EuroVis14: Eurographics Conference on Visualization

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/13889

Browse

Now showing 1 - 20 of 43

Visualizing Proximity-Based Spatiotemporal Behavior of Museum Visitors using Tangram Diagrams
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Lanir, Joel; Bak, Peter; Kuflik, Tsvi; H. Carr, P. Rheingans, and H. Schumann
For museum curators it is imperative to learn, analyze, and understand the behavior patterns of the visitors in their museum. Recent developments in the field of indoor positioning systems make the acquisition and availability of visitor behavior data more attainable. However, the analysis of such data remains a challenge due to its noisiness, complexity and sheer size. The current paper applies information visualization techniques to analyze this data and make it more accessible to museum curators and personnel. We first provide a detailed description of the application domain including an analysis of the curators' information needs and a description of how a dataset on visitors' spatiotemporal behavior could be acquired. In order to address the curators' needs, we designed a visualization to encode and convey the information based on a newly adjusted visual glyph that we call Tangram Diagrams. We thereby focus on the adaptability of the technique to a particular domain, rather than on the novelty aspects of the technique itself. We have evaluated our design decisions empirically, and conducted an expert study to describe the insights gained and the value of the information obtained from the visualization. The contribution of this work is twofold. First, we apply information visualization to the museum domain and discuss how it extends to general indoor spatiotemporal behavior analysis. Second, we show how a visual glyph metaphor can be applied in different ways and contexts to efficiently encode multi-faceted information.
RBF Volume Ray Casting on Multicore and Manycore CPUs
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Knoll, Aaron; Wald, Ingo; Navratil, Paul; Bowen, Anne; Reda, Khairi; Papka, Mike E.; Gaither, Kelly; H. Carr, P. Rheingans, and H. Schumann
Modern supercomputers enable increasingly large N-body simulations using unstructured point data. The structures implied by these points can be reconstructed implicitly. Direct volume rendering of radial basis function (RBF) kernels in domain-space offers flexible classification and robust feature reconstruction, but achieving performant RBF volume rendering remains a challenge for existing methods on both CPUs and accelerators. In this paper, we present a fast CPU method for direct volume rendering of particle data with RBF kernels. We propose a novel two-pass algorithm: first sampling the RBF field using coherent bounding hierarchy traversal, then subsequently integrating samples along ray segments. Our approach performs interactively for a range of data sets from molecular dynamics and astrophysics up to 82 million particles. It does not rely on level of detail or subsampling, and offers better reconstruction quality than structured volume rendering of the same data, exhibiting comparable performance and requiring no additional preprocessing or memory footprint other than the BVH. Lastly, our technique enables multi-field, multi-material classification of particle data, providing better insight and analysis.
Semi-Automatic Editing of Graphs with Customized Layouts
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Gladisch, Stefan; Schumann, Heidrun; Ernst, Mathias; Füllen, Georg; Tominski, Christian; H. Carr, P. Rheingans, and H. Schumann
Usually visualization is applied to gain insight into data. Yet consuming the data in form of visual representation is not always enough. Instead, users need to edit the data, preferably through the same means used to visualize them. In this work, we present a semi-automatic approach to visual editing of graphs. The key idea is to use an interactive EditLens that defines where an edit operation affects an already customized and established graph layout. Locally optimal node positions within the lens and edge routes to connected nodes are calculated according to different criteria. This spares the user much manual work, but still provides sufficient freedom to accommodate applicationdependent layout constraints. Our approach utilizes the advantages of multi-touch gestures, and is also compatible with classic mouse and keyboard interaction. Preliminary user tests have been conducted with researchers from bio-informatics who need to manually maintain a slowly, but constantly growing molecular network. As the user feedback indicates, our solution significantly improves the editing procedure applied so far.
Parallel Irradiance Caching for Interactive Monte-Carlo Direct Volume Rendering
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Khlebnikov, Rostislav; Voglreiter, Philip; Steinberger, Markus; Kainz, Bernhard; Schmalstieg, Dieter; H. Carr, P. Rheingans, and H. Schumann
We propose a technique to build the irradiance cache for isotropic scattering simultaneously with Monte Carlo progressive direct volume rendering on a single GPU, which allows us to achieve up to four times increased convergence rate for complex scenes with arbitrary sources of light. We use three procedures that run concurrently on a single GPU. The first is the main rendering procedure. The second procedure computes new cache entries, and the third one corrects the errors that may arise after creation of new cache entries. We propose two distinct approaches to allow massive parallelism of cache entry creation. In addition, we show a novel extrapolation approach which outputs high quality irradiance approximations and a suitable prioritization scheme to increase the convergence rate by dedicating more computational power to more complex rendering areas.
Visual Analysis of Time-Series Similarities for Anomaly Detection in Sensor Networks
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Steiger, Martin; Bernard, Jürgen; Mittelstädt, Sebastian; Lücke-Tieke, Hendrik; Keim, Daniel; May, Thorsten; Kohlhammer, Jörn; H. Carr, P. Rheingans, and H. Schumann
We present a system to analyze time-series data in sensor networks. Our approach supports exploratory tasks for the comparison of univariate, geo-referenced sensor data, in particular for anomaly detection. We split the recordings into fixed-length patterns and show them in order to compare them over time and space using two linked views. Apart from geo-based comparison across sensors we also support different temporal patterns to discover seasonal effects, anomalies and periodicities. The methods we use are best practices in the information visualization domain. They cover the daily, the weekly and seasonal and patterns of the data. Daily patterns can be analyzed in a clustering-based view, weekly patterns in a calendar-based view and seasonal patters in a projection-based view. The connectivity of the sensors can be analyzed through a dedicated topological network view. We assist the domain expert with interaction techniques to make the results understandable. As a result, the user can identify and analyze erroneous and suspicious measurements in the network. A case study with a domain expert verified the usefulness of our approach.
Towards an Unbiased Comparison of CC, BCC, and FCC Lattices in Terms of Prealiasing
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Vad, Viktor; Csébfalvi, Balázs; Rautek, Peter; Gröller, Eduard; H. Carr, P. Rheingans, and H. Schumann
In the literature on optimal regular volume sampling, the Body-Centered Cubic (BCC) lattice has been proven to be optimal for sampling spherically band-limited signals above the Nyquist limit. On the other hand, if the sampling frequency is below the Nyquist limit, the Face-Centered Cubic (FCC) lattice was demonstrated to be optimal in reducing the prealiasing effect. In this paper, we confirm that the FCC lattice is indeed optimal in this sense in a certain interval of the sampling frequency. By theoretically estimating the prealiasing error in a realistic range of the sampling frequency, we show that in other frequency intervals, the BCC lattice and even the traditional Cartesian Cubic (CC) lattice are expected to minimize the prealiasing. The BCC lattice is superior over the FCC lattice if the sampling frequency is not significantly below the Nyquist limit. Interestingly, if the original signal is drastically undersampled, the CC lattice is expected to provide the lowest prealiasing error. Additionally, we give a comprehensible clarification that the sampling efficiency of the FCC lattice is lower than that of the BCC lattice. Although this is a well-known fact, the exact percentage has been erroneously reported in the literature. Furthermore, for the sake of an unbiased comparison, we propose to rotate the Marschner-Lobb test signal such that an undue advantage is not given to either lattice
Many Plans: Multidimensional Ensembles for Visual Decision Support in Flood Management
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Waser, Jürgen; Konev, Artem; Sadransky, Bernhard; Horváth, Zsolt; Ribicic, Hrvoje; Carnecky, Robert; Kluding, Patrick; Schindler, Benjamin; H. Carr, P. Rheingans, and H. Schumann
Uncertainties in flood predictions complicate the planning of mitigation measures. There is a consensus that many possible incident scenarios should be considered. For each scenario, a specific response plan should be prepared which is optimal with respect to criteria such as protection, costs, or realization time. None of the existing software tools is capable of creating large scenario pools, nor do they provide means for quick exploration and assessment of the associated plans. In this paper, we present an integrated solution that is based on multidimensional, timedependent ensemble simulations of incident scenarios and protective measures. We provide scalable interfaces which facilitate and accelerate setting up multiple time-varying parameters for generating a pool of pre-cooked scenarios. In case of an emergency, disaster managers can quickly extract relevant information from the pool to deal with the situation at hand. An interactive 3D-view conveys details about how a response plan has to be executed. Linked information visualization and ranking views allow for a quick assessment of many plans. In collaboration with flood managers, we demonstrate the practical applicability of our solution. We tackle the challenges of planning mobile water barriers for protecting important infrastructure. We account for real-world limitations of available resources and handle the involved logistics problems.
Comparative Exploration of Document Collections: a Visual Analytics Approach
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Oelke, Daniela; Strobelt, Hendrik; Rohrdantz, Christian; Gurevych, Iryna; Deussen, Oliver; H. Carr, P. Rheingans, and H. Schumann
We present an analysis and visualization method for computing what distinguishes a given document collection from others. We determine topics that discriminate a subset of collections from the remaining ones by applying probabilistic topic modeling and subsequently approximating the two relevant criteria distinctiveness and characteristicness algorithmically through a set of heuristics. Furthermore, we suggest a novel visualization method called DiTop-View, in which topics are represented by glyphs (topic coins) that are arranged on a 2D plane. Topic coins are designed to encode all information necessary for performing comparative analyses such as the class membership of a topic, its most probable terms and the discriminative relations. We evaluate our topic analysis using statistical measures and a small user experiment and present an expert case study with researchers from political sciences analyzing two real-world datasets.
SimilarityExplorer: A Visual Inter-Comparison Tool for Multifaceted Climate Data
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Poco, Jorge; Dasgupta, Aritra; Wei, Yaxing; Hargrove, William; Schwalm, Christopher; Cook, Robert; Bertini, Enrico; Silva, Claudio; H. Carr, P. Rheingans, and H. Schumann
Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, like, simulations of photosynthesis and respiration, using algorithms and driving variables such as climate and land use. While it is widely accepted that interactive visualization can enable scientists to better explore model similarity from different perspectives and different granularity of space and time, currently there is a lack of such visualization tools. In this paper we present three main contributions. First, we propose a domain characterization for the TBM community by systematically defining the domain-specific intents for analyzing model similarity and characterizing the different facets of the data. Second, we define a classification scheme for combining visualization tasks and multiple facets of climate model data in one integrated framework, which can be leveraged for translating the tasks into the visualization design. Finally, we present SimilarityExplorer, an exploratory visualization tool that facilitates similarity comparison tasks across both space and time through a set of coordinated multiple views. We present two case studies from three climate scientists, who used our tool for a month for gaining scientific insights into model similarity. Their experience and results validate the effectiveness of our tool.
Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Liu, Shusen; Wang, Bei; Bremer, Peer-Timo; Pascucci, Valerio; H. Carr, P. Rheingans, and H. Schumann
Dimension reduction techniques are essential for feature selection and feature extraction of complex highdimensional data. These techniques, which construct low-dimensional representations of data, are typically geometrically motivated, computationally efficient and approximately preserve certain structural properties of the data. However, they are often used as black box solutions in data exploration and their results can be difficult to interpret. To assess the quality of these results, quality measures, such as co-ranking [LV09], have been proposed to quantify structural distortions that occur between high-dimensional and low-dimensional data representations. Such measures could be evaluated and visualized point-wise to further highlight erroneous regions [MLGH13]. In this work, we provide an interactive visualization framework for exploring high-dimensional data via its twodimensional embeddings obtained from dimension reduction, using a rich set of user interactions. We ask the following question: what new insights do we obtain regarding the structure of the data, with interactive manipulations of its embeddings in the visual space? We augment the two-dimensional embeddings with structural abstractions obtained from hierarchical clusterings, to help users navigate and manipulate subsets of the data. We use point-wise distortion measures to highlight interesting regions in the domain, and further to guide our selection of the appropriate level of clusterings that are aligned with the regions of interest. Under the static setting, point-wise distortions indicate the level of structural uncertainty within the embeddings. Under the dynamic setting, on-thefly updates of point-wise distortions due to data movement and data deletion reflect structural relations among different parts of the data, which may lead to new and valuable insights.
Sparse Representation and Visualization for Direct Numerical Simulation of Premixed Combustion
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Oster, Timo; Lehmann, Dirk J.; Frau, Gordon; Theisel, Holger; Thévenin, Dominique; H. Carr, P. Rheingans, and H. Schumann
Direct Numerical Simulations of premixed combustion produce terabytes of raw data, which are prohibitively large to be stored, and have to be analyzed and visualized. A simultaneous and integrated treatment of data storage, data analysis and data visualization is required. For this, we introduce a sparse representation tailored to DNS data which can directly be used for both analysis and visualization. The method is based on the observation that most information is located in narrow-band regions where the chemical reactions take place, but these regions are not well defined. An approach for the visual investigation of feature surfaces of the scalar fields involved in the simulation is shown as a possible application. We demonstrate our approach on multiple real datasets.
Comparative Blood Flow Visualization for Cerebral Aneurysm Treatment Assessment
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Pelt, Roy van; Gasteiger, Rocco; Lawonn, Kai; Meuschke, Monique; Preim, Bernhard; H. Carr, P. Rheingans, and H. Schumann
A pathological vessel dilation in the brain, termed cerebral aneurysm, bears a high risk of rupture, and is associated with a high mortality. In recent years, incidental findings of unruptured aneurysms have become more frequent, mainly due to advances in medical imaging. The pathological condition is often treated with a stent that diverts the blood flow from the aneurysm sac back to the original vessel. Prior to treatment, neuroradiologists need to decide on the optimal stent configuration and judge the long-term rupture risk, for which blood flow information is essential. Modern patient-specific simulations can model the hemodynamics for various stent configurations, providing important indicators to support the decision-making process. However, the necessary visual analysis of these data becomes tedious and time-consuming, because of the abundance of information. We introduce a comprehensive comparative visualization that integrates morphology with blood flow indicators to facilitate treatment assessment. To deal with the visual complexity, we propose a details-on-demand approach, combining established medical visualization techniques with innovative glyphs inspired by information visualization concepts. In an evaluation we have obtained informal feedback from domain experts, gauging the value of our visualization.
Preface and Table of Contents
(The Eurographics Association and Blackwell Publishing Ltd., 2014) H. Carr, P. Rheingans, and H. Schumann
Networks of Names: Visual Exploration and Semi-Automatic Tagging of Social Networks from Newspaper Articles
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Kochtchi, Artjom; Landesberger, Tatiana von; Biemann, Chris; H. Carr, P. Rheingans, and H. Schumann
Understanding relationships between people and organizations by reading newspaper articles is difficult to manage for humans due to the large amount of data. To address this problem, we present and evaluate a new visual analytics system, which offers interactive exploration and tagging of social networks extracted from newspapers. For the visual exploration of the network, we extract ''interesting'' neighbourhoods of nodes, using a new degree of interest (DOI) measure based on edges instead of nodes. It improves the seminal definition of DOI, which we find to produce the same ''globally interesting'' neighbourhoods in our use case, regardless of the query. Our approach allows answering different user queries appropriately, avoiding uniform search results. We propose a user-driven pattern-based classifier for discovery and tagging of non-taxonomic semantic relations. Our approach does not require any a-priori user knowledge, such as expertise in syntax or pattern creation. An evaluation shows that our classifier is capable of identifying known lexico-syntactic patterns as well as various domain-specific patters. Our classifier yields good results already with a small amount of training, and continuously improves through user feedback. We conduct a user study to evaluate whether our visual interactive system has an impact on how users tag relationships, as compared to traditional text-based interfaces. Study results suggest that users of the visual system tend to tag more concisely, avoiding too abstract or overly specific relationship labels.
InSpectr: Multi-Modal Exploration, Visualization, and Analysis of Spectral Data
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Amirkhanov, Artem; Fröhler, Bernhard; Kastner, Johann; Gröller, Eduard; Heinzl, Christoph; H. Carr, P. Rheingans, and H. Schumann
This paper addresses the increasing demand in industry for methods to analyze and visualize multimodal data involving a spectral modality. Two data modalities are used: high-resolution X-ray computed tomography (XCT) for structural characterization and low-resolution X-ray fluorescence (XRF) spectral data for elemental decomposition. We present InSpectr, an integrated tool for the interactive exploration and visual analysis of multimodal, multiscalar data. The tool has been designed around a set of tasks identified by domain experts in the fields of XCT and XRF. It supports registered single scalar and spectral datasets optionally coupled with element maps and reference spectra. InSpectr is instantiating various linked views for the integration of spatial and non-spatial information to provide insight into an industrial component's structural and material composition: views with volume renderings of composite and individual 3D element maps visualize global material composition; transfer functions defined directly on the spectral data and overlaid pie-chart glyphs show elemental composition in 2D slice-views; a representative aggregated spectrum and spectra density histograms are introduced to provide a global overview in the spectral view. Spectral magic lenses, spectrum probing and elemental composition probing of points using a pie-chart view and a periodic table view aid the local material composition analysis. Two datasets are investigated to outline the usefulness of the presented techniques: a 3D virtually created phantom with a brass metal alloy and a real-world 2D water phantom with insertions of gold, barium, and gadolinium. Additionally a detailed user evaluation of the results is provided
Visual-interactive Exploration of Interesting Multivariate Relations in Mixed Research Data Sets
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Bernard, Jürgen; Steiger, Martin; Widmer, Sven; Lücke-Tieke, Hendrik; May, Thorsten; Kohlhammer, Jörn; H. Carr, P. Rheingans, and H. Schumann
The analysis of research data plays a key role in data-driven areas of science. Varieties of mixed research data sets exist and scientists aim to derive or validate hypotheses to find undiscovered knowledge. Many analysis techniques identify relations of an entire dataset only. This may level the characteristic behavior of different subgroups in the data. Like automatic subspace clustering, we aim at identifying interesting subgroups and attribute sets. We present a visual-interactive system that supports scientists to explore interesting relations between aggregated bins of multivariate attributes in mixed data sets. The abstraction of data to bins enables the application of statistical dependency tests as the measure of interestingness. An overview matrix view shows all attributes, ranked with respect to the interestingness of bins. Complementary, a node-link view reveals multivariate bin relations by positioning dependent bins close to each other. The system supports information drill-down based on both expert knowledge and algorithmic support. Finally, visual-interactive subset clustering assigns multivariate bin relations to groups. A list-based cluster result representation enables the scientist to communicate multivariate findings at a glance. We demonstrate the applicability of the system with two case studies from the earth observation domain and the prostate cancer research domain. In both cases, the system enabled us to identify the most interesting multivariate bin relations, to validate already published results, and, moreover, to discover unexpected relations.
Stability of Dissipation Elements: A Case Study in Combustion
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Gyulassy, Attila; Bremer, Peer-Timo; Grout, Ray; Kolla, Hemanth; Chen, Jacqueline; Pascucci, Valerio; H. Carr, P. Rheingans, and H. Schumann
Recently, dissipation elements have been gaining popularity as a mechanism for measurement of fundamental properties of turbulent flow, such as turbulence length scales and zonal partitioning. Dissipation elements segment a domain according to the source and destination of streamlines in the gradient flow field of a scalar function f :M!R. They have traditionally been computed by numerically integrating streamlines from the center of each voxel in the positive and negative gradient directions, and grouping those voxels whose streamlines terminate at the same extremal pair. We show that the same structures map well to combinatorial topology concepts developed recently in the visualization community. Namely, dissipation elements correspond to sets of cells of the Morse- Smale complex. The topology-based formulation enables a more exploratory analysis of the nature of dissipation elements, in particular, in understanding their stability with respect to small scale variations. We present two examples from combustion science that raise significant questions about the role of small scale perturbation and indeed the definition of dissipation elements themselves.
GuideME: Slice-guided Semiautomatic Multivariate Exploration of Volumes
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Zhou, Liang; Hansen, Charles; H. Carr, P. Rheingans, and H. Schumann
Multivariate volume visualization is important for many applications including petroleum exploration and medicine. State-of-the-art tools allow users to interactively explore volumes with multiple linked parameter-space views. However, interactions in the parameter space using trial-and-error may be unintuitive and time consuming. Furthermore, switching between different views may be distracting. In this paper, we propose GuideME: a novel slice-guided semiautomatic multivariate volume exploration approach. Specifically, the approach comprises four stages: attribute inspection, guided uncertainty-aware lasso creation, automated feature extraction and optional spatial fine tuning and visualization. Throughout the exploration process, the user does not need to interact with the parameter views at all and examples of complex real-world data demonstrate the usefulness, efficiency and ease-of-use of our method.
LoVis: Local Pattern Visualization for Model Refinement
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Zhao, Kaiyu; Ward, Matthew O.; Rundensteiner, Elke A.; Higgins, Huong N.; H. Carr, P. Rheingans, and H. Schumann
Linear models are commonly used to identify trends in data. While it is an easy task to build linear models using pre-selected variables, it is challenging to select the best variables from a large number of alternatives. Most metrics for selecting variables are global in nature, and thus not useful for identifying local patterns. In this work, we present an integrated framework with visual representations that allows the user to incrementally build and verify models in three model spaces that support local pattern discovery and summarization: model complementarity, model diversity, and model representivity. Visual representations are designed and implemented for each of the model spaces. Our visualizations enable the discovery of complementary variables, i.e., those that perform well in modeling different subsets of data points. They also support the isolation of local models based on a diversity measure. Furthermore, the system integrates a hierarchical representation to identify the outlier local trends and the local trends that share similar directions in the model space. A case study on financial risk analysis is discussed, followed by a user study.
Authoring Narrative Visualizations with Ellipsis
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Satyanarayan, Arvind; Heer, Jeffrey; H. Carr, P. Rheingans, and H. Schumann
Data visualization is now a popular medium for journalistic storytelling. However, current visualization tools either lack support for storytelling or require significant technical expertise. Informed by interviews with journalists, we introduce a model of storytelling abstractions that includes state-based scene structure, dynamic annotations and decoupled coordination of multiple visualization components. We instantiate our model in Ellipsis: a system that combines a domain-specific language (DSL) for storytelling with a graphical interface for story authoring. User interactions are automatically translated into statements in the Ellipsis DSL. By enabling storytelling without programming, the Ellipsis interface lowers the threshold for authoring narrative visualizations. We evaluate Ellipsis through example applications and user studies with award-winning journalists. Study participants find Ellipsis to be a valuable prototyping tool that can empower journalists in the creation of interactive narratives.

Browse

Browsing EuroVis14: Eurographics Conference on Visualization by Issue Date

Results Per Page

Sort Options