fluid dynamic vol...
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Analyzing, visualizing, and illustrating changes within time-varying volumetric data is challenging due to the dynamic changes occurring between timesteps. The changes and variations in computational fluid dynamic volumes and atmospheric 3D datasets do not follow any particular transformation. Features within the data move at different speeds and directions making the tracking and visualization of these features a difficult task. We introduce a texture-based feature tracking technique to overcome some of the current limitations found in the illustration and visualization of dynamic changes within time-varying volumetric data. Our texture-based technique tracks various features individually and then uses the tracked objects to better visualize structural changes. We show the effectiveness of our texture-based tracking technique with both synthetic and real world time-varying data. Furthermore, we highlight the specific visualization, annotation, registration, and feature isolation benefits of our technique. For instance, we show how our texture-based tracking can lead to insightful visualizations of time-varying data. Such visualizations, more than traditional visualization techniques, can assist domain scientists to explore and understand dynamic changes.
We present a comprehensive system for weather datavisualization. Weather data are multivariate and contain vector fields formed by wind speed and direction. Several well-established visualization techniques such as p...
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We present a comprehensive system for weather datavisualization. Weather data are multivariate and contain vector fields formed by wind speed and direction. Several well-established visualization techniques such as parallel coordinates and polar systems are integrated into our system. We also develop various novel methods, including circular pixel bar charts embedded into polar systems, enhanced parallel coordinates with S-shape axis, and weighted complete graphs. Our system was used to analyze the air pollution problem in Hong Kong and some interesting patterns have been found.
This paper describes Show Me, an integrated set of user interface commands and defaults that incorporate automatic presentation into a commercial visual analysis system called Tableau. A key aspect of Tableau is VizQL...
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This paper describes Show Me, an integrated set of user interface commands and defaults that incorporate automatic presentation into a commercial visual analysis system called Tableau. A key aspect of Tableau is VizQL, a language for specifying views, which is used by Show Me to extend automatic presentation to the generation of tables of views (commonly called small multiple displays). A key research issue for the commercial application of automatic presentation is the user experience, which must support the flow of visual analysis. User experience has not been the focus of previous research on automatic presentation. The Show Me user experience includes the automatic selection of mark types, a command to add a single field to a view, and a pair of commands to build views for multiple fields. Although the use of these defaults and commands is optional, user interface logs indicate that Show Me is used by commercial users.
The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do ...
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The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily resolve the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections to and from node-link and matrix forms, and to flexibly manipulate the NocleTrix representation to explore the dataset and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship clataset to illustrate the capabilities of NocleTrix as both an exploration tool and an effective means of communicating results.
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