31-Issue 3

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https://diglib.eg.org/handle/10.2312/172

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Perception of Animated Node-Link Diagrams for Dynamic Graphs
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Ghani, Sohaib; Elmqvist, Niklas; Yi, Ji Soo; S. Bruckner, S. Miksch, and H. Pfister
Effective visualization of dynamic graphs remains an open research topic, and many state-of-the-art tools use animated node-link diagrams for this purpose. Despite its intuitiveness, the effectiveness of animation in nodelink diagrams has been questioned, and several empirical studies have shown that animation is not necessarily superior to static visualizations. However, the exact mechanics of perceiving animated node-link diagrams are still unclear. In this paper, we study the impact of different dynamic graph metrics on user perception of the animation. After deriving candidate visual graph metrics, we perform an exploratory user study where participants are asked to reconstruct the event sequence in animated node-link diagrams. Based on these findings, we conduct a second user study where we investigate the most important visual metrics in depth. Our findings show that node speed and target separation are prominent visual metrics to predict the performance of event sequencing tasks.
Computing Voronoi Treemaps: Faster, Simpler, and Resolution-independent
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Nocaj, Arlind; Brandes, Ulrik; S. Bruckner, S. Miksch, and H. Pfister
Voronoi treemaps represent hierarchies as nested polygons. We here show that, contrary to the apparent popular belief, utilization of an algorithm for weighted Voronoi diagrams is not only feasible, but also more efficient than previous low-resolution approximations, even when the latter are implemented on graphics hardware. More precisely, we propose an instantiation of Lloyd's method for centroidal Voronoi diagrams with Aurenhammer's algorithm for power diagrams that yields an algorithm running in O(n log n) rather than Ω(n2) time per iteration, with n the number of sites. We describe its implementation and present evidence that it is faster also in practice.
The World's Languages Explorer: Visual Analysis of Language Features in Genealogical and Areal Contexts
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Rohrdantz, Christian; Hund, Michael; Mayer, Thomas; Wälchli, Bernhard; Keim, Daniel A.; S. Bruckner, S. Miksch, and H. Pfister
This paper presents a novel Visual Analytics approach that helps linguistic researchers to explore the world's languages with respect to several important tasks: (1) The comparison of manually and automatically extracted language features across languages and within the context of language genealogy, (2) the exploration of interrelations among several of such features as well as their homogeneity and heterogeneity within subtrees of the language genealogy, and (3) the exploration of genealogical and areal influences on the features. We introduce the WORLD'S LANGUAGES EXPLORER, which provides the required functionalities in one single Visual Analytics environment. Contributions are made for different parts of the system: We introduce an extended Sunburst visualization whose so-called feature-rings allow for a cross-comparison of a large number of features at once, within the hierarchical context of the language genealogy. We suggest a mapping of homogeneity measures to all levels of the hierarchy. In addition, we suggest an integration of information from the areal data space into the hierarchical data space. With our approach we bring Visual Analytics research to a new application field, namely Historical Comparative Linguistics, and Linguistic and Areal Typology. Finally, we provide evidence of the good performance of our system in this area through two application case studies conducted by domain experts.
iVisClustering: An Interactive Visual Document Clustering via Topic Modeling
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Lee, Hanseung; Kihm, Jaeyeon; Choo, Jaegul; Stasko, John; Park, Haesun; S. Bruckner, S. Miksch, and H. Pfister
Clustering plays an important role in many large-scale data analyses providing users with an overall understand- ing of their data. Nonetheless, clustering is not an easy task due to noisy features and outliers existing in the data, and thus the clustering results obtained from automatic algorithms often do not make clear sense. To remedy this problem, automatic clustering should be complemented with interactive visualization strategies. This paper proposes an interactive visual analytics system for document clustering, called iVisClustering, based on a widely- used topic modeling method, latent Dirichlet allocation (LDA). iVisClustering provides a summary of each cluster in terms of its most representative keywords and visualizes soft clustering results in parallel coordinates. The main view of the system provides a 2D plot that visualizes cluster similarities and the relation among data items with a graph-based representation. iVisClustering provides several other views, which contain useful interaction methods. With help of these visualization modules, we can interactively refine the clustering results in various ways. Keywords can be adjusted so that they characterize each cluster better. In addition, our system can filter out noisy data and re-cluster the data accordingly. Cluster hierarchy can be constructed using a tree structure and for this purpose, the system supports cluster-level interactions such as sub-clustering, removing unimportant clusters, merging the clusters that have similar meanings, and moving certain clusters to any other node in the tree structure. Furthermore, the system provides document-level interactions such as moving mis-clustered documents to another cluster and removing useless documents. Finally, we present how interactive clustering is performed via iVisClustering by using real-world document data sets.
StratomeX: Visual Analysis of Large-Scale Heterogeneous Genomics Data for Cancer Subtype Characterization
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Lex, Alexander; Streit, Marc; Schulz, Hans-Joerg; Partl, Christian; Schmalstieg, Dieter; Park, Peter J.; Gehlenborg, Nils; S. Bruckner, S. Miksch, and H. Pfister
Identification and characterization of cancer subtypes are important areas of research that are based on the integrated analysis of multiple heterogeneous genomics datasets. Since there are no tools supporting this process, much of this work is done using ad-hoc scripts and static plots, which is inefficient and limits visual exploration of the data. To address this, we have developed StratomeX, an integrative visualization tool that allows investigators to explore the relationships of candidate subtypes across multiple genomic data types such as gene expression, DNA methylation, or copy number data. StratomeX represents datasets as columns and subtypes as bricks in these columns. Ribbons between the columns connect bricks to show subtype relationships across datasets. Drill-down features enable detailed exploration. StratomeX provides insights into the functional and clinical implications of candidate subtypes by employing small multiples, which allow investigators to assess the effect of subtypes on molecular pathways or outcomes such as patient survival. As the configuration of viewing parameters in such a multi-dataset, multi-view scenario is complex, we propose a meta visualization and configuration interface for dataset dependencies and data-view relationships. StratomeX is developed in close collaboration with domain experts.We describe case studies that illustrate how investigators used the tool to explore subtypes in large datasets and demonstrate how they efficiently replicated findings from the literature and gained new insights into the data.
Porosity Maps - Interactive Exploration and Visual Analysis of Porosity in Carbon Fiber Reinforced Polymers
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Reh, Andreas; Plank, Bernhard; Kastner, Johann; Gröller, M. Eduard; Heinzl, Christoph; S. Bruckner, S. Miksch, and H. Pfister
In this work a novel method for the characterization of porosity in carbon fiber reinforced polymers (CFRP) is presented. A visualization pipeline for the interactive exploration and visual analysis of CFRP specimens is developed to enhance the evaluation workflow for non-destructive testing (NDT) practitioners based on specified tasks. Besides quantitative porosity determination and the calculation of local pore properties, i.e., volume, surface, dimensions and shape factors, we employ a drill-down approach to explore pores in a CFRP specimen. We introduce Porosity Maps (PM), to allow for a fast porosity evaluation of the specimen. Pores are filtered in two stages. First a region of interest is selected in the porosity maps. Second, pores are filtered with parallel coordinates according to their local properties. Furthermore a histogram-based best-viewpoint widget was implemented to visualize the quality of viewpoints on a sphere. The advantages of our approach are demonstrated using real world CFRP specimens. We are able to show that our visualization-driven approach leads to a better evaluation of CFRP components than existing reference methods.
Semantic Wordification of Document Collections
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Paulovich, Fernando V.; Toledo, Franklina M. B.; Telles, Guilherme P.; Minghim, Rosane; Nonato, Luis Gustavo; S. Bruckner, S. Miksch, and H. Pfister
Word clouds have become one of the most widely accepted visual resources for document analysis and visualization, motivating the development of several methods for building layouts of keywords extracted from textual data. Existing methods are effective to demonstrate content, but are not capable of preserving semantic relationships among keywords while still linking the word cloud to the underlying document groups that generated them. Such representation is highly desirable for exploratory analysis of document collections. In this paper we present a novel approach to build document clouds, named ProjCloud that aim at solving both semantical layouts and linking with document sets. ProjCloud generates a semantically consistent layout from a set of documents. Through a multidimensional projection, it is possible to visualize the neighborhood relationship between highly related documents and their corresponding word clouds simultaneously. Additionally, we propose a new algorithm for building word clouds inside polygons, which employs spectral sorting to maintain the semantic relationship among words. The effectiveness and flexibility of our methodology is confirmed when comparisons are made to existing methods. The technique automatically constructs projection based layouts the user may choose to examine in the form of the point clouds or corresponding word clouds, allowing a high degree of control over the exploratory process.
Biopsy Planner - Visual Analysis for Needle Pathway Planning in Deep Seated Brain Tumor Biopsy
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Herghelegiu, Paul-Corneliu; Manta, Vasile-Ion; Perin, Radu; Bruckner, Stefan; Gröller, Eduard; S. Bruckner, S. Miksch, and H. Pfister
Biopsies involve taking samples from living tissue using a biopsy needle. In current clinical practice they are a first mandatory step before any further medical actions are planned. Performing a biopsy on a deep seated brain tumor requires considerable time for establishing and validating the desired biopsy needle pathway to avoid damage. In this paper, we present a system for the visualization, analysis, and validation of biopsy needle pathways. Our system uses a multi-level approach for identifying stable needle placements which minimize the risk of hitting blood vessels. This is one of the major dangers in this type of intervention. Our approach helps in identifying and visualizing the point on the pathway that is closest to a surrounding blood vessel, requiring a closer inspection by the neurosurgeon. An evaluation by medical experts is performed to demonstrate the utility of our system.
Conceptualizing Visual Uncertainty in Parallel Coordinates
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Dasgupta, Aritra; Chen, Min; Kosara, Robert; S. Bruckner, S. Miksch, and H. Pfister
Uncertainty is an intrinsic part of any visual representation in visualization, no matter how precise the input data. Existing research on uncertainty in visualization mainly focuses on depicting data-space uncertainty in a visual form. Uncertainty is thus often seen as a problem to deal with, in the data, and something to be avoided if possible. In this paper, we highlight the need for analyzing visual uncertainty in order to design more effective visual representations. We study various forms of uncertainty in the visual representation of parallel coordinates and propose a taxonomy for categorizing them. By building a taxonomy, we aim to identify different sources of uncertainty in the screen space and relate them to different effects of uncertainty upon the user. We examine the literature on parallel coordinates and apply our taxonomy to categorize various techniques for reducing uncertainty. In addition, we consider uncertainty from a different perspective by identifying cases where increasing certain forms of uncertainty may even be useful, with respect to task, data type and analysis scenario. This work suggests that uncertainty is a feature that can be both useful and problematic in visualization, and it is beneficial to augment an information visualization pipeline with a facility for visual uncertainty analysis.
Graph Bundling by Kernel Density Estimation
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Hurter, Christophe; Ersoy, Ozan; Telea, Alex; S. Bruckner, S. Miksch, and H. Pfister
We present a fast and simple method to compute bundled layouts of general graphs. For this, we first transform a given graph drawing into a density map using kernel density estimation. Next, we apply an image sharpening technique which progressively merges local height maxima by moving the convolved graph edges into the height gradient flow. Our technique can be easily and efficiently implemented using standard graphics acceleration techniques and produces graph bundlings of similar appearance and quality to state-of-the-art methods at a fraction of the cost. Additionally, we show how to create bundled layouts constrained by obstacles and use shading to convey information on the bundling quality. We demonstrate our method on several large graphs.
Procedural Texture Synthesis for Zoom-Independent Visualization of Multivariate Data
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Khlebnikov, Rostislav; Kainz, Bernhard; Steinberger, Markus; Streit, Marc; Schmalstieg, Dieter; S. Bruckner, S. Miksch, and H. Pfister
Simultaneous visualization of multiple continuous data attributes in a single visualization is a task that is important for many application areas. Unsurprisingly, many methods have been proposed to solve this task. However, the behavior of such methods during the exploration stage, when the user tries to understand the data with panning and zooming, has not been given much attention. In this paper, we propose a method that uses procedural texture synthesis to create zoom-independent visualizations of three scalar data attributes. The method is based on random-phase Gabor noise, whose frequency is adapted for the visualization of the first data attribute. We ensure that the resulting texture frequency lies in the range that is perceived well by the human visual system at any zoom level. To enhance the perception of this attribute, we also apply a specially constructed transfer function that is based on statistical properties of the noise. Additionally, the transfer function is constructed in a way that it does not introduce any aliasing to the texture. We map the second attribute to the texture orientation. The third attribute is color coded and combined with the texture by modifying the value component of the HSV color model. The necessary contrast needed for texture and color perception was determined in a user study. In addition, we conducted a second user study that shows significant advantages of our method over current methods with similar goals. We believe that our method is an important step towards creating methods that not only succeed in visualizing multiple data attributes, but also adapt to the behavior of the user during the data exploration stage.
Interactive Rendering of Materials and Biological Structures on Atomic and Nanoscopic Scale
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Lindow, Norbert; Baum, Daniel; Hege, Hans-Christian; S. Bruckner, S. Miksch, and H. Pfister
The properties of both inorganic and organic materials and the function of biological structures can often only be understood by analyzing them simultaneously on atomic and nanoscopic, if not mesoscopic, scale. Here, the problem arises to render millions to billions of atoms. We propose a method by which it is possible to interactively visualize atomic data, bridging five orders of magnitude in length scale. For this, we propose a simple yet efficient GPU rendering method that enables interactive visualization of biological structures consisting of up to several billions of atoms. To be able to load all atomic data onto the GPU, we exploit the fact that biological structures often consist of recurring molecular substructures. We also exploit that these objects typically are rendered opaquely, so that only a fraction of the atoms is visible. The method is demonstrated on both biological structures as well as atom probe tomography data of an inorganic specimen. We conclude with a discussion about when during ascension from atomic to mesoscopic scale level-of-detail representations become necessary.
Automating Transfer Function Design with Valley Cell-Based Clustering of 2D Density Plots
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Wang, Yunhai; Zhang, Jian; Lehmann, Dirk J.; Theisel, Holger; Chi, Xuebin; S. Bruckner, S. Miksch, and H. Pfister
Two-dimensional transfer functions are an effective and well-accepted tool in volume classification. The design of them mostly depends on the user's experience and thus remains a challenge. Therefore, we present an approach in this paper to automate the transfer function design based on 2D density plots. By exploiting their smoothness, we adopted the Morse theory to automatically decompose the feature space into a set of valley cells. We design a simplification process based on cell separability to eliminate cells which are mainly caused by noise in the original volume data. Boundary persistence is first introduced to measure the separability between adjacent cells and to suitably merge them. Afterward, a reasonable classification result is achieved where each cell represents a potential feature in the volume data. This classification procedure is automatic and facilitates an arbitrary number and shape of features in the feature space. The opacity of each feature is determined by its persistence and size. To further incorporate the user's prior knowledge, a hierarchical feature representation is created by successive merging of the cells. With this representation, the user is allowed to merge or split features of interest and set opacity and color freely. Experiments on various volumetric data sets demonstrate the effectiveness and usefulness of our approach in transfer function generation.
Importance Driven Automatic Color Design for Direct Volume Rendering
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Wang, Lei; Kaufman, Arie; S. Bruckner, S. Miksch, and H. Pfister
This paper introduces an automatic color design method that is driven by an importance function of the objects within a volumetric dataset. Our method allows the user to intuitively modify the object classification and the importance distribution function in the 2D rendered image. It automatically computes the transfer function, especially the color distribution, to convey the importance of the objects. In our approach, the importance of an object is represented as the attentiveness of a color. In addition, we preserve the color harmony in the rendered image in order to provide a visually pleasing result. In this paper, we propose a set of computational measurements to compute the color attentiveness and color harmony. Our color assignment algorithm supports arbitrary-dimensional transfer functions and obtains interactive frame rates. Our method involves three color spaces, namely Coloroid system, CIE LChuv, and Adobe RGB color space. It calculates the color attentiveness in CIE LChuv space, and the color harmony in Coloroid system. It, then, assigns the transfer function in a dual space of Adobe RGB space and renders the resulting image in Adobe RGB space. We conducted a detailed user study, which proves that our method successfully conveys the importance distributions. Our contribution in this paper is not only our importance driven approach, but also our computational measurements and our color assignment algorithm.
Visualization of Global Correlation Structures in Uncertain 2D Scalar Fields
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Pfaffelmoser, Tobias; Westermann, Rüdiger; S. Bruckner, S. Miksch, and H. Pfister
Visualizing correlations, i.e., the tendency of uncertain data values at different spatial positions to change contrarily or according to each other, allows inferring on the possible variations of structures in the data. Visualizing global correlation structures, however, is extremely challenging, since it is not clear how the visualization of complicated long-range dependencies can be integrated into standard visualizations of spatial data. Furthermore, storing correlation information imposes a memory requirement that is quadratic in the number of spatial sample positions. This paper presents a novel approach for visualizing both positive and inverse global correlation structures in uncertain 2D scalar fields, where the uncertainty is modeled via a multivariate Gaussian distribution. We introduce a new measure for the degree of dependency of a random variable on its local and global surroundings, and we propose a spatial clustering approach based on this measure to classify regions of a particular correlation strength. The clustering performs a correlation filtering, which results in a representation that is only linear in the number of spatial sample points. Via cluster coloring the correlation information can be embedded into visualizations of other statistical quantities, such as the mean and the standard deviation. We finally propose a hierarchical cluster subdivision scheme to further allow for the simultaneous visualization of local and global correlations.
Employing 2D Projections for Fast Visual Exploration of Large Fiber Tracking Data
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Poco, Jorge; Eler, Danilo M.; Paulovich, Fernando; Minghim, Rosane; S. Bruckner, S. Miksch, and H. Pfister
Fiber tracts detection is an increasingly common technology for diagnosis and also understanding of brain function. Although tools for tracing and presenting brain fibers are advanced, it is still difficult for physicians or students to explore the dataset in 3D due to their intricate topology. In this work we present a visual exploration approach for fiber tracts data aimed at supporting exploration of such data. The work employs a local, precise and fast 2D multidimensional projection technique that allows a large number of fibers to be handled simultaneously and to select groups of bundled fibers for further exploration. In this approach, a DTI feature dataset, including curvature as well as spatial features, is projected on a 2D or 3D view. By handling groups formed in this view, exploration is linked to corresponding brain fibers in object space. The link exists in both directions and fibers selected in object space are also mapped to feature space. Our approach also allows users to modify the projection, controlling and improving, if necessary, the definition of groups of fibers for small and large datasets, due to the local nature of the projection. Compared to other related work, the method presented here is faster for creating visual representations, making it possible to explore complete sets of fibers tracts up to 250K fibers, which was not possible previously. Additionally, the ability to change configuration of the feature space representation adds a high degree of flexibility to the process.
Comparative Visual Analysis of 2D Function Ensembles
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Piringer, Harald; Pajer, Stephan; Berger, Wolfgang; Teichmann, Heike; S. Bruckner, S. Miksch, and H. Pfister
In the development process of powertrain systems, 2D function ensembles frequently occur in the context of multirun simulations. An analysis has many facets, including distributions of extracted features, comparisons between ensemble members and target functions, and details-on-demand. The primary contribution of this paper is a design study of an interactive approach for a comparative visual analysis of 2D function ensembles. The design focuses on a tight integration of domain-oriented and member-oriented visualization techniques, and it seeks to preserve the mental model of 2D functions on multiple levels of detail. In this context, we propose a novel focus+context approach for visualizations relying on data-driven placement which is based on labeling. We also extend work on feature-preserving downsampling of 2D functions. Our design supports a comparison of 2D functions based on juxtaposition, overlay, and explicit differences. It also enables an analysis in terms of extracted scalar features and 1D aggregations. An evaluation illustrates a workflow in our application context. User feedback indicates a time saving of 70% for common tasks and a qualitative gain for the entire development process.
COVRA: A Compression-domain Output-sensitive Volume Rendering Architecture Based on a Sparse Representation of Voxel Blocks
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Gobbetti, Enrico; Guitian, José Antonio Iglesias; Marton, Fabio; S. Bruckner, S. Miksch, and H. Pfister
We present a novel multiresolution compression-domain GPU volume rendering architecture designed for inter- active local and networked exploration of rectilinear scalar volumes on commodity platforms. In our approach, the volume is decomposed into a multiresolution hierarchy of bricks. Each brick is further subdivided into smaller blocks, which are compactly described by sparse linear combinations of prototype blocks stored in an overcomplete dictionary. The dictionary is learned, using limited computational and memory resources, by applying the K-SVD algorithm to a re-weighted non-uniformly sampled subset of the input volume, harnessing the recently introduced method of coresets. The result is a scalable high quality coding scheme, which allows very large volumes to be compressed off-line and then decompressed on-demand during real-time GPU-accelerated rendering. Volumetric information can be maintained in compressed format through all the rendering pipeline. In order to efficiently support high quality filtering and shading, a specialized real-time renderer closely coordinates decompression with rendering, combining at each frame images produced by raycasting selectively decompressed portions of the current view- and transfer-function-dependent working set. The quality and performance of our approach is demonstrated on massive static and time-varying datasets.
Tracing Tuples Across Dimensions: A Comparison of Scatterplots and Parallel Coordinate Plots
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Kuang, Xiaole; Zhang, Haimo; Zhao, Shengdong; McGuffin, Michael J.; S. Bruckner, S. Miksch, and H. Pfister
One of the fundamental tasks for analytic activity is retrieving (i.e., reading) the value of a particular quantity in an information visualization. However, few previous studies have compared user performance in such value retrieval tasks for different visualizations. We present an experimental comparison of user performance (time and error distance) across four multivariate data visualizations. Three variants of scatterplot (SCP) visualizations, namely SCPs with common vertical axes (SCP-common), SCPs with a staircase layout (SCP-staircase), and SCPs with rotated axes between neighboring cells (SCP-rotated), and a baseline parallel coordinate plots (PCP) were compared. Results show that the baseline PCP is better than SCP-rotated and SCP-staircase under all conditions, while the difference between SCP-common and PCP depends on the dimensionality and density of the dataset. PCP shows advantages over SCP-common when the dimensionality and density of the dataset are low, but SCP- common eventually outperforms PCP as data dimensionality and density increase. The results suggest guidelines for the use of SCPs and PCPs that can benefit future researchers and practitioners.
Rolled-out Wordles: A Heuristic Method for Overlap Removal of 2D Data Representatives
(The Eurographics Association and Blackwell Publishing Ltd., 2012) Strobelt, Hendrik; Spicker, Marc; Stoffel, Andreas; Keim, Daniel; Deussen, Oliver; S. Bruckner, S. Miksch, and H. Pfister
When representing 2D data points with spacious objects such as labels, overlap can occur. We present a simple algorithm which modifies the (Mani-)Wordle idea with scan-line based techniques to allow a better placement. We give an introduction to common placement techniques from different fields and compare our method to these techniques w.r.t. euclidean displacement, changes in orthogonal ordering as well as shape and size preservation. Especially in dense scenarios our method preserves the overall shape better than known techniques and allows a good trade-off between the other measures. Applications on real world data are given and discussed.

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