EuroVisShort2019

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https://diglib.eg.org/handle/10.2312/2632781

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Authoring Combined Textual and Visual Descriptions of Graph Data
(The Eurographics Association, 2019) Latif, Shahid; Su, Kaidie; Beck, Fabian; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
The interactive linking of text and visualizations supports easy and guided exploration of information and results in a coherent document. Authoring such documents for the web requires writing custom HTML and JavaScript. Existing research aims at reducing the effort by providing a declarative syntax. However, these approaches either do not support the interactive linking of text and visualizations or require advance programming skills to establish this linking. Targeting a specific type of data i.e., graph data, we introduce an approach that uses a declarative syntax to produce interactive documents and requires little to no programming. Based on the user specifications in an HTML file, the system queries the database to retrieve subgraphs and link them to the relevant text fragments. The resulting document consists of a node-link diagram and text; the two representations are closely linked via interactions and word-sized graphics, and provide an active reading experience.
CoCoa: A Linked Network Visualization System of Co-citation and Co-author Relationships
(The Eurographics Association, 2019) Nakazawa, Rina; Itoh, Takayuki; Saito, Takafumi; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
We usually use a text-based search engine while surveying research papers. Such search systems have difficulties for novice researchers in case they do not know appropriate keywords or do not understand the positions of papers. Many visualization tools of citation networks have been proposed to help this task. These tools demonstrated that not only text information of papers but citation relationships and co-author relationships also are helpful clues for research survey. We propose CoCoa, a linked network visualization of co-citation and co-author relationships for surveying research papers. Our system visualizes both citation and co-author networks at the same time. To make comparison and grasp of correspondence between co-citation and co-author networks easier, the system treats both a paper and an author as bags of words and cluster them into topics applying LDA (Latent Dirichlet Allocation) at the same time. Based on the clustering result, it places the clusters of a citation network by a hybrid force-directed and space-filling algorithm. The position of topic clusters in the networks would have an influence on the correspondence of a particular topic in the networks. Our system extracts the clusters which consist of the common combinations of topics in two networks. Then it reuses the positions of the clusters in a citation network as the initial cluster positions of a co-author network, supposing there are a large number of authors.
Color Names Across Languages: Salient Colors and Term Translation in Multilingual Color Naming Models
(The Eurographics Association, 2019) Kim, Younghoon; Thayer, Kyle; Gorsky, Gabriella Silva; Heer, Jeffrey; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
Color names facilitate the identification and communication of colors, but may vary across languages. We contribute a set of human color name judgments across 14 common written languages and build probabilistic models that find different sets of nameable (salient) colors across languages. For example, we observe that unlike English and Chinese, Russian and Korean have more than one nameable blue color among fully-saturated RGB colors. In addition, we extend these probabilistic models to translate color terms from one language to another via a shared perceptual color space. We compare Korean-English translations from our model to those from online translation tools and find that our method better preserves perceptual similarity of the colors corresponding to the source and target terms. We conclude with implications for visualization and future research.
A Construction Kit for Visual Exploration Interfaces
(The Eurographics Association, 2019) Keck, Mandy; Groh, Rainer; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
With a continuously increasing amount of data and resources on the internet and in large document collections, effective visual exploration interfaces are becoming more and more important. In recent years, many novel approaches have been proposed for the exploration of complex, multidimensional data sets. However, little guidance is available for designers to create similar solutions and to reuse established patterns. In this paper, we propose a construction kit for visual exploration interfaces. It provides a set of building blocks that can be easily combined with each other. These building blocks can support the designer in the creation of novel visual exploration interfaces but also in the analysis and variation of existing interface solutions. Furthermore, we present a workshop method that evaluates the application of the construction kit for the creation and analysis of visual exploration interfaces.
The Curious Case of Combining Text and Visualization
(The Eurographics Association, 2019) Ottley, Alvitta; Kaszowska, Aleksandra; Crouser, R. Jordan; Peck, Evan M.; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
Visualization research has made significant progress in demonstrating the value of graphical data representation. Even still, the value added by static visualization is disputed in some areas. When presenting Bayesian reasoning information, for example, some studies suggest that combining text and visualizations could have an interactive effect. In this paper, we use eye tracking to compare how people extract information from text and visualization. Using a Bayesian reasoning problem as a test bed, we provide evidence that visualization makes it easier to identify critical information, but that once identified as critical, information is more easily extracted from the text. These tendencies persist even when text and visualization are presented together, indicating that users do not integrate information well across the two representation types. We discuss these findings and argue that effective representations should consider the ease of both information identification and extraction.
Defining an Analysis: A Study of Client-Facing Data Scientists
(The Eurographics Association, 2019) Mosca, Abigail; Robinson, Shannon; Clarke, Meredith; Redelmeier, Rebecca; Coates, Sebastian; Cashman, Dylan; Chang, Remco; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
As the sophistication of data analyses increases many subject matter experts looking to make data-driven decisions turn to data scientists to help with their data analysis needs. These subject matter experts may have little to no experience in data analysis, and may have little to no idea of what exactly they need to support their decision making. It is up to data scientists to determine the exact analysis needs of these clients before they can run an analysis. We call this step of the analysis process initialization and define it as: translating clients' broad, high-level questions into analytic queries. Despite the fact that this can be a very time consuming task for data scientists, few visualization tools exist to support it. To provide guidance on how future tools may fill this gap, we conducted 14 semi-structured interviews with client-facing data scientists in an array of fields. In analyzing interviews we find data scientists generally employ three methods for initialization: working backwards, probing, and recommending. We discus existing techniques that share synergy with each of these methods and could be leveraged in the design of future visualization tools to support initialization.
The Design Space of SparkWords
(The Eurographics Association, 2019) Brath, Richard; MacMurchy, Peter; Banissi, Ebad; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
The design space of SparkWords is consistently-sized words; embedded in sequential text (e.g. prose, lists); embellished by adding data, including categoric, ordered or quantitative data, that is encoded by a variety of attributes (singular or multiple) applied to words or letters. The breadth of the design space is illustrated with historic examples and novel implementations.
Highly Efficient Controlled Hierarchical Data Reduction techniques for Interactive Visualization of Massive Simulation Data
(The Eurographics Association, 2019) Dubois, Jérôme; Lekien, Jacques-Bernard; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
With the constant increase in compute power of supercomputers, high performance computing simulations are producing higher fidelity results and possibly massive amounts of data. To keep visualization of such results interactive, existing techniques such as Adaptive Mesh Refinement (AMR) can be of use. In particular, Tree-Based AMR methods (TB-AMR) are widespread in simulations and are becoming more present in general purpose visualization pipelines such as VTK. In this work, we show how TB-AMR data structures could lead to more efficient exploration of massive data sets in the Exascale era. We discuss how algorithms (filters) should be designed to take advantage of tree-like data structures for both data filtering or rendering. By introducing controlled hierarchical data reduction we greatly reduce the processing time for existing algorithms, sometimes with no visual impact, and drastically decrease exploration time for analysts. Also thanks to the techniques and implementations we propose, visualization of very large data is made possible on very constrained resources. These ideas are illustrated on million to billion-scale native TB-AMR or resampled meshes, with the HyperTreeGrid object and associated filters we have recently optimized and made available in the Visualisation Toolkit (VTK) for use by the scientific community.
The Human User in Progressive Visual Analytics
(The Eurographics Association, 2019) Micallef, Luana; Schulz, Hans-Jörg; Angelini, Marco; Aupetit, Michaël; Chang, Remco; Kohlhammer, Jörn; Perer, Adam; Santucci, Giuseppe; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
The amount of generated and analyzed data is ever increasing, and processing such large data sets can take too long in situations where time-to-decision or fluid data exploration are critical. Progressive visual analytics (PVA) has recently emerged as a potential solution that allows users to analyze intermediary results during the computation without waiting for the computation to complete. However, there has been limited consideration on how these techniques impact the user. Based on discussions from a Dagstuhl seminar held in October 2018, this paper characterizes PVA users by their common roles, their main tasks, and their distinct focus of analysis. It further discusses cognitive biases that play a particular role in PVA. This work will help PVA visualization designers in devising systems that are tailored for their specific target users and their characteristics.
Label Placement for Outliers in Scatterplots
(The Eurographics Association, 2019) Mumtaz, Haris; Garderen, Mereke van; Beck, Fabian; Weiskopf, Daniel; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
In many application scenarios, outliers can be associated with specific importance for various reasons. In such cases, labeling outliers is important to connect them to the actual semantics of the respective entity. In this paper, we present a cost-based greedy approach that places labels with outliers within scatterplots. The approach uses a search strategy to find the position that represents the least cost to place labels. Our approach can also produce different labeling outcomes by adjusting the weights of the criteria of the cost function. We demonstrate our approach with scatterplots produced from object-oriented software metrics, where outliers often relate to bad smells in the software.
MOOCad: Visual Analysis of Anomalous Learning Activities in Massive Open Online Courses
(The Eurographics Association, 2019) Mu, Xing; Xu, Ke; Chen, Qing; Du, Fan; Wang, Yun; Qu, Huamin; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
The research on Massive Open Online Course (MOOC) has mushroomed worldwide due to the technical revolution and its unprecedented enrollments. Existing work mainly focuses on performance prediction, content recommendation, and learning behavior summarization. However, finding anomalous learning activities in MOOC data has posed special challenges and requires providing a clear definition of anomalous behavior, analyzing the multifaceted learning sequence data, and interpreting anomalies at different scales. In this paper, we present a novel visual analytics system, MOOCad, for exploring anomalous learning patterns and their clustering in MOOC data. The system integrates an anomaly detection algorithm to cluster learning sequences of MOOC learners into staged-based groups. Moreover, it allows interactive anomaly detection between and within groups on the basis of semantic and interpretable group-wise data summaries. We demonstrate the effectiveness of MOOCad via an in-depth interview with a MOOC lecturer with real-world course data.
Objective Finite-Time Saddles and their Connection to FTLE
(The Eurographics Association, 2019) Bujack, Roxana; Dutta, Soumya; Rojo, Irene Baeza; Zhang, Duan; Günther, Tobias; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
Based on an intuitive physical definition of what a finite-time saddle-like behavior is, we derive a mathematical definition. We show that this definition builds the link between two FTLE-based saddle generalizations, which is not only of theoretical interest but also provides a more robust extraction of finite-time saddles.
Online Learning of Visualization Preferences through Dueling Bandits for Enhancing Visualization Recommendations
(The Eurographics Association, 2019) Kassel, Jan-Frederik; Rohs, Michael; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
A visualization recommender supports the user through automatic visualization generation. While previous contributions primarily concentrated on integrating visualization design knowledge either explicitly or implicitly, they mostly do not consider the user's individual preferences. In order to close this gap we explore online learning of visualization preferences through dueling bandits. Additionally, we consider this challenge from a usability perspective. Through a user study (N = 15), we empirically evaluate not only the bandit's performance in terms of both effectively learning preferences and properly predicting visualizations (satisfaction regarding the last prediction: μ = 85%), but also the participants' effort with respect to the learning procedure (e.g., NASA-TLX = 24:26). While our findings affirm the applicability of dueling bandits, they further provide insights on both the needed training time in order to achieve a usability-aligned procedure and the generalizability of the learned preferences. Finally, we point out a potential integration into a recommender system.
ReLVis: Visual Analytics for Situational Awareness During Reinforcement Learning Experimentation
(The Eurographics Association, 2019) Saldanha, Emily; Praggastis, Brenda; Billow, Todd; Arendt, Dustin L.; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
Reinforcement learning (RL) is a branch of machine learning where an agent learns to maximize reward through trial and error. RL is challenging and data/compute intensive leading practitioners to become overwhelmed and make poor modeling decisions. Our contribution is a Visual Analytics tool designed to help data scientists maintain situation awareness during RL experimentation. Our tool allows users to understand which hyper-parameter values lead to better or worse outcomes, what behaviors are associated with high and low reward, and how behaviors evolve throughout training. We evaluated our tool through three uses cases using state of the art deep RL models demonstrating how our tool leads to RL situation awareness.
Simulation and Visualization of Fluid Flows Around Real Objects in Augmented Reality
(The Eurographics Association, 2019) Tian, Xingze; Günther, Tobias; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
The long-term vision of augmented reality is to seamlessly integrate digital content into the real world, which provides new means to make physical processes visible that are usually invisible to the naked eye. One such example is the motion of air around us. With the help of a head-mounted augmented reality device, an interactive air flow simulation and the tracking of real-world objects, we develop a flow visualization tool box in which users interactively explore approximations of the real-world air flow around real objects. Since the flows respond dynamically to real-world objects, the influence of obstacle size and air flow speed on the creation and movement of vortices can be explored interactively using geometry-based flow visualization techniques, including pathlines and streaklines. We see our setup mainly used in an educational context or for science communication.
Visualizing Transportation Flows with Mode Split using Glyphs
(The Eurographics Association, 2019) Pérez-Messina, Ignacio; Graells-Garrido, Eduardo; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
The increasing trend of using unconventional data in urban planning environments has led to the need for developing systems that can visualize this data. Here we present a visualization for studying commuting flows within a city, with a particular focus on the distribution of mode of transportation usage. Our design, called ModalCell, uses a glyph-based flow map to show a city's flows considering mode split, direction, and distance range. We evaluate ModalCell with a pilot survey and a use case that shows the potential of the approach to make flows within a city visible and understandable.
Viz-Blocks: Building Visualizations and Documents in the Browser
(The Eurographics Association, 2019) McNeill, Graham; Hale, Scott A.; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
Viz-Blocks is a simple browser-based UI for data exploration and document creation. It incorporates the Vega-Lite grammar of graphics for standard visualizations (including multiple views and interaction) whereas 'code blocks' provide the full power of the JavaScript ecosystem for creating custom visualizations and other bespoke content. Visualizations are treated as reusable 'blocks' that are easily created, modified and compared during exploration. When preparing results for dissemination, visualizations can be customized and combined with Markdown and image blocks to produce a single or multi-page HTML document that is easily styled and exported. Viz-blocks was designed in consultation with academics, students and policy makers to bridge the gap between visualization tools and more traditional document-authoring tools. The application is aimed at a wide audience: the lightweight, hybrid UI allows all users to access the core functionality, while experienced users can take advantage of code-blocks and the option to use advanced features of Vega-Lite via JSON/YAML snippets.
Voronoi-Based Foveated Volume Rendering
(The Eurographics Association, 2019) Bruder, Valentin; Schulz, Christoph; Bauer, Ruben; Frey, Steffen; Weiskopf, Daniel; Ertl, Thomas; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
Foveal vision is located in the center of the field of view with a rich impression of detail and color, whereas peripheral vision occurs on the side with more fuzzy and colorless perception. This visual acuity fall-off can be used to achieve higher frame rates by adapting rendering quality to the human visual system. Volume raycasting has unique characteristics, preventing a direct transfer of many traditional foveated rendering techniques. We present an approach that utilizes the visual acuity fall-off to accelerate volume rendering based on Linde-Buzo-Gray sampling and natural neighbor interpolation. First, we measure gaze using a stationary 1200 Hz eye-tracking system. Then, we adapt our sampling and reconstruction strategy to that gaze. Finally, we apply a temporal smoothing filter to attenuate undersampling artifacts since peripheral vision is particularly sensitive to contrast changes and movement. Our approach substantially improves rendering performance with barely perceptible changes in visual quality. We demonstrate the usefulness of our approach through performance measurements on various data sets.

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