DevLan/vispubs huggingface dataset:
Multi-Resolution Techniques for Visual Exploration of Large Time-Series Data
Authors: Ming C. Hao, Umeshwar Dayal, Daniel A. Keim, Tobias Schreck
Published at EuroVis, 2007

Time series are a data type of utmost importance in many domains such as business management and service monitoring. We address the problem of visualizing large time-related data sets which are difficult to visualize effectively with standard techniques given the limitations of current display devices. We propose a framework for intelligent time- and data-dependent visual aggregation of data along multiple resolution levels. This idea leads to effective visualization support for long time-series data providing both focus and context. The basic idea of the technique is that either data-dependent or application-dependent, display space is allocated in proportion to the degree of interest of data subintervals, thereby (a) guiding the user in perceiving important information, and (b) freeing required display space to visualize all the data. The automatic part of the framework can accommodate any time series analysis algorithm yielding a numeric degree of interest scale. We apply our techniques on real-world data sets, compare it with the standard visualization approach, and conclude the usefulness and scalability of the approach.
Multiresolution MIP Rendering of Large Volumetric Data Accelerated on Graphics Hardware
Authors: Wladimir J. van der Laan, Andrei C. Jalba, Jos B. T. M. Roerdink
Published at EuroVis, 2007

This paper is concerned with a multiresolution representation for maximum intensity projection (MIP) volume rendering based on morphological pyramids which allows progressive refinement. We consider two algorithms for progressive rendering from the morphological pyramid: one which projects detail coefficients level by level, and a second one, called streaming MIP, which resorts the detail coefficients of all levels simultaneously with respect to decreasing magnitude of a suitable error measure. The latter method outperforms the level-by-level method, both with respect to image quality with a fixed amount of detail data, and in terms of flexibility of controlling approximation error or computation time. We improve the streaming MIP algorithm, present a GPU implementation for both methods, and perform a comparison with existing CPU and GPU implementations.
Multiscale Visualization of Dynamic Software Logs
Authors: Sergio Moreta, Alexandru C. Telea
Published at EuroVis, 2007

We present a set of techniques and design principles for the visualization of large dynamic software logs consisting of attributed change events, such as obtained from instrumenting programs or mining software repositories. We enhance the visualization scalability with importance-based antialiasing techniques that guarantee visibility of several types of events. We present a hierarchical clustering method that uncovers several patterns of interest in the event logs, such as same-lifetime memory allocations and software releases. We visualize the clusters using a new type of technique called interleaved cushions. We demonstrate our methods on two real-world problems: the monitoring of a dynamic memory allocator and the analysis of a software repository.
Online Dynamic Graph Drawing
Authors: Yaniv Frishman, Ayellet Tal
Published at EuroVis, 2007

This paper presents an algorithm for drawing a sequence of graphs online. The algorithm strives to maintain the global structure of the graph and thus the user's mental map, while allowing arbitrary modifications between consecutive layouts. The algorithm works online and uses various execution culling methods in order to reduce the layout time and handle large dynamic graphs. Techniques for representing graphs on the GPU allow a speedup by a factor of up to 8 compared to the CPU implementation. An application to visualization of discussion threads in Internet sites is provided.
Parametric Visualization of High Resolution Correlated Multi-spectral Features Using PCA
Authors: Alexander Broersen, Robert van Liere, Ron M. A. Heeren
Published at EuroVis, 2007

An imaging mass spectrometer is an analytical instrument that can determine the spatial distribution of chemical compounds on complex surfaces. The output of the device is a multi-spectral datacube; a three-dimensional (3D) dataset in which the xy-dimension represents the surface position and the z-dimension represents the mass spectral distribution. Analysts try to discover correlations in spectral profiles and spatial distributions inside a datacube. New technological developments allow mass spectrometric imaging on a higher spatial and spectral resolution. In this paper we present a parametric visualization technique which allows an analyst to examine spectral and spatially correlated patterns on the highest possible resolution. Principal component analysis (PCA) is used to decompose the datacube into several discriminating components. We represent these extracted features as abstract geometric shapes and use three parameters to allow for data exploration. The first parameter thresholds the spectral contribution at which an extracted component is visualized. The level of detail the shapes is controlled by a second parameter and a third parameter determines at which density-level the extracted feature is represented. This new visualization technique enables an analyst to select the most relevant spectral correlations and investigate their specific spatial distribution. With this method, less noise is included in the visualization of extracted features and by introducing various levels of detail the full spectral resolution can be utilized.
Path Visualization for Adjacency Matrices
Authors: Zeqian Shen, Kwan-Liu Ma
Published at EuroVis, 2007

For displaying a dense graph, an adjacency matrix is superior than a node-link diagram because it is more compact and free of visual clutter. A node-link diagram, however, is far better for the task of path finding because a path can be easily traced by following the corresponding links, provided that the links are not heavily crossed or tangled. We augment adjacency matrices with path visualization and associated interaction techniques to facilitate path finding. Our design is visually pleasing, and also effectively displays multiple paths based on the design commonly found in metro maps. We illustrate and assess the key aspects of our design with the results obtained from two case studies and an informal user study.
Priority Streamlines: A context-based Visualization of Flow Fields
Authors: Michael Schlemmer, Ingrid Hotz, Bernd Hamann, Florian Morr, Hans Hagen
Published at EuroVis, 2007

Flow vector fields contain a wealth of information that needs to be visualized. As an extension of the well-known streamline technique, we have developed a context-based method for visualizing steady flow vector fields in two and three dimensions. We call our method "Priority Streamlines". In our approach, the density of the streamlines is controlled by a scalar function that can be user-defined, or be given by additional information (e.g., temperature, pressure, vorticity, velocity) considering the underlying flow vector field. In regions, which are interesting the streamlines are drawn with increased density, while less interesting regions are drawn sparsely. Since streamlines in the most important regions are drawn first, we can use thresholding to obtain a streamline representation highlighting essential features. Color-mapping and transparency can be used for visualizing other information hidden in the flow vector field.
Relevance Driven Visualization of Financial Performance Measures
Authors: Hartmut Ziegler, Tilo Nietzschmann, Daniel A. Keim
Published at EuroVis, 2007

Visual data analysis has received a lot of research interest in recent years, and a wide variety of new visualization techniques and applications have been developed to improve insight into the various application domains. In financial data analysis, however, analysts still primarily rely on a set of statistical performance parameters in combination with traditional line charts in order to evaluate assets and to make decisions, and information visualization is only very slowly entering this important domain. In this paper, we analyze some of the standard statistical measures for technical financial data analysis and demonstrate cases where they produce insufficient and misleading results that do not reflect the real performance of an asset. We propose a technique for visualizing financial time series data that eliminates these inadequacies, offering a complete view on the real performance of an asset. The technique is enhanced by relevance and weighting functions according to the users' preferences in order to emphasize specific regions of interest. Based on these principles we redefine some of the standard performance measures. We apply our technique on real world financial data sets and combine it with higher-level financial analysis techniques such as performance/risk analysis, dominance evaluation, and efficiency curves in order to show how traditional techniques from economics can be improved by modern visual data analysis techniques.
See What You Know: Analyzing Data Distribution to Improve Density Map Visualization
Authors: Enrico Bertini, Alessio Di Girolamo, Giuseppe Santucci
Published at EuroVis, 2007

Density maps allow for visually rendering density differences, usually mapping density values to a grey or color scale. The paper analyzes the drawbacks arising from the commonly used strategies and introduces a novel technique able to improve the overall mapping process. The technique is driven by statistical knowledge about the density distribution and a set of quality metrics allows for validating, in an objective way, its effectiveness.
Segmentation of DT-MRI Anisotropy Isosurfaces
Authors: Thomas Schultz 0001, Holger Theisel, Hans-Peter Seidel
Published at EuroVis, 2007

While isosurfaces of anisotropy measures for data from diffusion tensor magnetic resonance imaging (DT-MRI) are known to depict major anatomical structures, the anisotropy metric reduces the rich tensor data to a simple scalar field. In this work, we suggest that the part of the data which has been ignored by the metric can be used to segment anisotropy isosurfaces into anatomically meaningful regions. For the implementation, we propose an edge-based watershed method that adapts and extends a method from curvature-based mesh segmentation [MW99]. Finally, we use the segmentation results to enhance visualization of the data.
Sonar Explorer: A New Tool for Visualization of Fish Schools from 3D Sonar Data
Authors: Jean-Paul Balabanian, Ivan Viola, Egil Ona, Ruben Patel, M. Eduard Gröller
Published at EuroVis, 2007

We present a novel framework for analysis and visualization of fish schools in 3D sonar surveys. The 3D sonar technology is new and there have not been applications to visualize the data in 3D. We have created an application called Sonar Explorer that satisfies the requirements of domain scientists. Sonar Explorer provides easy and intuitive semi-automatic fish school tracking and survey map generation. The overall pipeline is described and all pipeline stages relevant for visualization are highlighted. We present techniques to deal with 3D sonar data specifics: highly anisotropic volume data aligned on a curvilinear grid. Domain scientists provide initial impressions on interaction and outlook.
Story Telling for Presentation in Volume Visualization
Authors: Michael Wohlfart, Helwig Hauser
Published at EuroVis, 2007

In this paper we present a novel approach to volume visualization for presentation purposes that improves both the comprehensibility and credibility of the intended visualization message. Therefore, we combine selected aspects from storytelling as well as from interactive volume visualization to create a guided but at the same time interactive visualization presentation approach. To ease the observer's access to a presented visualization result we not only communicate the result itself, but also deliver its creational process in the form of an annotated visualization animation, which we call a visualization story. Additionally, we enable variable means of interactivity during story playback. The story observers may just watch the presentation passively, but they are also allowed to reinvestigate the visualization independently from story guidance, offering the ability to verify, confirm, or even disapprove the presented visualization message. For demonstration purposes, we developed a prototype application that provides tools to author, edit, and watch visualization stories. We demonstrate the potential of our approach on the basis of medical visualization examples.
Subdivision Volume Splatting
Authors: Kevin T. McDonnell, Neophytos Neophytou, Klaus Mueller 0001, Hong Qin
Published at EuroVis, 2007

Volumetric Subdivision (VS) is a powerful paradigm that enables volumetric sculpting and realistic volume deformations that give rise to the concept of "virtual clay". In VS, volumes are commonly represented as a space-filling set of deformed polyhedra, which can be further decomposed into a mesh of tetrahedra for rendering. Images can then be generated via tetrahedral projection or raycasting. A current shortcoming in VS-based operations is the need for a very high level of subdivision to represent fine detail in the mesh and to obtain a high-fidelity visualization. However, we have discovered that the subdivision process itself can be closely simulated with radial basis functions (RBFs), making it possible to replace the finer subdivision levels by a coarser aggregation of RBF kernels. This reduction to a simplified assembly of RBFs subsequently enables interactive rendering of volumetric subdivision shapes within a GPU-based volume splatting framework.
The CoMIRVA Toolkit for Visualizing Music-Related Data
Authors: Markus Schedl, Peter Knees, Klaus Seyerlehner, Tim Pohle
Published at EuroVis, 2007

We present CoMIRVA, which is an abbreviation for Collection of Music Information Retrieval and Visualization Applications. CoMIRVA is a Java framework and toolkit for information retrieval and visualization. It is licensed under the GNU GPL and can be downloaded from http://www.cp.jku.at/comirva/. At the moment, the main functionalities include music information retrieval, web retrieval, and visualization of the extracted information. In this paper, we focus on the visualization aspects of CoMIRVA. Since many of the information retrieval functions are intended to be applied to problems of the field of music information retrieval (MIR), we demonstrate the functions using data like similarity matrices of music artists gained by analyzing artist-related web pages. CoMIRVA is continuously being extended. Currently, it supports the following visualization techniques: Self-Organizing Map, Smoothed Data Histogram, Circled Bars, Circled Fans, Probabilistic Network, Continuous Similarity Ring, Sunburst, and Music Description Map. Since space is limited, we can only present a selected number of these in this paper. As one key feature of CoMIRVA is its easy extensibility, we further elaborate on how CoMIRVA was used for creating a novel user interface to digital music repositories.
TrustNeighborhoods: Visualizing Trust in Distributed File Sharing Systems
Authors: Niklas Elmqvist, Philippas Tsigas
Published at EuroVis, 2007

We present TrustNeighborhoods, a security trust visualization for situational awareness on the Internet aimed at novice and intermediate users of a distributed file sharing system. The TrustNeighborhoods technique uses the metaphor of a multi-layered city or fortress to intuitively represent trust as a simple geographic relation. The visualization uses a radial space-filling layout; there is a 2D mode for editing and configuration, as well as a 3D mode for exploration and overview. In addition, the 3D mode supports a simple animated "fly-to" command that is intended to show the user the context and trust of a particular document by zooming in on the document and its immediate neighborhood in the 3D city. The visualization is intended for integration into an existing desktop environment, connecting to the distributed file sharing mechanisms of the environment and non-obtrusively displaying a 3D orientation animation in the background for any file being accessed over the network. A formal user study shows that the technique supports significantly higher trust assignment accuracy than manual trust assignment at the cost of only a minor time investment.
Viewpoint Selection for Intervention Planning
Authors: Konrad Mühler, Mathias Neugebauer, Christian Tietjen, Bernhard Preim
Published at EuroVis, 2007

Viewpoint selection is crucial for medical intervention planning. The interactive exploration of a scene with 3d objects involves the systematic analysis of several anatomic structures. Viewpoint selection techniques enhance the display of the currently selected structure. For animations in collaborative intervention planning and surgical education, the authoring process may be significantly enhanced if 'good' viewpoints for important objects as well as for the whole scene are chosen automatically. We describe a viewpoint selection technique guided by parameters like size of unoccluded surface, importance of occluding objects, preferred region and viewpoint stability. The influence of these parameters may be flexibly adjusted by weights. Parameter maps indicate the influence of the current parameter settings on the viewpoints. For selected applications, the weights may be predefined and reused for other cases. We also describe an informal user study which was accomplished to understand if our viewpoint selection strategies produce adequate results from the users' point of view.
Visualization Methods for Vortex Rings and Vortex Breakdown Bubbles
Authors: Ronald Peikert, Filip Sadlo
Published at EuroVis, 2007

Vortex breakdown bubbles are a subject which is of interest in many disciplines such as aeronautics, mixing, and combustion. Existing visualization methods are based on stream surfaces, direct volume rendering, tensor field visualization, and vector field topology. This paper presents a topological approach which is more closely oriented at the underlying theory of continuous dynamical systems. Algorithms are described for the detection of vortex rings and vortex breakdown bubbles, and for visualization of their characteristic properties such as the boundary, the chaotic dynamics, and possible islands of stability. Since some of these require very long streamlines, the effect of numerically introduced divergence has to be considered. From an existing subdivision scheme, a novel method for divergence conserving interpolation of cuboid cells is derived, and results are compared with those from standard trilinear interpolation. Also a comparison of results obtained with and without divergence cleaning is given.
Visualization of Uncertainty in Lattices to Support Decision-Making
Authors: Christopher Collins 0001, Sheelagh Carpendale, Gerald Penn
Published at EuroVis, 2007

Lattice graphs are used as underlying data structures in many statistical processing systems, including natural language processing. Lattices compactly represent multiple possible outputs and are usually hidden from users. We present a novel visualization intended to reveal the uncertainty and variability inherent in statistically-derived lattice structures. Applications such as machine translation and automated speech recognition typically present users with a best-guess about the appropriate output, with apparent complete confidence. Through case studies we show how our visualization uses a hybrid layout along with varying transparency, colour, and size to reveal the lattice structure, expose the inherent uncertainty in statistical processing, and help users make better-informed decisions about statistically-derived outputs.
An empirical study of the use of visually enhanced voip audio conferencing: the case of IEAC
Authors: Xianghua Ding, Thomas Erickson, Wendy A. Kellogg, Stephen Levy, Jim Christensen, Jeremy B. Sussman, Tracee Vetting Wolf, William E. Bennett
Published at CHI, 2007

IBM Enhanced Audio Conferencing (IEAC) is a VoIP-based audio conferencing system that, like several other systems, provides a visualization showing who is present and their states (e.g., speaking, muted). This paper presents the first study of the use of such a system. Drawing on log files collected over six weeks of use by over 1300 corporate employees, and interviews with 10 of them, we look at how and why various features of the system are used and what sorts of practices are supported. Our findings shed light on the factors that drive the use of visual enhancements to audio conferencing, and suggest further research topics.
Beyond visual acuity: the perceptual scalability of information visualizations for large displays
Authors: Beth Yost, Yonca Haciahmetoglu, Chris North 0001
Published at CHI, 2007

The scalability of information visualizations has typically been limited by the number of available display pixels. As displays become larger, the scalability limit may shift away from the number of pixels and toward human perceptual abilities. This work explores the effect of using large, high resolution displays to scale up information visualizations beyond potential visual acuity limitations. Displays that are beyond visual acuity require physical navigation to see all of the pixels. Participants performed various information visualization tasks using display sizes with a sufficient number of pixels to be within, equal to, or beyond visual acuity. Results showed that performance on most tasks was more efficient and sometimes more accurate because of the additional data that could be displayed, despite the physical navigation that was required. Visualization design issues on large displays are also discussed.
CAAD: an automatic task support system
Authors: Tye Rattenbury, John F. Canny
Published at CHI, 2007

Recent HCI research shows strong interest in task management systems (e.g. [19, 27]) that support the multi-tasked nature of information work [13]. These systems either require users to manually create and maintain task representations or they depend on explicit user cues to guide the creation and maintenance process. To access and use the task representations in these systems, users must also specify their current task. This interaction overhead inhibits the adoption of these systems. In this paper, we present a novel approach to task management that automates the creation and maintenance of task representations. Our system supports the user by making commonly used information more "ready-at-hand" through an intuitive visualization of their task representations. Users can correct and organize their task representations by directly manipulating the visualization; however, this interaction is not required. We describe a feasibility study that demonstrates the actual utility (in terms of overhead reduction) and perceived utility of our system.
ExperiScope: an analysis tool for interaction data
Authors: François Guimbretière, Morgan Dixon, Ken Hinckley
Published at CHI, 2007

We present ExperiScope, an analytical tool to help designers and experimenters explore the results of quantitative evaluations of interaction techniques. ExperiScope combines a new visualization incorporating aspects of the KLM and the three-state model with an interface helping users to rapidly cluster similar patterns of interactions. The tool makes it easy to identify and compare key patterns of use encountered during data collection. This promotes a deeper understanding of the results of a given evaluation.We illustrate the advantages of this tool by revisiting the data collected for an experiment conducted by Hinckley et al. [19] which compared different mode switching techniques. Our results show that our tool complements the previously reported results by offering insights about error behavior and the impact of mode switching on user performance.By providing a more fine-grained analysis of the data gathered during empirical evaluations, we hope that our tool will improve researchers' understanding of existing and newly developed interaction techniques.