36-Issue 3

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https://diglib.eg.org/handle/10.2312/2631433

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Interactive Ambiguity Resolution of Named Entities in Fictional Literature
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Stoffel, Florian; Jentner, Wolfgang; Behrisch, Michael; Fuchs, Johannes; Keim, Daniel A.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Named entity recognition (NER) denotes the task to detect entities and their corresponding classes, such as person or location, in unstructured text data. For most applications, state of the art NER software is producing reasonable results. However, as a consequence of the methodological limitations and the well-known pitfalls when analyzing natural language data, the NER results are likely to contain ambiguities. In this paper, we present an interactive NER ambiguity resolution technique, which enables users to create (post-processing) rules for named entity recognition data based on the content and entity context of the analyzed documents. We specifically address the problem that in use-cases where ambiguities are problematic, such as the attribution of fictional characters with traits, it is often unfeasible to train models on custom data to improve state of the art NER software. We derive an iterative process model for improving NER results, show an interactive NER ambiguity resolution prototype, illustrate our approach with contemporary literature, and discuss our work and future research.
Integrating Visual Analytics Support for Grounded Theory Practice in Qualitative Text Analysis
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Chandrasegaran, Senthil; Badam, Sriram Karthik; Kisselburgh, Lorraine; Ramani, Karthik; Elmqvist, Niklas; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
We present an argument for using visual analytics to aid Grounded Theory methodologies in qualitative data analysis. Grounded theory methods involve the inductive analysis of data to generate novel insights and theoretical constructs. Making sense of unstructured text data is uniquely suited for visual analytics. Using natural language processing techniques such as parts-ofspeech tagging, retrieving information content, and topic modeling, different parts of the data can be structured and semantically associated, and interactively explored, thereby providing conceptual depth to the guided discovery process. We review grounded theory methods and identify processes that can be enhanced through visual analytic techniques. Next, we develop an interface for qualitative text analysis, and evaluate our design with qualitative research practitioners who analyze texts with and without visual analytics support. The results of our study suggest how visual analytics can be incorporated into qualitative data analysis tools, and the analytic and interpretive benefits that can result.
Graph Layouts by t-SNE
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Kruiger, J. F.; Rauber, Paulo E.; Martins, Rafael Messias; Kerren, Andreas; Kobourov, Stephen; Telea, Alexandru C.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
We propose a new graph layout method based on a modification of the t-distributed Stochastic Neighbor Embedding (t-SNE) dimensionality reduction technique. Although t-SNE is one of the best techniques for visualizing high-dimensional data as 2D scatterplots, t-SNE has not been used in the context of classical graph layout. We propose a new graph layout method, tsNET, based on representing a graph with a distance matrix, which together with a modified t-SNE cost function results in desirable layouts. We evaluate our method by a formal comparison with state-of-the-art methods, both visually and via established quality metrics on a comprehensive benchmark, containing real-world and synthetic graphs. As evidenced by the quality metrics and visual inspection, tsNET produces excellent layouts.
Minimum-Displacement Overlap Removal for Geo-referenced Data Visualization
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Garderen, Mereke van; Pampel, Barbara; Nocaj, Arlind; Brandes, Ulrik; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Given a set of rectangles embedded in the plane, we consider the problem of adjusting the layout to remove all overlap while preserving the orthogonal order of the rectangles. The objective is to minimize the displacement of the rectangles. We call this problem MINIMUM-DISPLACEMENT OVERLAP REMOVAL (MDOR). Our interest in this problem is motivated by the application of displaying metadata of archaeological sites. Because most existing overlap removal algorithms are not designed to minimize displacement while preserving orthogonal order, we present and compare several approaches which are tailored to our particular usecase. We introduce a new overlap removal heuristic which we call REARRANGE. Although conceptually simple, it is very effective in removing the overlap while keeping the displacement small. Furthermore, we propose an additional procedure to repair the orthogonal order after every iteration, with which we extend both our new heuristic and PRISM, a widely used overlap removal algorithm. We compare the performance of both approaches with and without this order repair method. The experimental results indicate that REARRANGE is very effective for heterogeneous input data where the overlap is concentrated in few dense regions.
Sclow Plots: Visualizing Empty Space
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Giesen, Joachim; Kühne, Lars; Lucas, Philipp; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Scatter plots are mostly used for correlation analysis, but are also a useful tool for understanding the distribution of highdimensional point cloud data. An important characteristic of such distributions are clusters, and scatter plots have been used successfully to identify clusters in data. Another characteristic of point cloud data that has received less attention so far are regions that contain no or only very few data points. We show that augmenting scatter plots by projections of flow lines along the gradient vector field of the distance function to the point cloud reveals such empty regions or voids. The augmented scatter plots, that we call sclow plots, enable a much better understanding of the geometry underlying the point cloud than traditional scatter plots, and by that support tasks like dimension inference, detecting outliers, or identifying data points at the interface between clusters. We demonstrate the feasibility of our approach on synthetic and real world data sets.
Visual Analysis of Confocal Raman Spectroscopy Data using Cascaded Transfer Function Design
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Schikora, Christoph Markus; Plack, Markus; Bornemann, Rainer; Bolívar, Peter Haring; Kolb, Andreas; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
2D Confocal Raman Microscopy (CRM) data consist of high dimensional per-pixel spectral data of 1000 bands and allows for complex spectral and spatial-spectral analysis tasks, i.e., in material discrimination, material thickness, and spatial material distributions. Currently, simple integral methods are commonly applied as visual analysis solutions to CRM data which exhibit restricted discrimination power in various regards. In this paper we present a novel approach for the visual analysis of 2D multispectral CRM data using multi-variate visualization techniques. Due to the large amount of data and the demand of an explorative approach without a-priori restriction, our system allows for arbitrary interactive (de)selection of varaibles w/o limitation and an unrestricted online definition/construction of new, combined properties. Our approach integrates CRM specific quantitative measures and handles material-related features for mixed materials in a quantitative manner. Technically, we realize the online definition/construction of new, combined properties as semi-automatic, cascaded, 1D and 2D multidimensional transfer functions (MD-TFs). By interactively incorporating new (raw or derived) properties, the dimensionality of the MD-TF space grows during the exploration procedure and is virtually unlimited. The final visualization is achieved by an enhanced color mixing step which improves saturation and contrast.
Measuring Symmetry in Drawings of Graphs
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Welch, Eric; Kobourov, Stephen; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Layout symmetry is an important and desired feature in graph drawing. While there is a substantial body of work in computer vision around the detection and measurement of symmetry in images, there has been little effort to define and validate meaningful measures of the symmetry of graph drawings. In this paper, we evaluate two algorithms that have been proposed for measuring graph drawing symmetry, comparing their judgments to those of human subjects, and investigating the use of stress as an alternative measure of symmetry. We discuss advantages and disadvantages of these measures, possible ways to improve them, and implications for the design of algorithms that optimize the symmetry in the layout.
Visualization of Delay Uncertainty and its Impact on Train Trip Planning: A Design Study
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Wunderlich, Marcel; Ballweg, Kathrin; Fuchs, Georg; Landesberger, Tatiana von; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Uncertainty about possible train delays has an impact on train trips, as the exact arrival time is unknown during trip planning. Delays can lead to missing a connecting train at the transfer station, or to coming too late to an appointment at the destination. Facing this uncertainty, the traveler may wish to use an earlier train or a different connection arriving well before the appointment. Currently, train trip planning is based on scheduled times of connections between two stations. Information about approximate delays is only available shortly before train departure. Although several visualization approaches can show temporal uncertainty, we are not aware of any visual design specifically supporting trip planning, which can show delay uncertainty and its impact on the connections. We propose and evaluate a visual design which extends train trip planning with delay uncertainty. It shows the scheduled train connections together with their expected train delays as well as their impacts on both the arrival time, and the potential of missing a transfer. The visualization also includes information about alternative connections in case of these critical transfers. In this way the user is able to judge which train connection is suitable for a trip. We conducted a user study with 76 participants to evaluate our design. We compared it to two alternative presentations that are prominent in Germany. The study showed that our design performs comparably well for tasks concerning train schedules. The additional uncertainty display as well as the visualization of alternative connections was appreciated and well understood. The participants were able to estimate when they would likely arrive at their destination despite possible train delays while they were unable to estimate this with existing presentations. The users would prefer to use the new design for their trip planning.
Adaptable Radial Axes Plots for Improved Multivariate Data Visualization
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Rubio-Sánchez, Manuel; Sanchez, Alberto; Lehmann, Dirk J.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Radial axes plots are multivariate visualization techniques that extend scatterplots in order to represent high-dimensional data as points on an observable display. Well-known methods include star coordinates or principal component biplots, which represent data attributes as vectors that de ne axes, and produce linear dimensionality reduction mappings. In this paper we propose a hybrid approach that bridges the gap between star coordinates and principal component biplots, which we denominate adaptable radial axes plots . It is based on solving convex optimization problems where users can: (a) update the axis vectors interactively, as in star coordinates, while producing mappings that enable to estimate attribute values optimally through labeled axes, similarly to principal component biplots; (b) use different norms in order to explore additional nonlinear mappings of the data; and (c) include weights and constraints in the optimization problems for sorting the data along one axis. The result is a exible technique that complements, extends, and enhances current radial methods for data analysis.
GraSp: Combining Spatially-aware Mobile Devices and a Display Wall for Graph Visualization and Interaction
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Kister, Ulrike; Klamka, Konstantin; Tominski, Christian; Dachselt, Raimund; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Going beyond established desktop interfaces, researchers have begun re-thinking visualization approaches to make use of alternative display environments and more natural interaction modalities. In this paper, we investigate how spatially-aware mobile displays and a large display wall can be coupled to support graph visualization and interaction. For that purpose, we distribute typical visualization views of classic node-link and matrix representations between displays. The focus of our work lies in novel interaction techniques that enable users to work with personal mobile devices in combination with the wall. We devised and implemented a comprehensive interaction repertoire that supports basic and advanced graph exploration and manipulation tasks, including selection, details-on-demand, focus transitions, interactive lenses, and data editing. A qualitative study has been conducted to identify strengths and weaknesses of our techniques. Feedback showed that combining mobile devices and a wall-sized display is useful for diverse graph-related tasks. We also gained valuable insights regarding the distribution of visualization views and interactive tools among the combined displays.
Compactly Supported Biorthogonal Wavelet Bases on the Body Centered Cubic Lattice
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Horacsek, Joshua J.; Alim, Usman R.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
In this work, we present a family of compact, biorthogonal wavelet filter banks that are applicable to the Body Centered Cubic (BCC) lattice. While the BCC lattice has been shown to have superior approximation properties for volumetric data when compared to the Cartesian Cubic (CC) lattice, there has been little work in the way of designing wavelet filter banks that respect the geometry of the BCC lattice. Since wavelets have applications in signal de-noising, compression, and sparse signal reconstruction, these filter banks are an important tool that addresses some of the scalability concerns presented by the BCC lattice. We use these filters in the context of volumetric data compression and reconstruction and qualitatively evaluate our results by rendering images of isosurfaces from compressed data.
An Empirical Study on the Reliability of Perceiving Correlation Indices using Scatterplots
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Sher, Varshita; Bemis, Karen G.; Liccardi, Ilaria; Chen, Min; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Scatterplots have been in use for about two centuries, primarily for observing the relationship between two variables and commonly for supporting correlation analysis. In this paper, we report an empirical study that examines how humans' perception of correlation using scatterplots relates to the Pearson's product-moment correlation coefficient (PPMCC) - a commonly used statistical measure of correlation. In particular, we study human participants' estimation of correlation under different conditions, e.g., different PPMCC values, different densities of data points, different levels of symmetry of data enclosures, and different patterns of data distribution. As the participants were instructed to estimate the PPMCC of each stimulus scatterplot, the difference between the estimated and actual PPMCC is referred to as an offset. The results of the study show that varying PPMCC values, symmetry of data enclosure, or data distribution does have an impact on the average offsets, while only large variations in density cause an impact that is statistically significant. This study indicates that humans' perception of correlation using scatterplots does not correlate with computed PPMCC in a consistent manner. The magnitude of offsets may be affected not only by the difference between individuals, but also by geometric features of data enclosures. It suggests that visualizing scatterplots does not provide adequate support to the task of retrieving their corresponding PPMCC indicators, while the underlying model of humans' perception of correlation using scatterplots ought to feature other variables in addition to PPMCC. The paper also includes a theoretical discussion on the cost-benefit of using scatterplots.
Visual Verification of Cancer Staging for Therapy Decision Support
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Cypko, Mario A.; Wojdziak, Jan; Stoehr, Matthaeus; Kirchner, Bettina; Preim, Bernhard; Dietz, Andreas; Lemke, Heinz U.; Oeltze-Jafra, Steffen; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
It is generally accepted practice that each cancer patient case should be discussed in a clinical expert meeting, the so-called tumor board. A central role in finding the best therapy options for patients with solid tumors plays the Tumor, lymph Node, and Metastasis staging (TNM staging). Correctness of TNM staging has a significant impact on the therapy choice and hence on the patient's post-therapeutic quality of life or even survival. If inconsistencies in the TNM staging occur, possible explanations and solutions must be found based on the complex patient records, which takes the costly time of (multiple) physicians. We propose a more efficient visual analysis component, which supports a physician in verifying the given TNM staging before forwarding it to the tumor board. Our component comprises a Bayesian network model of the TNM staging process. Using information from the patient records and Bayesian inference, the models computes a patient-specific TNM staging, which is then explored and compared to the given staging by means of a graph-based visualization. Our component is implemented in a research prototype that supports an understanding of the model computations, allows for a fast identification of important influencing factors, and facilitates a quick detection of differences between two TNM stagings. We evaluated our component with five physicians, each studying 20 cases of laryngeal cancer.
Illustrative Visualization of Mesoscale Ocean Eddies
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Liu, Li; Silver, Deborah; Bemis, Karen; Kang, Dujuan; Curchitser, Enrique; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Feature-based time-varying volume visualization is combined with illustrative visualization to tell the story of how mesoscale ocean eddies form in the Gulf Stream and transport heat and nutrients across the ocean basin. The internal structure of these three-dimensional eddies and the kinematics with which they move are critical to a full understanding of ocean eddies. In this work, we apply a feature-based method to track instances of ocean eddies through the time steps of a high-resolution multidecadal regional ocean model and generate a series of eddy paths which reflect the life cycle of individual eddy instances. Based on the computed metadata, several important geometric and physical properties of eddy are computed. Illustrative visualization techniques, including visual effectiveness enhancement, focus+context, and smart visibility, are combined with the extracted volume features to explore eddy characteristics at different levels. An evaluation by domain experts indicates that combining our feature-based techniques with illustrative visualization techniques provides an insight into the role eddies play in ocean circulation. The domain experts expressed a preference for our methods over existing tools.
EuroVis 2017: Frontmatter
(Eurographics Association, 2017) Heer, Jeffrey; Ropinski, Timo; van Wijk, Jarke;
Visualizing a Sequence of a Thousand Graphs (or Even More)
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Burch, Michael; Hlawatsch, Marcel; Weiskopf, Daniel; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
The visualization of dynamic graphs demands visually encoding at least three major data dimensions: vertices, edges, and time steps. Many of the state-of-the-art techniques can show an overview of vertices and edges but lack a data-scalable visual representation of the time aspect. In this paper, we address the problem of displaying dynamic graphs with a thousand or more time steps. Our proposed interleaved parallel edge splatting technique uses a time-to-space mapping and shows the complete dynamic graph in a static visualization. It provides an overview of all data dimensions, allowing for visually detecting timevarying data patterns; hence, it serves as a starting point for further data exploration. By applying clustering and ordering techniques on the vertices, edge splatting on the links, and a dense time-to-space mapping, our approach becomes visually scalable in all three dynamic graph data dimensions. We illustrate the usefulness of our technique by applying it to call graphs and US domestic flight data with several hundred vertices, several thousand edges, and more than a thousand time steps.
Visual Exploration of Global Trade Networks with Time-Dependent and Weighted Hierarchical Edge Bundles on GPU
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Hofmann, Johannes; Größler, Michael; Rubio-Sánchez, Manuel; Pichler, Peter-Paul; Lehmann, Dirk J.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
The UN Comtrade database is the world's largest repository of bilateral trade data. Their complexity poses a challenge to visualization systems, leading to issues such as scalability and visual clutter. Thus, we propose a radial layout-based visual exploration system to enable the user to smoothly explore the change over time and to explore different commodity classes at once by using a novel edge bundling concept. We evaluated our system with the aid of a group of domain experts.
Interactive Regression Lens for Exploring Scatter Plots
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Shao, Lin; Mahajan, Aishwarya; Schreck, Tobias; Lehmann, Dirk J.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Data analysis often involves finding models that can explain patterns in data, and reduce possibly large data sets to more compact model-based representations. In Statistics, many methods are available to compute model information. Among others, regression models are widely used to explain data. However, regression analysis typically searches for the best model based on the global distribution of data. On the other hand, a data set may be partitioned into subsets, each requiring individual models. While automatic data subsetting methods exist, these often require parameters or domain knowledge to work with. We propose a system for visual-interactive regression analysis for scatter plot data, supporting both global and local regression modeling. We introduce a novel regression lens concept, allowing a user to interactively select a portion of data, on which regression analysis is run in interactive time. The lens gives encompassing visual feedback on the quality of candidate models as it is interactively navigated across the input data. While our regression lens can be used for fully interactive modeling, we also provide user guidance suggesting appropriate models and data subsets, by means of regression quality scores. We show, by means of use cases, that our regression lens is an effective tool for user-driven regression modeling and supports model understanding.
Constructing and Evaluating Visualisation Task Classifications: Process and Considerations
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Kerracher, Natalie; Kennedy, Jessie; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Categorising tasks is a common pursuit in the visualisation research community, with a wide variety of taxonomies, typologies, design spaces, and frameworks having been developed over the last three decades. While these classifications are universally purported to be useful in both the design and evaluation processes and in guiding future research, remarkably little attention has been paid to how these frameworks have-and can be-constructed and evaluated. In this paper we review the task classification literature and report on current practices in construction and evaluation. We consider the stages of task classification construction and identify the associated threats to validity arising at each stage and in response to the different methods employed. We provide guidance on suitable validation approaches in order to mitigate these threats. We also consider the appropriateness of evaluation strategies according to the different aspects of the classification which they evaluate. In so doing, we seek to provide guidance for developers of classifications in determining appropriate construction and evaluation strategies when developing a classification, and also for those selecting between competing classifications for use in the design and evaluation processes.
Internal and External Visual Cue Preferences for Visualizations in Presentations
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Kong, Ha-Kyung; Liu, Zhicheng; Karahalios, Karrie; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Presenters, such as analysts briefing to an executive committee, often use visualizations to convey information. In these cases, providing clear visual guidance is important to communicate key concepts without confusion. This paper explores visual cues that guide attention to a particular area of a visualization. We developed a visual cue taxonomy distinguishing internal from external cues, designed a web tool based on the taxonomy, and conducted a user study with 24 participants to understand user preferences in choosing visual cues. Participants perceived internal cues (e.g., transparency, brightness, and magnification) as the most useful visual cues and often combined them with other internal or external cues to emphasize areas of focus for their audience. Interviews also revealed that the choice of visual cues depends on not only the chart type, but also the presentation setting, the audience, and the function cues are serving. Considering the complexity of choosing visual cues, we provide design implications for improving the organization, consistency, and integration of visual cues within existing workflows.

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