Conference stringclasses 6 values | Year int64 1.99k 2.03k | Title stringlengths 8 187 | DOI stringlengths 16 32 | Abstract stringlengths 128 7.15k ⌀ | Accessible bool 2 classes | Early bool 2 classes | AuthorNames-Deduped listlengths 1 24 | Award listlengths 0 2 | Resources listlengths 0 5 | ResourceLinks listlengths 0 10 |
|---|---|---|---|---|---|---|---|---|---|---|
EuroVis | 2,019 | A stable graph layout algorithm for processes | 10.1111/cgf.13723 | Process mining enables organizations to analyze data about their (business) processes. Visualization is key to gaining insight into these processes and the associated data. Process visualization requires a high‐quality graph layout that intuitively represents the semantics of the process. Process analysis additionally requires interactive filtering to explore the process data and process graph. The ideal process visualization therefore provides a high‐quality, intuitive layout and preserves the mental map of the user during the visual exploration. The current industry standard used for process visualization does not satisfy either of these requirements. In this paper, we propose a novel layout algorithm for processes based on the Sugiyama framework. Our approach consists of novel ranking and order constraint algorithms and a novel crossing minimization algorithm. These algorithms make use of the process data to compute stable, high‐quality layouts. In addition, we use phased animation to further improve mental map preservation. Quantitative and qualitative evaluations show that our approach computes layouts of higher quality and preserves the mental map better than the industry standard. Additionally, our approach is substantially faster, especially for graphs with more than 250 edges. | false | false | [
"Robin J. P. Mennens",
"Roeland Scheepens",
"Michel A. Westenberg"
] | [] | [] | [] |
EuroVis | 2,019 | A User-based Visual Analytics Workflow for Exploratory Model Analysis | 10.1111/cgf.13681 | Many visual analytics systems allow users to interact with machine learning models towards the goals of data exploration and insight generation on a given dataset. However, in some situations, insights may be less important than the production of an accurate predictive model for future use. In that case, users are more interested in generating of diverse and robust predictive models, verifying their performance on holdout data, and selecting the most suitable model for their usage scenario. In this paper, we consider the concept of Exploratory Model Analysis (EMA), which is defined as the process of discovering and selecting relevant models that can be used to make predictions on a data source. We delineate the differences between EMA and the well‐known term exploratory data analysis in terms of the desired outcome of the analytic process: insights into the data or a set of deployable models. The contributions of this work are a visual analytics system workflow for EMA, a user study, and two use cases validating the effectiveness of the workflow. We found that our system workflow enabled users to generate complex models, to assess them for various qualities, and to select the most relevant model for their task. | false | false | [
"Dylan Cashman",
"Shah Rukh Humayoun",
"Florian Heimerl",
"Kendall Park",
"Subhajit Das 0002",
"John Thompson 0002",
"Bahador Saket",
"Abigail Mosca",
"John T. Stasko",
"Alex Endert",
"Michael Gleicher",
"Remco Chang"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1809.10782v3",
"icon": "paper"
}
] |
EuroVis | 2,019 | A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science | 10.1111/cgf.13688 | We present visual analysis methods for the evaluation of tomographic fiber reconstruction algorithms by means of analysis, visual debugging and comparison of reconstructed fibers in materials science. The methods are integrated in a tool (FIAKER) that supports the entire workflow. It enables the analysis of various fiber reconstruction algorithms, of differently parameterized fiber reconstruction algorithms and of individual steps in iterative fiber reconstruction algorithms. Insight into the performance of fiber reconstruction algorithms is obtained by a list‐based ranking interface. A 3D view offers interactive visualization techniques to gain deeper insight, e.g., into the aggregated quality of the examined fiber reconstruction algorithms and parameterizations. The tool was designed in close collaboration with researchers who work with fiber‐reinforced polymers on a daily basis and develop algorithms for tomographic reconstruction and characterization of such materials. We evaluate the tool using synthetic datasets as well as tomograms of real materials. Five case studies certify the usefulness of the tool, showing that it significantly accelerates the analysis and provides valuable insights that make it possible to improve the fiber reconstruction algorithms. The main contribution of the paper is the well‐considered combination of methods and their seamless integration into a visual tool that supports the entire workflow. Further findings result from the analysis of (dis‐)similarity measures for fibers as well as from the discussion of design decisions. It is also shown that the generality of the analytical methods allows a wider range of applications, such as the application in pore space analysis. | false | false | [
"Bernhard Fröhler",
"Tim Elberfeld",
"Torsten Möller",
"Hans-Christian Hege",
"Johannes Weissenböck",
"Jan De Beenhouwer",
"Jan Sijbers",
"Johann Kastner",
"Christoph Heinzl"
] | [] | [] | [] |
EuroVis | 2,019 | An Exploratory User Study of Visual Causality Analysis | 10.1111/cgf.13680 | Interactive visualization tools are being used by an increasing number of members of the general public; however, little is known about how, and how well, people use visualizations to infer causality. Adapted from the mediation causal model, we designed an analytic framework to systematically evaluate human performance, strategies, and pitfalls in a visual causal reasoning task. We recruited 24 participants and asked them to identify the mediators in a fictitious dataset using bar charts and scatter plots within our visualization interface. The results showed that the accuracy of their responses as to whether a variable is a mediator significantly decreased when a confounding variable directly influenced the variable being analyzed. Further analysis demonstrated how individual visualization exploration strategies and interfaces might influence reasoning performance. We also identified common strategies and pitfalls in their causal reasoning processes. Design implications for how future visual analytics tools can be designed to better support causal inference are discussed. | false | false | [
"Chi-Hsien (Eric) Yen",
"Aditya G. Parameswaran",
"Wai-Tat Fu"
] | [] | [] | [] |
EuroVis | 2,019 | An Interactive Visualization System for Large Sets of Phase Space Trajectories | 10.1111/cgf.13690 | We introduce a visual analysis system with GPU acceleration techniques for large sets of trajectories from complex dynamical systems. The approach is based on an interactive Boolean combination of subsets into a Focus+Context phase‐space visualization. We achieve high performance through efficient bitwise algorithms utilizing runtime generated GPU shaders and kernels. This enables a higher level of interactivity for visualizing the large multivariate trajectory data. We explain how our design meets a set of carefully considered analysis requirements, provide performance results, and demonstrate utility through case studies with many‐particle simulation data from two application areas. | false | false | [
"Tyson Neuroth",
"Franz Sauer",
"Kwan-Liu Ma"
] | [] | [] | [] |
EuroVis | 2,019 | An Ontological Framework for Supporting the Design and Evaluation of Visual Analytics Systems | 10.1111/cgf.13677 | Designing, evaluating, and improving visual analytics (VA) systems is a primary area of activities in our discipline. In this paper, we present an ontological framework for recording and categorizing technical shortcomings to be addressed in a VA workflow, reasoning about the causes of such problems, identifying technical solutions, and anticipating secondary effects of the solutions. The methodology is built on the theoretical premise that designing a VA workflow is an optimization of the cost‐benefit ratio of the processes in the workflow. It makes uses three fundamental measures to group and connect “symptoms”, “causes”, “remedies”, and “side‐effects”, and guide the search for potential solutions to the problems. In terms of requirement analysis and system design, the proposed methodology can enable system designers to explore the decision space in a structured manner. In terms of evaluation, the proposed methodology is time‐efficient and complementary to various forms of empirical studies, such as user surveys, controlled experiments, observational studies, focus group discussions, and so on. In general, it reduces the amount of trial‐and‐error in the lifecycle of VA system development. | false | false | [
"Min Chen 0001",
"David S. Ebert"
] | [] | [] | [] |
EuroVis | 2,019 | Analysis of Decadal Climate Predictions with User-guided Hierarchical Ensemble Clustering | 10.1111/cgf.13706 | In order to gain probabilistic results, ensemble simulation techniques are increasingly applied in the weather and climate sciences (as well as in various other scientific disciplines). In many cases, however, only mean results or other abstracted quantities such as percentiles are used for further analyses and dissemination of the data. In this work, we aim at a more detailed visualization of the temporal development of the whole ensemble that takes the variability of all single members into account. We propose a visual analytics tool that allows an effective analysis process based on a hierarchical clustering of the time‐dependent scalar fields. The system includes a flow chart that shows the ensemble members' cluster affiliation over time, reflecting the whole cluster hierarchy. The latter one can be dynamically explored using a visualization derived from a dendrogram. As an aid in linking the different views, we have developed an adaptive coloring scheme that takes into account cluster similarity and the containment relationships. Finally, standard visualizations of the involved field data (cluster means, ground truth data, etc.) are also incorporated. We include results of our work on real‐world datasets to showcase the utility of our approach. | false | false | [
"Christopher P. Kappe",
"Michael Böttinger",
"Heike Leitte"
] | [] | [] | [] |
EuroVis | 2,019 | Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization | 10.1111/cgf.13701 | Analyzing molecular dynamics (MD) simulations is a key aspect to understand protein dynamics and function. With increasing computational power, it is now possible to generate very long and complex simulations, which are cumbersome to explore using traditional 3D animations of protein movements. Guided by requirements derived from multiple focus groups with protein engineering experts, we designed and developed a novel interactive visual analysis approach for long and crowded MD simulations. In this approach, we link a dynamic 3D focus+context visualization with a 2D chart of time series data to guide the detection and navigation towards important spatio‐temporal events. The 3D visualization renders elements of interest in more detail and increases the temporal resolution dependent on the time series data or the spatial region of interest. In case studies with different MD simulation data sets and research questions, we found that the proposed visual analysis approach facilitates exploratory analysis to generate, confirm, or reject hypotheses about causalities. Finally, we derived design guidelines for interactive visual analysis of complex MD simulation data. | false | false | [
"Jan Byska",
"Thomas Trautner",
"Sérgio M. Marques",
"Jirí Damborský",
"Barbora Kozlíková",
"Manuela Waldner"
] | [] | [] | [] |
EuroVis | 2,019 | Augmenting Tactile 3D Data Navigation With Pressure Sensing | 10.1111/cgf.13716 | We present a pressure‐augmented tactile 3D data navigation technique, specifically designed for small devices, motivated by the need to support the interactive visualization beyond traditional workstations. While touch input has been studied extensively on large screens, current techniques do not scale to small and portable devices. We use phone‐based pressure sensing with a binary mapping to separate interaction degrees of freedom (DOF) and thus allow users to easily select different manipulation schemes (e. g., users first perform only rotation and then with a simple pressure input to switch to translation). We compare our technique to traditional 3D‐RST (rotation, scaling, translation) using a docking task in a controlled experiment. The results show that our technique increases the accuracy of interaction, with limited impact on speed. We discuss the implications for 3D interaction design and verify that our results extend to older devices with pseudo pressure and are valid in realistic phone usage scenarios. | false | false | [
"Xiyao Wang",
"Lonni Besançon",
"Mehdi Ammi",
"Tobias Isenberg 0001"
] | [] | [] | [] |
EuroVis | 2,019 | Bird's-Eye - Large-Scale Visual Analytics of City Dynamics using Social Location Data | 10.1111/cgf.13713 | The analysis of behavioral city dynamics, such as temporal patterns of visited places and citizens' mobility routines, is an essential task for urban and transportation planning. Social media applications such as Foursquare and Twitter provide access to large‐scale and up‐to‐date dynamic movement data that not only help to understand the social life and pulse of a city but also to maintain and improve urban infrastructure. However, the fast growth rate of this data poses challenges for conventional methods to provide up‐to‐date, flexible analysis. Therefore, planning authorities barely consider it. We present a system and design study to leverage social media data that assist urban and transportation planners to achieve better monitoring and analysis of city dynamics such as visited places and mobility patterns in large metropolitan areas. We conducted a goal‐and‐task analysis with urban planning experts. To address these goals, we designed a system with a scalable data monitoring back‐end and an interactive visual analytics interface. The monitoring component uses intelligent pre‐aggregation to allow dynamic queries in near real‐time. The visual analytics interface leverages unsupervised learning to reveal clusters, routines, and unusual behavior in massive data, allowing to understand patterns in time and space. We evaluated our approach based on a qualitative user study with urban planning experts which demonstrates that intuitive integration of advanced analytical tools with visual interfaces is pivotal in making behavioral city dynamics accessible to practitioners. Our interviews also revealed areas for future research. | false | false | [
"Robert Krüger",
"Qi Han 0006",
"Nikolay Ivanov",
"Sanae Mahtal",
"Dennis Thom",
"Hanspeter Pfister",
"Thomas Ertl"
] | [] | [] | [] |
EuroVis | 2,019 | Bridging the Data Analysis Communication Gap Utilizing a Three-Component Summarized Line Graph | 10.1111/cgf.13696 | Communication‐minded visualizations are designed to provide their audience—managers, decision‐makers, and the public—with new knowledge. Authoring such visualizations effectively is challenging because the audience often lacks the expertise, context, and time that professional analysts have at their disposal to explore and understand datasets. We present a novel summarized line graph visualization technique designed specifically for data analysts to communicate data to decision‐makers more effectively and efficiently. Our summarized line graph reduces a large and detailed dataset of multiple quantitative time‐series into (1) representative data that provides a quick takeaway of the full dataset; (2) analytical highlights that distinguish specific insights of interest; and (3) a data envelope that summarizes the remaining aggregated data. Our summarized line graph achieved the best overall results when evaluated against line graphs, band graphs, stream graphs, and horizon graphs on four representative tasks. | false | false | [
"Calvin Yau",
"Morteza Karimzadeh",
"Chittayong Surakitbanharn",
"Niklas Elmqvist",
"David S. Ebert"
] | [] | [] | [] |
EuroVis | 2,019 | Capture & Analysis of Active Reading Behaviors for Interactive Articles on the Web | 10.1111/cgf.13720 | Journalists, educators, and technical writers are increasingly publishing interactive content on the web. However, popular analytics tools provide only coarse information about how readers interact with individual pages, and laboratory studies often fail to capture the variability of a real‐world audience. We contribute extensions to the Idyll markup language to automate the detailed instrumentation of interactive articles and corresponding visual analysis tools for inspecting reader behavior at both micro‐ and macro‐levels. We present three case studies of interactive articles that were instrumented, posted online, and promoted via social media to reach broad audiences, and share data from over 50,000 reader sessions. We demonstrate the use of our tools to characterize article‐specific interaction patterns, compare behavior across desktop and mobile devices, and reveal reading patterns common across articles. Our contributed findings, tools, and corpus of behavioral data can help advance and inform more comprehensive studies of narrative visualization. | false | false | [
"Matthew Conlen",
"Alex Kale",
"Jeffrey Heer"
] | [] | [] | [] |
EuroVis | 2,019 | Characterizing Exploratory Visual Analysis: A Literature Review and Evaluation of Analytic Provenance in Tableau | 10.1111/cgf.13678 | Supporting exploratory visual analysis (EVA) is a central goal of visualization research, and yet our understanding of the process is arguably vague and piecemeal. We contribute a consistent definition of EVA through review of the relevant literature, and an empirical evaluation of existing assumptions regarding how analysts perform EVA using Tableau, a popular visual analysis tool. We present the results of a study where 27 Tableau users answered various analysis questions across 3 datasets. We measure task performance, identify recurring patterns across participants' analyses, and assess variance from task specificity and dataset. We find striking differences between existing assumptions and the collected data. Participants successfully completed a variety of tasks, with over 80% accuracy across focused tasks with measurably correct answers. The observed cadence of analyses is surprisingly slow compared to popular assumptions from the database community. We find significant overlap in analyses across participants, showing that EVA behaviors can be predictable. Furthermore, we find few structural differences between behavior graphs for open‐ended and more focused exploration tasks. | false | false | [
"Leilani Battle",
"Jeffrey Heer"
] | [] | [] | [] |
EuroVis | 2,019 | ChronoCorrelator: Enriching Events with Time Series | 10.1111/cgf.13697 | Event sequences and time series are widely recorded in many application domains; examples are stock market prices, electronic health records, server operation and performance logs. Common goals for recording are monitoring, root cause analysis and predictive analytics. Current analysis methods generally focus on the exploration of either event sequences or time series. However, deeper insights are gained by combining both. We present a visual analytics approach where users can explore both time series and event data simultaneously, combining visualization, automated methods and human interaction. We enable users to iteratively refine the visualization. Correlations between event sequences and time series can be found by means of an interactive algorithm, which also computes the presence of monotonic effects. We illustrate the effectiveness of our method by applying it to real world and synthetic data sets. | false | false | [
"M. A. M. M. van Dortmont",
"Stef van den Elzen",
"Jarke J. van Wijk"
] | [] | [] | [] |
EuroVis | 2,019 | ClustMe: A Visual Quality Measure for Ranking Monochrome Scatterplots based on Cluster Patterns | 10.1111/cgf.13684 | We propose ClustMe, a new visual quality measure to rank monochrome scatterplots based on cluster patterns. ClustMe is based on data collected from a human‐subjects study, in which 34 participants judged synthetically generated cluster patterns in 1000 scatterplots. We generated these patterns by carefully varying the free parameters of a simple Gaussian Mixture Model with two components, and asked the participants to count the number of clusters they could see (1 or more than 1). Based on the results, we form ClustMe by selecting the model that best predicts these human judgments among 7 different state‐of‐the‐art merging techniques (Demp). To quantitatively evaluate ClustMe, we conducted a second study, in which 31 human subjects ranked 435 pairs of scatterplots of real and synthetic data in terms of cluster patterns complexity. We use this data to compare ClustMe's performance to 4 other state‐of‐the‐art clustering measures, including the well‐known Clumpiness scagnostics. We found that of all measures, ClustMe is in strongest agreement with the human rankings. | false | false | [
"Mostafa M. Abbas",
"Michaël Aupetit 0001",
"Michael Sedlmair",
"Halima Bensmail"
] | [] | [] | [] |
EuroVis | 2,019 | CV3: Visual Exploration, Assessment, and Comparison of CVs | 10.1111/cgf.13675 | The Curriculum Vitae (CV, also referred to as “résumé”) is an established representation of a person's academic and professional history. A typical CV is comprised of multiple sections associated with spatio‐temporal, nominal, hierarchical, and ordinal data. The main task of a recruiter is, given a job application with specific requirements, to compare and assess CVs in order to build a short list of promising candidates to interview. Commonly, this is done by viewing CVs in a side‐by‐side fashion. This becomes challenging when comparing more than two CVs, because the reader is required to switch attention between them. Furthermore, there is no guarantee that the CVs are structured similarly, thus making the overview cluttered and significantly slowing down the comparison process. In order to address these challenges, in this paper we propose “CV3”, an interactive exploration environment offering users a new way to explore, assess, and compare multiple CVs, to suggest suitable candidates for specific job requirements. We validate our system by means of domain expert feedback whose results highlight both the efficacy of our approach and its limitations. We learned that CV3 eases the overall burden of recruiters thereby assisting them in the selection process. | false | false | [
"Velitchko Andreev Filipov",
"Alessio Arleo",
"Paolo Federico 0001",
"Silvia Miksch"
] | [] | [] | [] |
EuroVis | 2,019 | Designing Animated Transitions to Convey Aggregate Operations | 10.1111/cgf.13709 | Data can be aggregated in many ways before being visualized in charts, profoundly affecting what a chart conveys. Despite this importance, the type of aggregation is often communicated only via axis titles. In this paper, we investigate the use of animation to disambiguate different types of aggregation and communicate the meaning of aggregate operations. We present design rationales for animated transitions depicting aggregate operations and present the results of an experiment assessing the impact of these different transitions on identification tasks. We find that judiciously staged animated transitions can improve subjects' accuracy at identifying the aggregation performed, though sometimes with longer response times than with static transitions. Through an analysis of participants' rankings and qualitative responses, we find a consistent preference for animation over static transitions and highlight visual features subjects report relying on to make their judgments. We conclude by extending our animation designs to more complex charts of aggregated data such as box plots and bootstrapped confidence intervals. | false | false | [
"Younghoon Kim",
"Michael Correll",
"Jeffrey Heer"
] | [] | [] | [] |
EuroVis | 2,019 | DIVA: Exploration and Validation of Hypothesized Drug-Drug Interactions | 10.1111/cgf.13674 | Adverse reactions caused by drug‐drug interactions are a major public health concern. Currently, adverse reaction signals are detected through a tedious manual process in which drug safety analysts review a large number of reports collected through post‐marketing drug surveillance. While computational techniques in support of this signal analysis are necessary, alone they are not sufficient. In particular, when machine learning techniques are applied to extract candidate signals from reports, the resulting set is (1) too large in size, i.e., exponential to the number of unique drugs and reactions in reports, (2) disconnected from the underlying reports that serve as evidence and context, and (3) ultimately requires human intervention to be validated in the domain context as a true signal warranting action. In this work, we address these challenges though a visual analytics system, DIVA, designed to align with the drug safety analysis workflow by supporting the detection, screening, and verification of candidate drug interaction signals. DTVA's abstractions and encodings are informed by formative interviews with drug safety analysts. DIVA's coordinated visualizations realize a proposed novel augmented interaction data model (AIM) which links signals generated by machine learning techniques with domain‐specific metadata critical for signal analysis. DIVA's alignment with the drug review process allows an analyst to interactively screen for important signals, triage signals for in‐depth investigation, and validate signals by reviewing the underlying reports that serve as evidence. The evaluation of DIVA encompasses case‐studies and interviews by drug analysts at the US Food and Drug Administration ‐ both of which confirm that DIVA indeed is effective in supporting analysts in the critical task of exploring and verifying dangerous drug‐drug interactions. | false | false | [
"Tabassum Kakar",
"Xiao Qin 0003",
"Elke A. Rundensteiner",
"Lane Harrison",
"Sanjay K. Sahoo",
"Suranjan De"
] | [] | [] | [] |
EuroVis | 2,019 | Efficient Optimal Overlap Removal: Algorithms and Experiments | 10.1111/cgf.13722 | Motivated by visualizing spatial data using proportional symbols, we study the following problem: given a set of overlapping squares of varying sizes, minimally displace the squares as to remove the overlap while maintaining the orthogonal order on their centers. Though this problem is NP‐hard, we show that rotating the squares by 45 degrees into diamonds allows for a linear or convex quadratic program. It is thus efficiently solvable even for relatively large instances.This positive result and the flexibility offered by constraint programming allow us to study various trade‐offs for overlap removal. Specifically, we model and evaluate through computational experiments the relations between displacement, scale and order constraints for static data, and between displacement and temporal coherence for time‐varying data. Finally, we also explore the generalization of our methodology to other shapes. | false | false | [
"Wouter Meulemans"
] | [] | [] | [] |
EuroVis | 2,019 | Evaluating image quality measures to assess the impact of lossy data compression applied to climate simulation data | 10.1111/cgf.13707 | Applying lossy data compression to climate model output is an attractive means of reducing the enormous volumes of data generated by climate models. However, because lossy data compression does not exactly preserve the original data, its application to scientific data must be done judiciously. To this end, a collection of measures is being developed to evaluate various aspects of lossy compression quality on climate model output. Given the importance of data visualization to climate scientists interacting with model output, any suite of measures must include a means of assessing whether images generated from the compressed model data are noticeably different from images based on the original model data. Therefore, in this work we conduct a forced‐choice visual evaluation study with climate model data that surveyed more than one hundred participants with domain relevant expertise. In addition to the images created from unaltered climate model data, study images are generated from model data that is subjected to two different types of lossy compression approaches and multiple levels (amounts) of compression. Study participants indicate whether a visual difference can be seen, with respect to the reference image, due to lossy compression effects. We assess the relationship between the perceptual scores from the user study to a number of common (full reference) image quality assessment (IQA) measures, and use statistical models to suggest appropriate measures and thresholds for evaluating lossily compressed climate data. We find the structural similarity index (SSIM) to perform the best, and our findings indicate that the threshold required for climate model data is much higher than previous findings in the literature. | false | false | [
"Allison H. Baker",
"Dorit Hammerling",
"Terece L. Turton"
] | [] | [] | [] |
EuroVis | 2,019 | Examining Implicit Discretization in Spectral Schemes | 10.1111/cgf.13695 | Two of the primary reasons rainbow color maps are considered ineffective trace back to the idea that they implicitly discretize encoded data into hue‐based bands, yet no research addresses what this discretization looks like or how consistent it is across individuals. This paper presents an exploratory study designed to empirically investigate the implicit discretization of common spectral schemes and explore whether the phenomenon can be modeled by variations in lightness, chroma, and hue. Our results suggest that three commonly used rainbow color maps are implicitly discretized with consistency across individuals. The results also indicate, however, that this implicit discretization varies across different datasets, in a way that suggests the visualization community's understanding of both rainbow color maps, and more generally effective color usage, remains incomplete. | false | false | [
"P. Samuel Quinan",
"Lace M. K. Padilla",
"Sarah H. Creem-Regehr",
"Miriah D. Meyer"
] | [] | [] | [] |
EuroVis | 2,019 | External Labeling Techniques: A Taxonomy and Survey | 10.1111/cgf.13729 | External labeling is frequently used for annotating features in graphical displays and visualizations, such as technical illustrations, anatomical drawings, or maps, with textual information. Such a labeling connects features within an illustration by thin leader lines with their labels, which are placed in the empty space surrounding the image. Over the last twenty years, a large body of literature in diverse areas of computer science has been published that investigates many different aspects, models, and algorithms for automatically placing external labels for a given set of features. This state‐of‐the‐art report introduces a first unified taxonomy for categorizing the different results in the literature and then presents a comprehensive survey of the state of the art, a sketch of the most relevant algorithmic techniques for external labeling algorithms, as well as a list of open research challenges in this multidisciplinary research field. | false | false | [
"Michael A. Bekos",
"Benjamin Niedermann",
"Martin Nöllenburg"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1902.01454v2",
"icon": "paper"
}
] |
EuroVis | 2,019 | Focus+Context Exploration of Hierarchical Embeddings | 10.1111/cgf.13711 | Hierarchical embeddings, such as HSNE, address critical visual and computational scalability issues of traditional techniques for dimensionality reduction. The improved scalability comes at the cost of the need for increased user interaction for exploration. In this paper, we provide a solution for the interactive visual Focus+Context exploration of such embeddings. We explain how to integrate embedding parts from different levels of detail, corresponding to focus and context groups, in a joint visualization. We devise an according interaction model that relates typical semantic operations on a Focus+Context visualization with the according changes in the level‐of‐detail‐hierarchy of the embedding, including also a mode for comparative Focus+Context exploration and extend HSNE to incorporate the presented interaction model. In order to demonstrate the effectiveness of our approach, we present a use case based on the visual exploration of multi‐dimensional images. | false | false | [
"Thomas Höllt",
"Anna Vilanova",
"Nicola Pezzotti",
"Boudewijn P. F. Lelieveldt",
"Helwig Hauser"
] | [] | [] | [] |
EuroVis | 2,019 | Follow The Clicks: Learning and Anticipating Mouse Interactions During Exploratory Data Analysis | 10.1111/cgf.13670 | The goal of visual analytics is to create a symbiosis between human and computer by leveraging their unique strengths. While this model has demonstrated immense success, we are yet to realize the full potential of such a human‐computer partnership. In a perfect collaborative mixed‐initiative system, the computer must possess skills for learning and anticipating the users' needs. Addressing this gap, we propose a framework for inferring attention from passive observations of the user's click, thereby allowing accurate predictions of future events. We demonstrate this technique with a crime map and found that users' clicks can appear in our prediction set 92% ‐ 97% of the time. Further analysis shows that we can achieve high prediction accuracy typically after three clicks. Altogether, we show that passive observations of interaction data can reveal valuable information that will allow the system to learn and anticipate future events. | false | false | [
"Alvitta Ottley",
"Roman Garnett",
"Ran Wan"
] | [
"HM"
] | [] | [] |
EuroVis | 2,019 | Hybrid Touch/Tangible Spatial 3D Data Selection | 10.1111/cgf.13710 | We discuss spatial selection techniques for three‐dimensional datasets. Such 3D spatial selection is fundamental to exploratory data analysis. While 2D selection is efficient for datasets with explicit shapes and structures, it is less efficient for data without such properties. We first propose a new taxonomy of 3D selection techniques, focusing on the amount of control the user has to define the selection volume. We then describe the 3D spatial selection technique Tangible Brush, which gives manual control over the final selection volume. It combines 2D touch with 6‐DOF 3D tangible input to allow users to perform 3D selections in volumetric data. We use touch input to draw a 2D lasso, extruding it to a 3D selection volume based on the motion of a tangible, spatially‐aware tablet. We describe our approach and present its quantitative and qualitative comparison to state‐of‐the‐art structure‐dependent selection. Our results show that, in addition to being dataset‐independent, Tangible Brush is more accurate than existing dataset‐dependent techniques, thus providing a trade‐off between precision and effort. | false | false | [
"Lonni Besançon",
"Mickaël Sereno",
"Lingyun Yu 0001",
"Mehdi Ammi",
"Tobias Isenberg 0001"
] | [] | [] | [] |
EuroVis | 2,019 | IGM-Vis: Analyzing Intergalactic and Circumgalactic Medium Absorption Using Quasar Sightlines in a Cosmic Web Context | 10.1111/cgf.13705 | We introduce IGM‐Vis, a novel astrophysics visualization and data analysis application for investigating galaxies and the gas that surrounds them in context with their larger scale environment, the Cosmic Web. Environment is an important factor in the evolution of galaxies from actively forming stars to quiescent states with little, if any, discernible star formation activity. The gaseous halos of galaxies (the circumgalactic medium, or CGM) play a critical role in their evolution, because the gas necessary to fuel star formation and any gas expelled from widely observed galactic winds must encounter this interface region between galaxies and the intergalactic medium (IGM). We present a taxonomy of tasks typically employed in IGM/CGM studies informed by a survey of astrophysicists at various career levels, and demonstrate how these tasks are facilitated via the use of our visualization software. Finally, we evaluate the effectiveness of IGM‐Vis through two in‐depth use cases that depict real‐world analysis sessions that use IGM/CGM data. | false | false | [
"Joseph N. Burchett",
"David Abramov",
"Jasmine Otto",
"Cassia Artanegara",
"J. Xavier Prochaska",
"Angus G. Forbes"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1812.07092v2",
"icon": "paper"
}
] |
EuroVis | 2,019 | InsideInsights: Integrating Data-Driven Reporting in Collaborative Visual Analytics | 10.1111/cgf.13717 | Analyzing complex data is a non‐linear process that alternates between identifying discrete facts and developing overall assessments and conclusions. In addition, data analysis rarely occurs in solitude; multiple collaborators can be engaged in the same analysis, or intermediate results can be reported to stakeholders. However, current data‐driven communication tools are detached from the analysis process and promote linear stories that forego the hierarchical and branching nature of data analysis, which leads to either too much or too little detail in the final report. We propose a conceptual design for integrated data‐driven reporting that allows for iterative structuring of insights into hierarchies linked to analytic provenance and chosen analysis views. The hierarchies become dynamic and interactive reports where collaborators can review and modify the analysis at a desired level of detail. Our web‐based InsideInsights system provides interaction techniques to annotate states of analytic components, structure annotations, and link them to appropriate presentation views. We demonstrate the generality and usefulness of our system with two use cases and a qualitative expert review. | false | false | [
"Andreas Mathisen",
"Tom Horak",
"Clemens Nylandsted Klokmose",
"Kaj Grønbæk",
"Niklas Elmqvist"
] | [] | [] | [] |
EuroVis | 2,019 | Interactive Visualization of Flood and Heavy Rain Simulations | 10.1111/cgf.13669 | In this paper, we present a real‐time technique to visualize large‐scale adaptive height fields with C ‐continuous surface reconstruction. Grid‐based shallow water simulation is an indispensable tool for interactive flood management applications. Height fields defined on adaptive grids are often the only viable option to store and process the massive simulation data. Their visualization requires the reconstruction of a continuous surface from the spatially discrete simulation data. For regular grids, fast linear and cubic interpolation are commonly used for surface reconstruction. For adaptive grids, however, there exists no higher‐order interpolation technique fast enough for interactive applications.Our proposed technique bridges the gap between fast linear and expensive higher‐order interpolation for adaptive surface reconstruction. During reconstruction, no matter if regular or adaptive, discretization and interpolation artifacts can occur, which domain experts consider misleading and unaesthetic. We take into account boundary conditions to eliminate these artifacts, which include water climbing uphill, diving towards walls, and leaking through thin objects. We apply realistic water shading with visual cues for depth perception and add waves and foam synthesized from the simulation data to emphasize flow directions. The versatility and performance of our technique are demonstrated in various real‐world scenarios. A survey conducted with domain experts of different backgrounds and concerned citizens proves the usefulness and effectiveness of our technique. | false | false | [
"Daniel Cornel",
"Andreas Buttinger-Kreuzhuber",
"Artem Konev",
"Zsolt Horváth",
"Michael Wimmer 0001",
"R. Heidrich",
"Jürgen Waser"
] | [
"HM"
] | [] | [] |
EuroVis | 2,019 | Interactive Volumetric Visual Analysis of Glycogen-derived Energy Absorption in Nanometric Brain Structures | 10.1111/cgf.13700 | Digital acquisition and processing techniques are changing the way neuroscience investigation is carried out. Emerging applications range from statistical analysis on image stacks to complex connectomics visual analysis tools targeted to develop and test hypotheses of brain development and activity. In this work, we focus on neuroenergetics, a field where neuroscientists analyze nanoscale brain morphology and relate energy consumption to glucose storage in form of glycogen granules. In order to facilitate the understanding of neuroenergetic mechanisms, we propose a novel customized pipeline for the visual analysis of nanometric‐level reconstructions based on electron microscopy image data. Our framework supports analysis tasks by combining i) a scalable volume visualization architecture able to selectively render image stacks and corresponding labelled data, ii) a method for highlighting distance‐based energy absorption probabilities in form of glow maps, and iii) a hybrid connectivitybased and absorption‐based interactive layout representation able to support queries for selective analysis of areas of interest and potential activity within the segmented datasets. This working pipeline is currently used in a variety of studies in the neuroenergetics domain. Here, we discuss a test case in which the framework was successfully used by domain scientists for the analysis of aging effects on glycogen metabolism, extracting knowledge from a series of nanoscale brain stacks of rodents somatosensory cortex. | false | false | [
"Marco Agus",
"Corrado Calì",
"Ali K. Al-Awami",
"Enrico Gobbetti",
"Pierre J. Magistretti",
"Markus Hadwiger"
] | [] | [] | [] |
EuroVis | 2,019 | Investigating Effects of Visual Anchors on Decision-Making about Misinformation | 10.1111/cgf.13679 | Cognitive biases are systematic errors in judgment due to an over‐reliance on rule‐of‐thumb heuristics. Recent research suggests that cognitive biases, like numerical anchoring, transfers to visual analytics in the form of visual anchoring. However, it is unclear how visualization users can be visually anchored and how the anchors affect decision‐making. To investigate, we performed a between‐subjects laboratory experiment with 94 participants to analyze the effects of visual anchors and strategy cues using a visual analytics system. The decision‐making task was to identify misinformation from Twitter news accounts. Participants were randomly assigned to conditions that modified the scenario video (visual anchor) and/or strategy cues provided. Our findings suggest that such interventions affect user activity, speed, confidence, and, under certain circumstances, accuracy. We discuss implications of our results on the forking paths problem and raise concerns on how visualization researchers train users to avoid unintentionally anchoring users and affecting the end result. | false | false | [
"Ryan Wesslen",
"Sashank Santhanam",
"Alireza Karduni",
"Isaac Cho",
"Samira Shaikh",
"Wenwen Dou"
] | [] | [] | [] |
EuroVis | 2,019 | Investigating the Manual View Specification and Visualization by Demonstration Paradigms for Visualization Construction | 10.1111/cgf.13718 | Interactivity plays an important role in data visualization. Therefore, understanding how people create visualizations given different interaction paradigms provides empirical evidence to inform interaction design. We present a two‐phase study comparing people's visualization construction processes using two visualization tools: one implementing the manual view specification paradigm (Polestar) and another implementing visualization by demonstration (VisExemplar). Findings of our study indicate that the choice of interaction paradigm influences the visualization construction in terms of: 1) the overall effectiveness, 2) how participants phrase their goals, and 3) their perceived control and engagement. Based on our findings, we discuss trade‐offs and open challenges with these interaction paradigms. | false | false | [
"Bahador Saket",
"Alex Endert"
] | [] | [] | [] |
EuroVis | 2,019 | Kyrix: Interactive Pan/Zoom Visualizations at Scale | 10.1111/cgf.13708 | Pan and zoom are basic yet powerful interaction techniques for exploring large datasets. However, existing zoomable UI toolkits such as Pad++ and ZVTM do not provide the backend database support and data‐driven primitives that are necessary for creating large‐scale visualizations. This limitation in existing general‐purpose toolkits has led to many purpose‐built solutions (e.g. Google Maps and ForeCache) that address the issue of scalability but cannot be easily extended to support visualizations beyond their intended data types and usage scenarios. In this paper, we introduce Kyrix to ease the process of creating general and large‐scale web‐based pan/zoom visualizations. Kyrix is an integrated system that provides the developer with a concise and expressive declarative language along with a backend support for performance optimization of large‐scale data. To evaluate the scalability of Kyrix, we conducted a set of benchmarked experiments and show that Kyrix can support high interactivity (with an average latency of 100 ms or below) on pan/zoom visualizations of 100 million data points. We further demonstrate the accessibility of Kyrix through an observational study with 8 developers. Results indicate that developers can quickly learn Kyrix's underlying declarative model to create scalable pan/zoom visualizations. Finally, we provide a gallery of visualizations and show that Kyrix is expressive and flexible in that it can support the developer in creating a wide range of customized visualizations across different application domains and data types. | false | false | [
"Wenbo Tao",
"Xiaoyu Liu",
"Yedi Wang",
"Leilani Battle",
"Çagatay Demiralp",
"Remco Chang",
"Michael Stonebraker"
] | [] | [] | [] |
EuroVis | 2,019 | Latent Space Cartography: Visual Analysis of Vector Space Embeddings | 10.1111/cgf.13672 | Latent spaces—reduced‐dimensionality vector space embeddings of data, fit via machine learning—have been shown to capture interesting semantic properties and support data analysis and synthesis within a domain. Interpretation of latent spaces is challenging because prior knowledge, sometimes subtle and implicit, is essential to the process. We contribute methods for “latent space cartography”, the process of mapping and comparing meaningful semantic dimensions within latent spaces. We first perform a literature survey of relevant machine learning, natural language processing, and scientific research to distill common tasks and propose a workflow process. Next, we present an integrated visual analysis system for supporting this workflow, enabling users to discover, define, and verify meaningful relationships among data points, encoded within latent space dimensions. Three case studies demonstrate how users of our system can compare latent space variants in image generation, challenge existing findings on cancer transcriptomes, and assess a word embedding benchmark. | false | false | [
"Yang Liu 0136",
"Eunice Jun",
"Qisheng Li",
"Jeffrey Heer"
] | [] | [] | [] |
EuroVis | 2,019 | Linking and Layout: Exploring the Integration of Text and Visualization in Storytelling | 10.1111/cgf.13719 | Modern web technologies are enabling authors to create various forms of text visualization integration for storytelling. This integration may shape the stories' flow and thereby affect the reading experience. In this paper, we seek to understand two text visualization integration forms: (i) different text and visualization spatial arrangements (layout), namely, vertical and slideshow; and (ii) interactive linking of text and visualization (linking). Here, linking refers to a bidirectional interaction mode that explicitly highlights the explanatory visualization element when selecting narrative text and vice versa. Through a crowdsourced study with 180 participants, we measured the effect of layout and linking on the degree to which users engage with the story (user engagement), their understanding of the story content (comprehension), and their ability to recall the story information (recall). We found that participants performed significantly better in comprehension tasks with the slideshow layout. Participant recall was better with the slideshow layout under conditions with linking versus no linking. We also found that linking significantly increased user engagement. Additionally, linking and the slideshow layout were preferred by the participants. We also explored user reading behaviors with different conditions. | false | false | [
"Qiyu Zhi",
"Alvitta Ottley",
"Ronald A. Metoyer"
] | [] | [] | [] |
EuroVis | 2,019 | Multiple Views: different meanings and collocated words | 10.1111/cgf.13673 | We report on an in‐depth corpus linguistic study on ‘multiple views’ terminology and word collocation. We take a broad interpretation of these terms, and explore the meaning and diversity of their use in visualisation literature. First we explore senses of the term ‘multiple views’ (e.g., ‘multiple views’ can mean juxtaposition, many viewport projections or several alternative opinions). Second, we investigate term popularity and frequency of occurrences, investigating usage of ‘multiple’ and ‘view’ (e.g., multiple views, multiple visualisations, multiple sets). Third, we investigate word collocations and terms that have a similar sense (e.g., multiple views, side‐by‐side, small multiples). We built and used several corpora, including a 6‐million‐word corpus of all IEEE Visualisation conference articles published in IEEE Transactions on Visualisation and Computer Graphics 2012 to 2017. We draw on our substantial experience from early work in coordinated and multiple views, and with collocation analysis develop several lists of terms. This research provides insight into term use, a reference for novice and expert authors in visualisation, and contributes a taxonomy of ‘multiple view’ terms. | false | false | [
"Jonathan C. Roberts",
"Hayder Al-Maneea",
"Peter W. S. Butcher",
"Robert Lew",
"Geraint Rees 0002",
"Nirwan Sharma",
"Ana Frankenberg-Garcia"
] | [] | [] | [] |
EuroVis | 2,019 | netflower: Dynamic Network Visualization for Data Journalists | 10.1111/cgf.13721 | Journalists need visual interfaces that cater to the exploratory nature of their investigative activities. In this paper, we report on a four‐year design study with data journalists. The main result is netflower, a visual exploration tool that supports journalists in investigating quantitative flows in dynamic network data for story‐finding. The visual metaphor is based on Sankey diagrams and has been extended to make it capable of processing large amounts of input data as well as network change over time. We followed a structured, iterative design process including requirement analysis and multiple design and prototyping iterations in close cooperation with journalists. To validate our concept and prototype, a workshop series and two diary studies were conducted with journalists. Our findings indicate that the prototype can be picked up quickly by journalists and valuable insights can be achieved in a few hours. The prototype can be accessed at: http://netflower.fhstp.ac.at/ | false | false | [
"Christina Stoiber",
"Alexander Rind",
"Florian Grassinger",
"Robert Gutounig",
"Eva Goldgruber",
"Michael Sedlmair",
"Stefan Emrich",
"Wolfgang Aigner"
] | [] | [
"PW",
"P",
"C"
] | [
{
"name": "Paper Preprint",
"url": "https://phaidra.fhstp.ac.at/o:4838",
"icon": "paper"
},
{
"name": "Project Website with Demo",
"url": "https://netflower.fhstp.ac.at/",
"icon": "project_website"
},
{
"name": "GitHub",
"url": "https://github.com/VALIDproject/netflower",
"icon": "code"
}
] |
EuroVis | 2,019 | Optimizing Stepwise Animation in Dynamic Set Diagrams | 10.1111/cgf.13668 | A set diagram represents the membership relation among data elements. It is often visualized as secondary information on top of primary information, such as the spatial positions of elements on maps and charts. Visualizing the temporal evolution of such set diagrams as well as their primary features is quite important; however, conventional approaches have only focused on the temporal behavior of the primary features and do not provide an effective means to highlight notable transitions within the set relationships. This paper presents an approach for generating a stepwise animation between set diagrams by decomposing the entire transition into atomic changes associated with individual data elements. The key idea behind our approach is to optimize the ordering of the atomic changes such that the synthesized animation minimizes unwanted set occlusions by considering their depth ordering and reduces the gaze shift between two consecutive stepwise changes. Experimental results and a user study demonstrate that the proposed approach effectively facilitates the visual identification of the detailed transitions inherent in dynamic set diagrams. | false | false | [
"Kazuyo Mizuno",
"Hsiang-Yun Wu",
"Shigeo Takahashi",
"Takeo Igarashi"
] | [
"HM"
] | [] | [] |
EuroVis | 2,019 | Oui! Outlier Interpretation on Multi-dimensional Data via Visual Analytics | 10.1111/cgf.13683 | Outliers, the data instances that do not conform with normal patterns in a dataset, are widely studied in various domains, such as cybersecurity, social analysis, and public health. By detecting and analyzing outliers, users can either gain insights into abnormal patterns or purge the data of errors. However, different domains usually have different considerations with respect to outliers. Understanding the defining characteristics of outliers is essential for users to select and filter appropriate outliers based on their domain requirements. Unfortunately, most existing work focuses on the efficiency and accuracy of outlier detection, neglecting the importance of outlier interpretation. To address these issues, we propose Oui, a visual analytic system that helps users understand, interpret, and select the outliers detected by various algorithms. We also present a usage scenario on a real dataset and a qualitative user study to demonstrate the effectiveness and usefulness of our system. | false | false | [
"Xun Zhao",
"Weiwei Cui",
"Yanhong Wu",
"Haidong Zhang",
"Huamin Qu",
"Dongmei Zhang 0001"
] | [] | [] | [] |
EuroVis | 2,019 | Ray Tracing Generalized Tube Primitives: Method and Applications | 10.1111/cgf.13703 | We present a general high‐performance technique for ray tracing generalized tube primitives. Our technique efficiently supports tube primitives with fixed and varying radii, general acyclic graph structures with bifurcations, and correct transparency with interior surface removal. Such tube primitives are widely used in scientific visualization to represent diffusion tensor imaging tractographies, neuron morphologies, and scalar or vector fields of 3D flow. We implement our approach within the OSPRay ray tracing framework, and evaluate it on a range of interactive visualization use cases of fixed‐ and varying‐radius streamlines, pathlines, complex neuron morphologies, and brain tractographies. Our proposed approach provides interactive, high‐quality rendering, with low memory overhead. | false | false | [
"Mengjiao Han",
"Ingo Wald",
"Will Usher 0001",
"Qi Wu 0015",
"Feng Wang 0013",
"Valerio Pascucci",
"Charles D. Hansen",
"Christopher R. Johnson 0001"
] | [] | [] | [] |
EuroVis | 2,019 | Robust Extraction and Simplification of 2D Symmetric Tensor Field Topology | 10.1111/cgf.13693 | In this work, we propose a controlled simplification strategy for degenerated points in symmetric 2D tensor fields that is based on the topological notion of robustness. Robustness measures the structural stability of the degenerate points with respect to variation in the underlying field. We consider an entire pipeline for generating a hierarchical set of degenerate points based on their robustness values. Such a pipeline includes the following steps: the stable extraction and classification of degenerate points using an edge labeling algorithm, the computation and assignment of robustness values to the degenerate points, and the construction of a simplification hierarchy. We also discuss the challenges that arise from the discretization and interpolation of real world data. | false | false | [
"Jochen Jankowai",
"Bei Wang 0001",
"Ingrid Hotz"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "https://osf.io/k67qg",
"icon": "paper"
}
] |
EuroVis | 2,019 | Robust Reference Frame Extraction from Unsteady 2D Vector Fields with Convolutional Neural Networks | 10.1111/cgf.13689 | Robust feature extraction is an integral part of scientific visualization. In unsteady vector field analysis, researchers recently directed their attention towards the computation of near‐steady reference frames for vortex extraction, which is a numerically challenging endeavor. In this paper, we utilize a convolutional neural network to combine two steps of the visualization pipeline in an end‐to‐end manner: the filtering and the feature extraction. We use neural networks for the extraction of a steady reference frame for a given unsteady 2D vector field. By conditioning the neural network to noisy inputs and resampling artifacts, we obtain numerically stabler results than existing optimization‐based approaches. Supervised deep learning typically requires a large amount of training data. Thus, our second contribution is the creation of a vector field benchmark data set, which is generally useful for any local deep learning‐based feature extraction. Based on Vatistas velocity profile, we formulate a parametric vector field mixture model that we parameterize based on numerically‐computed example vector fields in near‐steady reference frames. Given the parametric model, we can efficiently synthesize thousands of vector fields that serve as input to our deep learning architecture. The proposed network is evaluated on an unseen numerical fluid flow simulation. | false | false | [
"Byungsoo Kim 0001",
"Tobias Günther"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1903.10255v1",
"icon": "paper"
}
] |
EuroVis | 2,019 | Route-Aware Edge Bundling for Visualizing Origin-Destination Trails in Urban Traffic | 10.1111/cgf.13712 | Origin‐destination (OD) trails describe movements across space. Typical visualizations thereof use either straight lines or plot the actual trajectories. To reduce clutter inherent to visualizing large OD datasets, bundling methods can be used. Yet, bundling OD trails in urban traffic data remains challenging. Two specific reasons hereof are the constraints implied by the underlying road network and the difficulty of finding good bundling settings. To cope with these issues, we propose a new approach called Route Aware Edge Bundling (RAEB). To handle road constraints, we first generate a hierarchical model of the road‐and‐trajectory data. Next, we derive optimal bundling parameters, including kernel size and number of iterations, for a user‐selected level of detail of this model, thereby allowing users to explicitly trade off simplification vs accuracy. We demonstrate the added value of RAEB compared to state‐of‐the‐art trail bundling methods on both synthetic and real‐world traffic data for tasks that include the preservation of road network topology and the support of multiscale exploration. | false | false | [
"Wei Zeng 0004",
"Qiaomu Shen",
"Yuzhe Jiang",
"Alexandru C. Telea"
] | [] | [] | [] |
EuroVis | 2,019 | Scalable Ray Tracing Using the Distributed FrameBuffer | 10.1111/cgf.13702 | Image‐ and data‐parallel rendering across multiple nodes on high‐performance computing systems is widely used in visualization to provide higher frame rates, support large data sets, and render data in situ. Specifically for in situ visualization, reducing bottlenecks incurred by the visualization and compositing is of key concern to reduce the overall simulation runtime. Moreover, prior algorithms have been designed to support either image‐ or data‐parallel rendering and impose restrictions on the data distribution, requiring different implementations for each configuration. In this paper, we introduce the Distributed FrameBuffer, an asynchronous image‐processing framework for multi‐node rendering. We demonstrate that our approach achieves performance superior to the state of the art for common use cases, while providing the flexibility to support a wide range of parallel rendering algorithms and data distributions. By building on this framework, we extend the open‐source ray tracing library OSPRay with a data‐distributed API, enabling its use in data‐distributed and in situ visualization applications. | false | false | [
"Will Usher 0001",
"Ingo Wald",
"Jefferson Amstutz",
"Johannes Günther 0001",
"Carson Brownlee",
"Valerio Pascucci"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2305.07083v1",
"icon": "paper"
}
] |
EuroVis | 2,019 | Segmentifier: Interactive Refinement of Clickstream Data | 10.1111/cgf.13715 | Clickstream data has the potential to provide insights into e‐commerce consumer behavior, but previous techniques fall short of handling the scale and complexity of real‐world datasets because they require relatively clean and small input. We present Segmentifier, a novel visual analytics interface that supports an iterative process of refining collections of action sequences into meaningful segments. We present task and data abstractions for clickstream data analysis, leading to a high‐level model built around an iterative view‐refine‐record loop with outcomes of conclude with an answer, export segment for further analysis in downstream tools, or abandon the question for a more fruitful analysis path. Segmentifier supports fast and fluid refinement of segments through tightly coupled visual encoding and interaction with a rich set of views that show evocative derived attributes for segments, sequences, and actions in addition to underlying raw sequences. These views support fast and fluid refinement of segments through filtering and partitioning attribute ranges. Interactive visual queries on custom action sequences are aggregated according to a three‐level hierarchy. Segmentifier features a detailed glyph‐based visual history of the automatically recorded analysis process showing the provenance of each segment as an analysis path of attribute constraints. We demonstrate the effectiveness of our approach through a usage scenario with real‐world data and a case study documenting the insights gained by a corporate e‐commerce analyst. | false | false | [
"K. Dextras-Romagnino",
"Tamara Munzner"
] | [] | [] | [] |
EuroVis | 2,019 | State-of-the-art in Multi-Light Image Collections for Surface Visualization and Analysis | 10.1111/cgf.13732 | Multi‐Light Image Collections (MLICs), i.e., stacks of photos of a scene acquired with a fixed viewpoint and a varying surface illumination, provide large amounts of visual and geometric information. In this survey, we provide an up‐to‐date integrative view of MLICs as a mean to gain insight on objects through the analysis and visualization of the acquired data. After a general overview of MLICs capturing and storage, we focus on the main approaches to produce representations usable for visualization and analysis. In this context, we first discuss methods for direct exploration of the raw data. We then summarize approaches that strive to emphasize shape and material details by fusing all acquisitions in a single enhanced image. Subsequently, we focus on approaches that produce relightable images through intermediate representations. This can be done both by fitting various analytic forms of the light transform function, or by locally estimating the parameters of physically plausible models of shape and reflectance and using them for visualization and analysis. We finally review techniques that improve object understanding by using illustrative approaches to enhance relightable models, or by extracting features and derived maps. We also review how these methods are applied in several, main application domains, and what are the available tools to perform MLIC visualization and analysis. We finally point out relevant research issues, analyze research trends, and offer guidelines for practical applications. | false | false | [
"Ruggero Pintus",
"Tinsae Dulecha",
"Irina Ciortan",
"Enrico Gobbetti",
"Andrea Giachetti 0001"
] | [] | [] | [] |
EuroVis | 2,019 | State-of-the-Art Report: Visual Computing in Radiation Therapy Planning | 10.1111/cgf.13726 | Radiation therapy (RT) is one of the major curative approaches for cancer. It is a complex and risky treatment approach, which requires precise planning, prior to the administration of the treatment. Visual Computing (VC) is a fundamental component of RT planning, providing solutions in all parts of the process—from imaging to delivery. Despite the significant technological advancements of RT over the last decades, there are still many challenges to address. This survey provides an overview of the compound planning process of RT, and of the ways that VC has supported RT in all its facets. The RT planning process is described to enable a basic understanding in the involved data, users and workflow steps. A systematic categorization and an extensive analysis of existing literature in the joint VC/RT research is presented, covering the entire planning process. The survey concludes with a discussion on lessons learnt, current status, open challenges, and future directions in VC/RT research. | false | false | [
"Matthias Schlachter",
"Renata G. Raidou",
"Ludvig P. Muren",
"Bernhard Preim",
"Paul Martin Putora",
"Katja Bühler"
] | [] | [] | [] |
EuroVis | 2,019 | SurgeryCuts: Embedding Additional Information in Maps without Occluding Features | 10.1111/cgf.13685 | Visualizing contextual information to a map often comes at the expense of overplotting issues. Especially for use cases with relevant map features in the immediate vicinity of an information to add, occlusion of the relevant map context should be avoided. We present SurgeryCuts, a map manipulation technique for the creation of additional canvas area for contextual visualizations on maps. SurgeryCuts is occlusion‐free and does not shift, zoom or alter the map viewport. Instead, relevant parts of the map can be cut apart. The affected area is controlledly distorted using a parameterizable warping function fading out the map distortion depending on the distance to the cut. We define extended metrics for our approach and compare to related approaches. As well, we demonstrate the applicability of our approach at the example of tangible use cases and a comparative user study. | false | false | [
"Marco Angelini",
"Juri Buchmüller",
"Daniel A. Keim",
"Philipp Meschenmoser",
"Giuseppe Santucci"
] | [] | [] | [] |
EuroVis | 2,019 | Tasks, Techniques, and Tools for Genomic Data Visualization | 10.1111/cgf.13727 | Genomic data visualization is essential for interpretation and hypothesis generation as well as a valuable aid in communicating discoveries. Visual tools bridge the gap between algorithmic approaches and the cognitive skills of investigators. Addressing this need has become crucial in genomics, as biomedical research is increasingly data‐driven and many studies lack well‐defined hypotheses. A key challenge in data‐driven research is to discover unexpected patterns and to formulate hypotheses in an unbiased manner in vast amounts of genomic and other associated data. Over the past two decades, this has driven the development of numerous data visualization techniques and tools for visualizing genomic data. Based on a comprehensive literature survey, we propose taxonomies for data, visualization, and tasks involved in genomic data visualization. Furthermore, we provide a comprehensive review of published genomic visualization tools in the context of the proposed taxonomies. | false | false | [
"Sabrina Nusrat",
"Theresa Anisja Harbig",
"Nils Gehlenborg"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1905.02853v1",
"icon": "paper"
}
] |
EuroVis | 2,019 | The Dependent Vectors Operator | 10.1111/cgf.13687 | In this paper, we generalize the parallel vectors operator due to Peikert and Roth to arbitrary dimension, i.e., to four‐dimensional fields and beyond. Whereas the original operator tested for parallelism of two (derived) 2D or 3D vector fields, we reformulate the concept in terms of linear dependency of sets of vector fields, and propose a generic technique to extract and filter the solution manifolds. We exemplify our approach for vortex cores, bifurcations, and ridges as well as valleys in higher dimensions. | false | false | [
"Lutz Hofmann",
"Filip Sadlo"
] | [] | [] | [] |
EuroVis | 2,019 | The State of the Art in Visual Analysis Approaches for Ocean and Atmospheric Datasets | 10.1111/cgf.13731 | The analysis of ocean and atmospheric datasets offers a unique set of challenges to scientists working in different application areas. These challenges include dealing with extremely large volumes of multidimensional data, supporting interactive visual analysis, ensembles exploration and visualization, exploring model sensitivities to inputs, mesoscale ocean features analysis, predictive analytics, heterogeneity and complexity of observational data, representing uncertainty, and many more. Researchers across disciplines collaborate to address such challenges, which led to significant research and development advances in ocean and atmospheric sciences, and also in several relevant areas such as visualization and visual analytics, big data analytics, machine learning and statistics. In this report, we perform an extensive survey of research advances in the visual analysis of ocean and atmospheric datasets. First, we survey the task requirements by conducting interviews with researchers, domain experts, and end users working with these datasets on a spectrum of analytics problems in the domain of ocean and atmospheric sciences. We then discuss existing models and frameworks related to data analysis, sense‐making, and knowledge discovery for visual analytics applications. We categorize the techniques, systems, and tools presented in the literature based on the taxonomies of task requirements, interaction methods, visualization techniques, machine learning and statistical methods, evaluation methods, data types, data dimensions and size, spatial scale and application areas. We then evaluate the task requirements identified based on our interviews with domain experts in the context of categorized research based on our taxonomies, and existing models and frameworks of visual analytics to determine the extent to which they fulfill these task requirements, and identify the gaps in current research. In the last part of this report, we summarize the trends, challenges, and opportunities for future research in this area.(see http://www.acm.org/about/class/class/2012) | false | false | [
"Shehzad Afzal",
"Mohamad Mazen Hittawe",
"Sohaib Ghani",
"Tahira Jamil",
"Omar M. Knio",
"Markus Hadwiger",
"Kevin I.-J. Ho"
] | [] | [] | [] |
EuroVis | 2,019 | The State of the Art in Visualizing Multivariate Networks | 10.1111/cgf.13728 | Multivariate networks are made up of nodes and their relationships (links), but also data about those nodes and links as attributes. Most real‐world networks are associated with several attributes, and many analysis tasks depend on analyzing both, relationships and attributes. Visualization of multivariate networks, however, is challenging, especially when both the topology of the network and the attributes need to be considered concurrently. In this state‐of‐the‐art report, we analyze current practices and classify techniques along four axes: layouts, view operations, layout operations, and data operations. We also provide an analysis of tasks specific to multivariate networks and give recommendations for which technique to use in which scenario. Finally, we survey application areas and evaluation methodologies. | false | false | [
"Carolina Nobre",
"Miriah D. Meyer",
"Marc Streit",
"Alexander Lex"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "https://osf.io/upbm2",
"icon": "paper"
}
] |
EuroVis | 2,019 | Topic Tomographies (TopTom): a visual approach to distill information from media streams | 10.1111/cgf.13714 | In this paper we present Top Tom, a digital platform whose goal is to provide analytical and visual solutions for the exploration of a dynamic corpus of user‐generated messages and media articles, with the aim of i) distilling the information from thousands of documents in a low‐dimensional space of explainable topics, ii) cluster them in a hierarchical fashion while allowing to drill down to details and stories as constituents of the topics, iii) spotting trends and anomalies. Top Tom implements a batch processing pipeline able to run both in near‐real time with time stamped data from streaming sources and on historical data with a temporal dimension in a cold start mode. The resulting output unfolds along three main axes: time, volume and semantic similarity (i.e. topic hierarchical aggregation). To allow the browsing of data in a multiscale fashion and the identification of anomalous behaviors, three visual metaphors were adopted from biological and medical fields to design visualizations, i.e. the flowing of particles in a coherent stream, tomographic cross sectioning and contrast‐like analysis of biological tissues. The platform interface is composed by three main visualizations with coherent and smooth navigation interactions: calendar view, flow view, and temporal cut view. The integration of these three visual models with the multiscale analytic pipeline proposes a novel system for the identification and exploration of topics from unstructured texts. We evaluated the system using a collection of documents about the emerging opioid epidemics in the United States. | false | false | [
"Beatrice Gobbo",
"Duilio Balsamo",
"Michele Mauri",
"Paolo Bajardi",
"André Panisson",
"Paolo Ciuccarelli"
] | [] | [] | [] |
EuroVis | 2,019 | Toward Understanding Representation Methods in Visualization Recommendations through Scatterplot Construction Tasks | 10.1111/cgf.13682 | Most visualization recommendation systems predominantly rely on graphical previews to describe alternative visual encodings. However, since InfoVis novices are not familiar with visual representations (e.g., interpretation barriers [GTS10]), novices might have difficulty understanding and choosing recommended visual encodings. As an initial step toward understanding effective representation methods for visualization recommendations, we investigate the effectiveness of three representation methods (i.e., previews, animated transitions, and textual descriptions) under scatterplot construction tasks. Our results show how different representations individually and cooperatively help users understand and choose recommended visualizations, for example, by supporting their expect‐and‐confirm process. Based on our study results, we discuss design implications for visualization recommendation interfaces. | false | false | [
"Sehi L'Yi",
"Youli Chang 0001",
"DongHwa Shin",
"Jinwook Seo"
] | [] | [] | [] |
EuroVis | 2,019 | Towards Glyphs for Uncertain Symmetric Second-Order Tensors | 10.1111/cgf.13692 | Measured data often incorporates some amount of uncertainty, which is generally modeled as a distribution of possible samples. In this paper, we consider second‐order symmetric tensors with uncertainty. In the 3D case, this means the tensor data consists of 6 coefficients – uncertainty, however, is encoded by 21 coefficients assuming a multivariate Gaussian distribution as model. The high dimension makes the direct visualization of tensor data with uncertainty a difficult problem, which was until now unsolved. The contribution of this paper consists in the design of glyphs for uncertain second‐order symmetric tensors in 2D and 3D. The construction consists of a standard glyph for the mean tensor that is augmented by a scalar field that represents uncertainty. We show that this scalar field and therefore the displayed glyph encode the uncertainty comprehensively, i.e., there exists a bijective map between the glyph and the parameters of the distribution. Our approach can extend several classes of existing glyphs for symmetric tensors to additionally encode uncertainty and therefore provides a possible foundation for further uncertain tensor glyph design. For demonstration, we choose the well‐known superquadric glyphs, and we show that the uncertainty visualization satisfies all their design constraints. | false | false | [
"Tim Gerrits",
"Christian Rössl",
"Holger Theisel"
] | [] | [] | [] |
EuroVis | 2,019 | V-Awake: A Visual Analytics Approach for Correcting Sleep Predictions from Deep Learning Models | 10.1111/cgf.13667 | The usage of deep learning models for tagging input data has increased over the past years because of their accuracy and high‐performance. A successful application is to score sleep stages. In this scenario, models are trained to predict the sleep stages of individuals. Although their predictive accuracy is high, there are still mis classifications that prevent doctors from properly diagnosing sleep‐related disorders. This paper presents a system that allows users to explore the output of deep learning models in a real‐life scenario to spot and analyze faulty predictions. These can be corrected by users to generate a sequence of sleep stages to be examined by doctors. Our approach addresses a real‐life scenario with absence of ground truth. It differs from others in that our goal is not to improve the model itself, but to correct the predictions it provides. We demonstrate that our approach is effective in identifying faulty predictions and helping users to fix them in the proposed use case. | false | false | [
"Humberto S. Garcia Caballero",
"Michel A. Westenberg",
"Binyam Gebrekidan Gebre",
"Jarke J. van Wijk"
] | [
"BP"
] | [] | [] |
EuroVis | 2,019 | VIAN: A Visual Annotation Tool for Film Analysis | 10.1111/cgf.13676 | While color plays a fundamental role in film design and production, existing solutions for film analysis in the digital humanities address perceptual and spatial color information only tangentially. We introduce VIAN, a visual film annotation system centered on the semantic aspects of film color analysis. The tool enables expert‐assessed labeling, curation, visualization and Classification of color features based on their perceived context and aesthetic quality. It is the first of its kind that incorporates foreground‐background information made possible by modern deep learning segmentation methods. The proposed tool seamlessly integrates a multimedia data management system, so that films can undergo a full color‐oriented analysis pipeline. | false | false | [
"Gaudenz Halter",
"Rafael Ballester-Ripoll",
"Barbara Flückiger",
"Renato Pajarola"
] | [] | [] | [] |
EuroVis | 2,019 | Visual Analysis of Charge Flow Networks for Complex Morphologies | 10.1111/cgf.13704 | In the field of organic electronics, understanding complex material morphologies and their role in efficient charge transport in solar cells is extremely important. Related processes are studied using the Ising model and Kinetic Monte Carlo simulations resulting in large ensembles of stochastic trajectories. Naive visualization of these trajectories, individually or as a whole, does not lead to new knowledge discovery through exploration. In this paper, we present novel visualization and exploration methods to analyze this complex dynamic data, which provide succinct and meaningful abstractions leading to scientific insights. We propose a morphology abstraction yielding a network composed of material pockets and the interfaces, which serves as backbone for the visualization of the charge diffusion. The trajectory network is created using a novel way of implicitly attracting the trajectories to the skeleton of the morphology relying on a relaxation process. Each individual trajectory is then represented as a connected sequence of nodes in the skeleton. The final network summarizes all of these sequences in a single aggregated network. We apply our method to three different morphologies and demonstrate its suitability for exploring this kind of data. | false | false | [
"Sathish Kottravel",
"Martin Falk",
"Talha Bin Masood",
"Mathieu Linares",
"Ingrid Hotz"
] | [] | [] | [] |
EuroVis | 2,019 | Visual-Interactive Preprocessing of Multivariate Time Series Data | 10.1111/cgf.13698 | Pre‐processing is a prerequisite to conduct effective and efficient downstream data analysis. Pre‐processing pipelines often require multiple routines to address data quality challenges and to bring the data into a usable form. For both the construction and the refinement of pre‐processing pipelines, human‐in‐the‐loop approaches are highly beneficial. This particularly applies to multivariate time series, a complex data type with multiple values developing over time. Due to the high specificity of this domain, it has not been subject to in‐depth research in visual analytics. We present a visual‐interactive approach for preprocessing multivariate time series data with the following aspects. Our approach supports analysts to carry out six core analysis tasks related to pre‐processing of multivariate time series. To support these tasks, we identify requirements to baseline toolkits that may help practitioners in their choice. We characterize the space of visualization designs for uncertainty‐aware pre‐processing and justify our decisions. Two usage scenarios demonstrate applicability of our approach, design choices, and uncertainty visualizations for the six analysis tasks. This work is one step towards strengthening the visual analytics support for data pre‐processing in general and for uncertainty‐aware pre‐processing of multivariate time series in particular. | false | false | [
"Jürgen Bernard",
"Marco Hutter 0002",
"Heiko Reinemuth",
"Hendrik Pfeifer",
"Christian Bors",
"Jörn Kohlhammer"
] | [] | [] | [] |
EuroVis | 2,019 | Visualization of Equivalence in 2D Bivariate Fields | 10.1111/cgf.13691 | In this paper, we show how the equivalence property leads to the novel concept of equivalent regions in mappings from ℝn to ℝn. We present a technique for obtaining these regions both in the domain and the codomain of such a mapping, and determine their correspondence. This enables effective investigation of variation equivalence within mappings, and between mappings in terms of comparative visualization. We implement our approach for n = 2, and demonstrate its utility using different examples. | false | false | [
"Boyan Zheng",
"Bastian Rieck",
"Heike Leitte",
"Filip Sadlo"
] | [] | [] | [] |
EuroVis | 2,019 | Visualization Support for Developing a Matrix Calculus Algorithm: A Case Study | 10.1111/cgf.13694 | The development of custom interactive visualization tools for specific domains and applications has been made much simpler recently by a surge of visualization tools, libraries and frameworks. Most of these tools are developed for classical data science applications, where a user is supported in analyzing measured or simulated data. But recently, there has also been an increasing interest in visual support for understanding machine learning algorithms and frameworks, especially for deep learning. Many, if not most, of the visualization support for (deep) learning addresses the developer of the learning system and not the end user (data scientist). Here we show on a specific example, namely the development of a matrix calculus algorithm, that supporting visualizations can also greatly benefit the development of algorithms in classical domains like in our case computer algebra. The idea is similar to visually supporting the understanding of learning algorithms, namely provide the developer with an interactive, visual tool that provides insights into the workings and, importantly, also into the failures of the algorithm under development. Developing visualization support for matrix calculus development went similar as the development of more traditional visual support systems for data analysts. First, we had to acquaint ourselves with the problem, its language and challenges by talking to the core developer of the matrix calculus algorithm. Once we understood the challenge, it was fairly easy to develop visual support that streamlined the development of the matrix calculus algorithm significantly. | false | false | [
"Joachim Giesen",
"Julien Klaus",
"Sören Laue",
"Ferdinand Schreck"
] | [] | [] | [] |
EuroVis | 2,019 | Visualizing for the Non-Visual: Enabling the Visually Impaired to Use Visualization | 10.1111/cgf.13686 | The majority of visualizations on the web are still stored as raster images, making them inaccessible to visually impaired users. We propose a deep‐neural‐network‐based approach that automatically recognizes key elements in a visualization, including a visualization type, graphical elements, labels, legends, and most importantly, the original data conveyed in the visualization. We leverage such extracted information to provide visually impaired people with the reading of the extracted information. Based on interviews with visually impaired users, we built a Google Chrome extension designed to work with screen reader software to automatically decode charts on a webpage using our pipeline. We compared the performance of the back‐end algorithm with existing methods and evaluated the utility using qualitative feedback from visually impaired users. | false | false | [
"Jinho Choi",
"Sanghun Jung",
"Deok Gun Park 0001",
"Jaegul Choo",
"Niklas Elmqvist"
] | [] | [] | [] |
CHI | 2,019 | A Bayesian Cognition Approach to Improve Data Visualization | 10.1145/3290605.3300912 | People naturally bring their prior beliefs to bear on how they interpret the new information, yet few formal models exist for accounting for the influence of users' prior beliefs in interactions with data presentations like visualizations. We demonstrate a Bayesian cognitive model for understanding how people interpret visualizations in light of prior beliefs and show how this model provides a guide for improving visualization evaluation. In a first study, we show how applying a Bayesian cognition model to a simple visualization scenario indicates that people's judgments are consistent with a hypothesis that they are doing approximate Bayesian inference. In a second study, we evaluate how sensitive our observations of Bayesian behavior are to different techniques for eliciting people subjective distributions, and to different datasets. We find that people don't behave consistently with Bayesian predictions for large sample size datasets, and this difference cannot be explained by elicitation technique. In a final study, we show how normative Bayesian inference can be used as an evaluation framework for visualizations, including of uncertainty. | false | false | [
"Yea-Seul Kim",
"Logan A. Walls",
"Peter M. Krafft",
"Jessica Hullman"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1901.02949v1",
"icon": "paper"
}
] |
CHI | 2,019 | A Comparison of Notification Techniques for Out-of-View Objects in Full-Coverage Displays | 10.1145/3290605.3300288 | Full-coverage displays can place visual content anywhere on the interior surfaces of a room (e.g., a weather display near the coat stand). In these settings, digital artefacts can be located behind the user and out of their field of view - meaning that it can be difficult to notify the user when these artefacts need attention. Although much research has been carried out on notification, little is known about how best to direct people to the necessary location in room environments. We designed five diverse attention-guiding techniques for full-coverage display rooms, and evaluated them in a study where participants completed search tasks guided by the different techniques. Our study provides new results about notification in full-coverage displays: we showed benefits of persistent visualisations that could be followed all the way to the target and that indicate distance-to-target. Our findings provide useful information for improving the usability of interactive full-coverage environments. | false | false | [
"Julian Petford",
"Iain Carson",
"Miguel A. Nacenta",
"Carl Gutwin"
] | [] | [] | [] |
CHI | 2,019 | A Lie Reveals the Truth: Quasimodes for Task-Aligned Data Presentation | 10.1145/3290605.3300423 | Designers are often discouraged from creating data visualizations that omit or distort information, because they can easily be misleading. However, the same representations that could be used to deceive can provide benefits when chosen to appropriately align with user tasks. We present an interaction technique, Perceptual Glimpses, which allows for the transparent presentation of so-called 'deceptive' views of information that are made temporary using quasimodes. When presented using Perceptual Glimpses, message-level exaggeration caused by a truncated axis on a bar chart was reduced under some conditions, but users require guidance to avoid errors, and view presentation order may affect trust. When Perceptual Glimpses was extended to display a range of views that might otherwise be deceptive or difficult to understand if shown out of context, users were able to understand and leverage these transformations to perform a range of low-level tasks. Design recommendations and examples suggest extensions of the technique. | false | false | [
"Jacob Ritchie",
"Daniel Wigdor",
"Fanny Chevalier"
] | [] | [] | [] |
CHI | 2,019 | A Rough Sketch of the Freehand Drawing Process: Blending the Line between Action and Artifact | 10.1145/3290605.3300312 | Dynamic elements of the drawing process (e.g., order of compilation, speed, length, and pressure of strokes) are considered important because they can reveal the technique, process, and emotions of the artist. To explore how sensing, visualizing, and sharing these aspects of the creative process might shape art making and art viewing experiences, we designed a research probe which unobtrusively tracks and visualizes the movement and pressure of the artist's pencil on an easel. Using our probe, we conducted studies with artists and art viewers, which reveal digital and physical representations of creative process as a means of reflecting on a multitude of factors about the finished artwork, including technique, style, and the emotions of the artists. We conclude by discussing future directions for HCI systems that sense and visualize aspects of the creative process in digitally-mediated arts, as well as the social considerations of sharing and curating intimate process information. | false | false | [
"Piyum Fernando",
"Jennifer Weiler",
"Stacey Kuznetsov"
] | [] | [] | [] |
CHI | 2,019 | A Wee Bit More Interaction: Designing and Evaluating an Overactive Bladder App | 10.1145/3290605.3300933 | Overactive Bladder (OAB) is a widespread condition, affecting 20% of the population. Even though it is a treatable condition, people often do not seek treatment. In this paper, we describe how we co-designed and evaluated with 30 stakeholders (9 medical professionals and 21 end-users) an OAB mobile health application that aims to increase adherence to self-managed treatment. Our results support previous research that visualizing progress, setting goals, receiving reminders and feedback increases use. We discovered that games could be used successfully as a distraction technique for urge suppression. Contrary to the current research direction, automatically calculated features could be a detriment to app interaction. Regarding evaluation, we found that designers may not want to rely only on questionnaires when assessing the success of a game and its emotional impact on users. | false | false | [
"Ana-Maria Salai",
"Lynne Baillie"
] | [] | [] | [] |
CHI | 2,019 | Aggregated Visualization of Playtesting Data | 10.1145/3290605.3300593 | Playtesting is a key component in the game development process aimed at improving the quality of games through the collection of gameplay data and identification of design issues. Visualization techniques are currently being employed to help integrate quantitative and qualitative data. Despite that, two existing challenges are to determine the level of detail to be presented to developers based on their needs and to effectively communicate the collected data so that informed design changes can be reached. In this paper, we first propose an aggregated visualization technique that makes use of clustering, territory tessellation, and trajectory aggregation to simultaneously display mixed playtesting data. Secondly, to assess the usefulness of our technique we evaluate it through interviews with professional game developers and compare it to a non-aggregated visualization. The results of this study also provide an important contribution towards identifying areas of improvement in the portrayal of gameplay data. | false | false | [
"Günter Wallner",
"Nour Halabi",
"Pejman Mirza-Babaei"
] | [] | [] | [] |
CHI | 2,019 | Analyzing Value Discovery in Design Decisions Through Ethicography | 10.1145/3290605.3300307 | HCI scholarship is increasingly concerned with the ethical impact of socio-technical systems. Current theoretically driven approaches that engage with ethics generally prescribe only abstract approaches by which designers might consider values in the design process. However, there is little guidance on methods that promote value discovery, which might lead to more specific examples of relevant values in specific design contexts. In this paper, we elaborate a method for value discovery, identifying how values impact the designer's decision making. We demonstrate the use of this method, called Ethicography, in describing value discovery and use throughout the design process. We present analysis of design activity by user experience (UX) design students in two lab protocol conditions, describing specific human values that designers considered for each task, and visualizing the interplay of these values. We identify opportunities for further research, using the Ethicograph method to illustrate value discovery and translation into design solutions. | false | false | [
"Shruthi Sai Chivukula",
"Colin M. Gray",
"Jason A. Brier"
] | [
"HM"
] | [] | [] |
CHI | 2,019 | ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning | 10.1145/3290605.3300911 | To relieve the pain of manually selecting machine learning algorithms and tuning hyperparameters, automated machine learning (AutoML) methods have been developed to automatically search for good models. Due to the huge model search space, it is impossible to try all models. Users tend to distrust automatic results and increase the search budget as much as they can, thereby undermining the efficiency of AutoML. To address these issues, we design and implement ATMSeer, an interactive visualization tool that supports users in refining the search space of AutoML and in analyzing the results. To guide the design of ATMSeer, we derive a workflow of using AutoML based on interviews with machine learning experts. A multi-granularity visualization is proposed to enable users to monitor the AutoML process, analyze the searched models, and refine the search space in real time. We demonstrate the utility and usability of ATMSeer through two case studies, expert interviews, and a user study with 13 end users. | false | false | [
"Qianwen Wang",
"Yao Ming",
"Zhihua Jin",
"Qiaomu Shen",
"Dongyu Liu",
"Micah J. Smith",
"Kalyan Veeramachaneni",
"Huamin Qu"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1902.05009v1",
"icon": "paper"
}
] |
CHI | 2,019 | Bookly: An Interactive Everyday Artifact Showing the Time of Physically Accumulated Reading Activity | 10.1145/3290605.3300614 | We introduce Bookly, an interactive artifact that physically represents the accumulated time of users' reading activity through abstract volumetric changes. Bookly accumulates the time of actions (e.g., picking up and putting down books) that users performed for reading and provides a designated space for the ongoing book being read. The results of our 2-week in-field study with six participants showed that continuous exposure to volumetric changes representing the accumulated time of reading activities helped the users to understand their unsettled reading patterns. Bookly also motivated the users to improve their reading behavior by gradually making reading part of their schedules. Additionally, the definite distinction of the ongoing book improved its visual affordance and accessibility for the users to start reading books. Based on the findings, we confirmed the possibility of making intangible data physical for self-reflection to enhance changes in behaviors that are difficult to perform due to weak motivation. | false | false | [
"Somi Ju",
"Kyung-Ryong Lee",
"Subin Kim",
"Young-Woo Park"
] | [] | [] | [] |
CHI | 2,019 | Card Mapper: Enabling Data-Driven Reflections on Ideation Cards | 10.1145/3290605.3300801 | We explore how usage data captured from ideation cards can enable reflection on design. We deployed a deck of ideation cards on a Masters level module over two years, developing the means to capture the students' designs into a digital repository. We created two visualisations to reveal the relative co-occurrences of the cards as concept space and the relative proximity of designs (through cards used in common) as design space. We used these to elicit reflections from the perspectives of students, teachers and card designers. Our findings inspire ideas for extending the data-driven use of ideation cards throughout the design process; informing the redesign of cards, the rules for using them and their live connection to supporting materials and enabling stakeholders to reflect and recognise challenges and opportunities. We also identified the need, and potential ways, to capture a richer design rationale, including annotations, discarded cards and varying card interpretations. | false | false | [
"Dimitrios Paris Darzentas",
"Raphael Velt",
"Richard Wetzel",
"Peter J. Craigon",
"Hanne Gesine Wagner",
"Lachlan D. Urquhart",
"Steve Benford"
] | [] | [] | [] |
CHI | 2,019 | Color Builder: A Direct Manipulation Interface for Versatile Color Theme Authoring | 10.1145/3290605.3300686 | Color themes or palettes are popular for sharing color combinations across many visual domains. We present a novel interface for creating color themes through direct manipulation of color swatches. Users can create and rearrange swatches, and combine them into smooth and step-based gradients and three-color blends -- all using a seamless touch or mouse input. Analysis of existing solutions reveals a fragmented color design workflow, where separate software is used for swatches, smooth and discrete gradients and for in-context color visualization. Our design unifies these tasks, while encouraging playful creative exploration. Adjusting a color using standard color pickers can break this interaction flow with mechanical slider manipulation. To keep interaction seamless, we additionally design an in situ color tweaking interface for freeform exploration of an entire color neighborhood. We evaluate our interface with a group of professional designers and students majoring in this field. | false | false | [
"Maria Shugrina",
"Wenjia Zhang",
"Fanny Chevalier",
"Sanja Fidler",
"Karan Singh"
] | [] | [] | [] |
CHI | 2,019 | Communicating Uncertainty in Fertility Prognosis | 10.1145/3290605.3300391 | Communicating uncertainty has been shown to provide positive effects on user understanding and decision-making. Surprisingly however, most personal health tracking applications fail to disclose the accuracy of their measurements and predictions. In the case of fertility tracking applications (FTAs), inaccurate predictions have already led to numerous unwanted pregnancies and law suits. However, integrating uncertainty into FTAs is challenging: Prediction accuracy is hard to understand and communicate, and its effect on users' trust and behavior is not well understood. We created a prototype for uncertainty visualizations for FTAs and evaluated it in a four-week field study with real users and their own data (N=9). Our results uncover far-reaching effects of communicating uncertainty: For example, users interpreted prediction accuracy as a proxy for their cycle health and as a security indicator for contraception. Displaying predicted and detected fertile phases next to each other helped users to understand uncertainty without negative emotional effects. | false | false | [
"Hanna Schneider",
"Julia Wayrauther",
"Mariam Hassib",
"Andreas Butz"
] | [] | [] | [] |
CHI | 2,019 | Concept-Driven Visual Analytics: an Exploratory Study of Model- and Hypothesis-Based Reasoning with Visualizations | 10.1145/3290605.3300298 | Visualization tools facilitate exploratory data analysis, but fall short at supporting hypothesis-based reasoning. We conducted an exploratory study to investigate how visualizations might support a concept-driven analysis style, where users can optionally share their hypotheses and conceptual models in natural language, and receive customized plots depicting the fit of their models to the data. We report on how participants leveraged these unique affordances for visual analysis. We found that a majority of participants articulated meaningful models and predictions, utilizing them as entry points to sensemaking. We contribute an abstract typology representing the types of models participants held and externalized as data expectations. Our findings suggest ways for rearchitecting visual analytics tools to better support hypothesis- and model-based reasoning, in addition to their traditional role in exploratory analysis. We discuss the design implications and reflect on the potential benefits and challenges involved. | false | false | [
"In Kwon Choi",
"Taylor Childers",
"Nirmal Kumar Raveendranath",
"Swati Mishra 0006",
"Kyle Harris",
"Khairi Reda"
] | [] | [] | [] |
CHI | 2,019 | Connect-to-Connected Worlds: Piloting a Mobile, Data-Driven Reflection Tool for an Open-Ended Simulation at a Museum | 10.1145/3290605.3300237 | Immersive open-ended museum exhibits promote ludic engagement and can be a powerful draw for visitors, but these qualities may also make learning more challenging. We describe our efforts to help visitors engage more deeply with an interactive exhibit's content by giving them access to visualizations of data skimmed from their use of the exhibit. We report on the motivations and challenges in designing this reflective tool, which positions visitors as a "human in the loop" to understand and manage their engagement with the exhibit. We used an iterative design process and qualitative methods to explore how and if visitors could (1) access and (2) comprehend the data visualizations, (3) reflect on their prior engagement with the exhibit, (4)plan their future engagement with the exhibit, and (5) act on their plans. We further discuss the essential design challenges and the opportunities made possible for visitors through data-driven reflection tools. | false | false | [
"Aditi Mallavarapu",
"Leilah Lyons",
"Stephen M. Uzzo",
"Wren Thompson",
"Rinat Levy-Cohen",
"Brian Slattery"
] | [] | [] | [] |
CHI | 2,019 | Data is Personal: Attitudes and Perceptions of Data Visualization in Rural Pennsylvania | 10.1145/3290605.3300474 | Many of the guidelines that inform how designers create data visualizations originate in studies that unintentionally exclude populations that are most likely to be among the 'data poor'. In this paper, we explore which factors may drive attention and trust in rural populations with diverse economic and educational backgrounds - a segment that is largely underrepresented in the data visualization literature. In 42 semi-structured interviews in rural Pennsylvania (USA), we find that a complex set of factors intermix to inform attitudes and perceptions about data visualization - including educational background, political affiliation, and personal experience. The data and materials for this research can be found at https://osf.io/uxwts/ | false | false | [
"Evan M. Peck",
"Sofia E. Ayuso",
"Omar El-Etr"
] | [
"BP"
] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1901.01920v1",
"icon": "paper"
}
] |
CHI | 2,019 | DataSelfie: Empowering People to Design Personalized Visuals to Represent Their Data | 10.1145/3290605.3300309 | Many personal informatics systems allow people to collect and manage personal data and reflect more deeply about themselves. However, these tools rarely offer ways to customize how the data is visualized. In this work, we investigate the question of how to enable people to determine the representation of their data. We analyzed the Dear Data project to gain insights into the design elements of personal visualizations. We developed DataSelfie, a novel system that allows individuals to gather personal data and design custom visuals to represent the collected data. We conducted a user study to evaluate the usability of the system as well as its potential for individual and collaborative sensemaking of the data. | false | false | [
"Nam Wook Kim",
"Hyejin Im",
"Nathalie Henry Riche",
"Alicia Wang",
"Krzysztof Gajos",
"Hanspeter Pfister"
] | [] | [] | [] |
CHI | 2,019 | DataToon: Drawing Dynamic Network Comics With Pen + Touch Interaction | 10.1145/3290605.3300335 | Comics are an entertaining and familiar medium for presenting compelling stories about data. However, existing visualization authoring tools do not leverage this expressive medium. In this paper, we seek to incorporate elements of comics into the construction of data-driven stories about dynamic networks. We contribute DataToon, a flexible data comic storyboarding tool that blends analysis and presentation with pen and touch interactions. A storyteller can use DataToon rapidly generate visualization panels, annotate them, and position them within a canvas to produce a visually compelling narrative. In a user study, participants quickly learned to use DataToon for producing data comics. | false | false | [
"Nam Wook Kim",
"Nathalie Henry Riche",
"Benjamin Bach",
"Guanpeng Xu",
"Matthew Brehmer",
"Ken Hinckley",
"Michel Pahud",
"Haijun Xia",
"Michael J. McGuffin",
"Hanspeter Pfister"
] | [] | [] | [] |
CHI | 2,019 | Effect of Orientation on Unistroke Touch Gestures | 10.1145/3290605.3300928 | As touchscreens are the most successful input method of current mobile devices, touch gestures became a widely used input technique. While gestures provide users with advantages to express themselves, they also introduce challenges regarding accuracy and memorability. In this paper, we investigate the effect of a gesture's orientation on how well the gesture can be performed. We conducted a study in which participants performed systematically rotated unistroke gestures. For straight lines as well as for compound lines, we found that users tend to align gestures with the primary axes. We show that the error can be described by a Clausen function with R² = .93. Based on our findings, we suggest design implications and highlight the potential for recognizing flick gestures, visualizing gestures and improving recognition of compound gestures. | false | false | [
"Sven Mayer",
"Valentin Schwind",
"Huy Viet Le",
"Dominik Weber",
"Jonas Vogelsang",
"Johannes Wolf",
"Niels Henze"
] | [] | [] | [] |
CHI | 2,019 | Embodied Imagination: An Approach to Stroke Recovery Combining Participatory Performance and Interactive Technology | 10.1145/3290605.3300735 | Participatory performance provides methods for exploring social identities and situations in ways that can help people to imagine new ways of being. Digital technologies provide tools that can help people envision these possibilities. We explore this combination through a performance workshop process designed to help stroke survivors imagine new physical and social possibilities by enacting fantasies of "things they always wanted to do". This process uses performance methods combined with specially designed real-time movement visualisations to progressively build fantasy narratives that are enacted with and for other workshop participants. Qualitative evaluations suggest this process successfully stimulates participant's embodied imagination and generates a diverse range of fantasies. The interactive and communal aspects of the workshop process appear to be especially important in achieving these effects. This work highlights how the combination of performance methods and interactive tools can bring a rich, prospective and political understanding of people's lived experience to design. | false | false | [
"Rosella P. Galindo Esparza",
"Patrick G. T. Healey",
"Lois Weaver",
"Matthew Delbridge"
] | [] | [] | [] |
CHI | 2,019 | Ethical Dimensions of Visualization Research | 10.1145/3290605.3300418 | Visualizations have a potentially enormous influence on how data are used to make decisions across all areas of human endeavor. However, it is not clear how this power connects to ethical duties: what obligations do we have when it comes to visualizations and visual analytics systems, beyond our duties as scientists and engineers? Drawing on historical and contemporary examples, I address the moral components of the design and use of visualizations, identify some ongoing areas of visualization research with ethical dilemmas, and propose a set of additional moral obligations that we have as designers, builders, and researchers of visualizations. | false | false | [
"Michael Correll"
] | [
"HM"
] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1811.07271v2",
"icon": "paper"
}
] |
CHI | 2,019 | Evaluating the Impact of Pseudo-Colour and Coordinate System on the Detection of Medication-induced ECG Changes | 10.1145/3290605.3300353 | The electrocardiogram (ECG), a graphical representation of the heart's electrical activity, is used for detecting cardiac pathologies. Certain medications can produce a complication known as 'long QT syndrome', shown on the ECG as an increased gap between two parts of the waveform. Self-monitoring for this could be lifesaving, as the syndrome can result in sudden death, but detecting it on the ECG is difficult. Here we evaluate whether using pseudo-colour to highlight wave length and changing the coordinate system can support lay people in identifying increases in the QT interval. The results show that introducing colour significantly improves accuracy, and that whilst it is easier to detect a difference without colour with Cartesian coordinates, the greatest accuracy is achieved when Polar coordinates are combined with colour. The results show that applying simple visualisation techniques has the potential to improve ECG interpretation accuracy, and support people in monitoring their own ECG. | false | false | [
"Alaa Alahmadi",
"Alan Davies",
"Jennifer Royle",
"Markel Vigo",
"Caroline Jay"
] | [] | [] | [] |
CHI | 2,019 | Examining and Enhancing the Illusory Touch Perception in Virtual Reality Using Non-Invasive Brain Stimulation | 10.1145/3290605.3300477 | Virtual reality (VR) can be immersive to such a degree that users sometimes report feeling tactile sensations based on visualization of the touch, without any actual physical contact. This effect is not only interesting for studies of human perception, but can also be leveraged to improve the quality of VR by evoking tactile sensations without usage of specialized equipment. The aim of this paper is to study brain processing of the illusory touch and its enhancement for purposes of exploitation in VR scene design. To amplify the illusory touch, transcranial direct current stimulation (tDCS) was used. Participants attended two sessions with blinded stimulation and interacted with a virtual ball using tracked hands in VR. The effects were studied using electroencephalography (EEG), that allowed us to examine stimulation-induced changes in processing of the illusory touch in the brain, as well as to identify its neural correlates. Results confirm enhanced processing of the illusory touch after the stimulation, and some of these changes were correlated to subjective rating of its magnitude. | false | false | [
"Filip Skola",
"Fotis Liarokapis"
] | [] | [] | [] |
CHI | 2,019 | Exploring Sound Awareness in the Home for People who are Deaf or Hard of Hearing | 10.1145/3290605.3300324 | The home is filled with a rich diversity of sounds from mundane beeps and whirs to dog barks and children's shouts. In this paper, we examine how deaf and hard of hearing (DHH) people think about and relate to sounds in the home, solicit feedback and reactions to initial domestic sound awareness systems, and explore potential concerns. We present findings from two qualitative studies: in Study 1, 12 DHH participants discussed their perceptions of and experiences with sound in the home and provided feedback on initial sound awareness mockups. Informed by Study 1, we designed three tablet-based sound awareness prototypes, which we evaluated with 10 DHH participants using a Wizard-of-Oz approach. Together, our findings suggest a general interest in smarthome-based sound awareness systems particularly for displaying contextually aware, personalized and glanceable visualizations but key concerns arose related to privacy, activity tracking, cognitive overload, and trust. | false | false | [
"Dhruv Jain",
"Angela Lin",
"Rose Guttman",
"Marcus Amalachandran",
"Aileen Zeng",
"Leah Findlater",
"Jon Froehlich"
] | [] | [] | [] |
CHI | 2,019 | Eye-Write: Gaze Sharing for Collaborative Writing | 10.1145/3290605.3300727 | Online collaborative writing is an increasingly common practice. Despite its positive effect on productivity and quality of work, it poses challenges to co-authors in remote settings because of limitations in conversational grounding and activity awareness. This paper presents Eye-Write, a novel system which allows two co-authors to see at will the location of their partner's gaze within a text editor. To investigate the effect of shared gaze on collaboration, we conducted a study on synchronous remote collaborative writing in academic settings with 20 dyads. Gaze sharing improved five aspects of perceived collaboration quality: mutual understanding, level of joint attention, flow of communication, level of negotiation, and awareness of the co-author's activity. Furthermore, dyads whose participants deactivated the gaze visualization showed a smaller degree of collaboration. Our findings offer insights for future text editors by outlining the benefits of at-will gaze sharing in collaborative writing. | false | false | [
"Grete Helena Kütt",
"Kevin Lee",
"Ethan Hardacre",
"Alexandra Papoutsaki"
] | [] | [] | [] |
CHI | 2,019 | Falcon: Balancing Interactive Latency and Resolution Sensitivity for Scalable Linked Visualizations | 10.1145/3290605.3300924 | We contribute user-centered prefetching and indexing methods that provide low-latency interactions across linked visualizations, enabling cold-start exploration of billion-record datasets. We implement our methods in Falcon, a web-based system that makes principled trade-offs between latency and resolution to optimize brushing and view switching times. To optimize latency-sensitive brushing actions, Falcon reindexes data upon changes to the active view a user is brushing in. To limit view switching times, Falcon initially loads reduced interactive resolutions, then progressively improves them. Benchmarks show that Falcon sustains real-time interactivity of 50fps for pixel-level brushing and linking across multiple visualizations with no costly precomputation. We show constant brushing performance regardless of data size on datasets ranging from millions of records in the browser to billions when connected to a backing database system. | false | false | [
"Dominik Moritz",
"Bill Howe",
"Jeffrey Heer"
] | [] | [] | [] |
CHI | 2,019 | Frequency-Based Design of Smart Textiles | 10.1145/3290605.3300524 | Despite the increasing amount of smart textile design practitioners, the methods and tools commonly available have not progressed to the same scale. Most smart textile interaction designs today rely on detecting changes in resistance. The tools and sensors for this are generally limited to DC-voltage-divider based sensors and multimeters. Furthermore, the textiles and the materials used in smart textile design can exhibit behaviour making it difficult to identify even simple interactions using those means. For instance, steel-based textiles exhibit intrinsic semiconductive properties that are difficult to identify with current methods. In this paper, we show an alternative way to measure interaction with smart textiles. By relying on visualisation known as Lissajous-figures and frequency-based signals, we can detect even subtle and varied forms of interaction with smart textiles. We also show an approach to measuring frequency-based signals and present an Arduino-based system called Teksig to support this type of textile practice. | false | false | [
"Jussi Mikkonen",
"Riikka Townsend"
] | [] | [] | [] |
CHI | 2,019 | Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models | 10.1145/3290605.3300809 | Without good models and the right tools to interpret them, data scientists risk making decisions based on hidden biases, spurious correlations, and false generalizations. This has led to a rallying cry for model interpretability. Yet the concept of interpretability remains nebulous, such that researchers and tool designers lack actionable guidelines for how to incorporate interpretability into models and accompanying tools. Through an iterative design process with expert machine learning researchers and practitioners, we designed a visual analytics system, Gamut, to explore how interactive interfaces could better support model interpretation. Using Gamut as a probe, we investigated why and how professional data scientists interpret models, and how interface affordances can support data scientists in answering questions about model interpretability. Our investigation showed that interpretability is not a monolithic concept: data scientists have different reasons to interpret models and tailor explanations for specific audiences, often balancing competing concerns of simplicity and completeness. Participants also asked to use Gamut in their work, highlighting its potential to help data scientists understand their own data. | false | false | [
"Fred Hohman",
"Andrew Head",
"Rich Caruana",
"Robert DeLine",
"Steven Mark Drucker"
] | [] | [] | [] |
CHI | 2,019 | GymSoles: Improving Squats and Dead-Lifts by Visualizing the User's Center of Pressure | 10.1145/3290605.3300404 | The correct execution of exercises, such as squats and dead-lifts, is essential to prevent various bodily injuries. Existing solutions either rely on expensive motion tracking or multiple Inertial Measurement Units (IMU) systems require an extensive set-up and individual calibration. This paper introduces a proof of concept, GymSoles, an insole prototype that provides feedback on the Centre of Pressure (CoP) at the feet to assist users with maintaining the correct body posture, while performing squats and dead-lifts. GymSoles was evaluated with 13 users in three conditions: 1) no feedback, 2) vibrotactile feedback, and 3) visual feedback. It has shown that solely providing feedback on the current CoP, results in a significantly improved body posture. | false | false | [
"Don Samitha Elvitigala",
"Denys J. C. Matthies",
"Löic David",
"Chamod Weerasinghe",
"Suranga Nanayakkara"
] | [] | [] | [] |
CHI | 2,019 | Haptipedia: Accelerating Haptic Device Discovery to Support Interaction & Engineering Design | 10.1145/3290605.3300788 | Creating haptic experiences often entails inventing, modifying, or selecting specialized hardware. However, interaction designers are rarely engineers, and 30 years of haptic inventions are buried in a fragmented literature that describes devices mechanically rather than by potential purpose. We conceived of Haptipedia to unlock this trove of examples: Haptipedia presents a device corpus for exploration through metadata that matter to both device and interaction designers. It is a taxonomy of device attributes that go beyond physical description to capture potential utility, applied to a growing database of 105 grounded force-feedback devices, and accessed through a public visualization that links utility to morphology. Haptipedia's design was driven by both systematic review of the haptic device literature and rich input from diverse haptic designers. We describe Haptipedia's reception (including hopes it will redefine device reporting standards) and our plans for its sustainability through community participation. | false | false | [
"Hasti Seifi",
"Farimah Fazlollahi",
"Michael Oppermann",
"John Andrew Sastrillo",
"Jessica Ip",
"Ashutosh Agrawal",
"Gunhyuk Park",
"Katherine J. Kuchenbecker",
"Karon E. MacLean"
] | [] | [] | [] |
CHI | 2,019 | In a Silent Way: Communication Between AI and Improvising Musicians Beyond Sound | 10.1145/3290605.3300268 | Collaboration is built on trust, and establishing trust with a creative Artificial Intelligence is difficult when the decision process or internal state driving its behaviour isn't exposed. When human musicians improvise together, a number of extra-musical cues are used to augment musical communication and expose mental or emotional states which affect musical decisions and the effectiveness of the collaboration. We developed a collaborative improvising AI drummer that communicates its confidence through an emoticon-based visualisation. The AI was trained on musical performance data, as well as real-time skin conductance, of musicians improvising with professional drummers, exposing both musical and extra-musical cues to inform its generative process. Uni- and bi-directional extra-musical communication with real and false values were tested by experienced improvising musicians. Each condition was evaluated using the FSS-2 questionnaire, as a proxy for musical engagement. The results show a positive correlation between extra-musical communication of machine internal state and human musical engagement. | false | false | [
"Jon McCormack",
"Toby Gifford",
"Patrick Hutchings",
"Maria Teresa Llano Rodriguez",
"Matthew Yee-King",
"Mark d'Inverno"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1902.06442v1",
"icon": "paper"
}
] |
CHI | 2,019 | Making Sense of Human-Food Interaction | 10.1145/3290605.3300908 | Activity in Human-Food Interaction (HFI) research is skyrocketing across a broad range of disciplinary interests and concerns. The dynamic and heterogeneous nature of this emerging field presents a challenge to scholars wishing to critically engage with prior work, identify gaps and ensure impact. It also challenges the formation of community. We present a Systematic Mapping Study of HFI research and an online data visualisation tool developed to respond to these issues. The tool allows researchers to engage in new ways with the HFI literature, propose modifications and additions to the review, and thereby actively engage in community-making. Our contribution is threefold: (1) we characterize the state of HFI, reporting trends, challenges and opportunities; (2) we provide a taxonomy and tool for diffractive reading of the literature; and (3) we offer our approach for adaptation by research fields facing similar challenges, positing value of the tool and approach beyond HFI. | false | false | [
"Ferran Altarriba Bertran",
"Samvid Niravbhai Jhaveri",
"Rosa Lutz",
"Katherine Isbister",
"Danielle Wilde"
] | [] | [] | [] |
CHI | 2,019 | Managing Messes in Computational Notebooks | 10.1145/3290605.3300500 | Data analysts use computational notebooks to write code for analyzing and visualizing data. Notebooks help analysts iteratively write analysis code by letting them interleave code with output, and selectively execute cells. However, as analysis progresses, analysts leave behind old code and outputs, and overwrite important code, producing cluttered and inconsistent notebooks. This paper introduces code gathering tools, extensions to computational notebooks that help analysts find, clean, recover, and compare versions of code in cluttered, inconsistent notebooks. The tools archive all versions of code outputs, allowing analysts to review these versions and recover the subsets of code that produced them. These subsets can serve as succinct summaries of analysis activity or starting points for new analyses. In a qualitative usability study, 12 professional analysts found the tools useful for cleaning notebooks and writing analysis code, and discovered new ways to use them, like generating personal documentation and lightweight versioning. | false | false | [
"Andrew Head",
"Fred Hohman",
"Titus Barik",
"Steven Mark Drucker",
"Robert DeLine"
] | [
"BP"
] | [] | [] |
CHI | 2,019 | Measuring the Separability of Shape, Size, and Color in Scatterplots | 10.1145/3290605.3300899 | Scatterplots commonly use multiple visual channels to encode multivariate datasets. Such visualizations often use size, shape, and color as these dimensions are considered separable--dimensions represented by one channel do not significantly interfere with viewers' abilities to perceive data in another. However, recent work shows the size of marks significantly impacts color difference perceptions, leading to broader questions about the separability of these channels. In this paper, we present a series of crowdsourced experiments measuring how mark shape, size, and color influence data interpretation in multiclass scatterplots. Our results indicate that mark shape significantly influences color and size perception, and that separability among these channels functions asymmetrically: shape more strongly influences size and color perceptions in scatterplots than size and color influence shape. Models constructed from the resulting data can help designers anticipate viewer perceptions to build more effective visualizations. | false | false | [
"Stephen Smart",
"Danielle Albers Szafir"
] | [] | [] | [] |
CHI | 2,019 | MindDot: Supporting Effective Cognitive Behaviors in Concept Map-Based Learning Environments | 10.1145/3290605.3300258 | While prior research has revealed the promising impact of concept mapping on learning, few have comprehensively modeled different cognitive behaviors during concept mapping. In addition, existing concept mapping tools lack effective feedback to support better learning behaviors. This work presents MindDot, a concept map-based learning environment that facilitates the cognitive process of comparing and integrating related concepts via two forms of support. A hyperlink support and an expert template. Study results suggested that both types of support had positive impact on the development of comparative strategies and that hyperlink support enhanced learning. We further evaluated the cognitive learning progress at a fine-grained level with two forms of visualizations. We then extracted several behavioral patterns that provided insights about the cognitive progress in learning. Lastly, we derive design recommendations that we hope will inspire future intelligent tutoring systems that automatically evaluate students' learning behaviors and foster them in developing effective learning behaviors | false | false | [
"Shang Wang 0001",
"Deniz Sonmez Unal",
"Erin Walker"
] | [] | [] | [] |
CHI | 2,019 | On the Shoulder of the Giant: A Multi-Scale Mixed Reality Collaboration with 360 Video Sharing and Tangible Interaction | 10.1145/3290605.3300458 | We propose a multi-scale Mixed Reality (MR) collaboration between the Giant, a local Augmented Reality user, and the Miniature, a remote Virtual Reality user, in Giant-Miniature Collaboration (GMC). The Miniature is immersed in a 360-video shared by the Giant who can physically manipulate the Miniature through a tangible interface, a combined 360-camera with a 6 DOF tracker. We implemented a prototype system as a proof of concept and conducted a user study (n=24) comprising of four parts comparing: A) two types of virtual representations, B) three levels of Miniature control, C) three levels of 360-video view dependencies, and D) four 360-camera placement positions on the Giant. The results show users prefer a shoulder mounted camera view, while a view frustum with a complimentary avatar is a good visualization for the Miniature virtual representation. From the results, we give design recommendations and demonstrate an example Giant-Miniature Interaction. | false | false | [
"Thammathip Piumsomboon",
"Gun A. Lee",
"Andrew Irlitti",
"Barrett Ens",
"Bruce H. Thomas",
"Mark Billinghurst"
] | [] | [] | [] |
CHI | 2,019 | PeerLens: Peer-inspired Interactive Learning Path Planning in Online Question Pool | 10.1145/3290605.3300864 | Online question pools like LeetCode provide hands-on exercises of skills and knowledge. However, due to the large volume of questions and the intent of hiding the tested knowledge behind them, many users find it hard to decide where to start or how to proceed based on their goals and performance. To overcome these limitations, we present PeerLens, an interactive visual analysis system that enables peer-inspired learning path planning. PeerLens can recommend a customized, adaptable sequence of practice questions to individual learners, based on the exercise history of other users in a similar learning scenario. We propose a new way to model the learning path by submission types and a novel visual design to facilitate the understanding and planning of the learning path. We conducted a within-subject experiment to assess the efficacy and usefulness of PeerLens in comparison with two baseline systems. Experiment results show that users are more confident in arranging their learning path via PeerLens and find it more informative and intuitive. | false | false | [
"Meng Xia",
"Mingfei Sun",
"Huan Wei",
"Qing Chen 0001",
"Yong Wang 0021",
"Lei Shi 0002",
"Huamin Qu",
"Xiaojuan Ma"
] | [] | [] | [] |
CHI | 2,019 | PicMe: Interactive Visual Guidance for Taking Requested Photo Composition | 10.1145/3290605.3300625 | PicMe is a mobile application that provides interactive on-screen guidance that helps the user take pictures of a composition that another person requires. Once the requester captures a picture of the desired composition and delivers it to the user (photographer), a 2.5D guidance system, called the virtual frame, guides the user in real-time by showing a three-dimensional composition of the target image (i.e., size and shape). In addition, according to the matching accuracy rate, we provide a small-sized target image in an inset window as feedback and edge visualization for further alignment of the detail elements. We implemented PicMe to work fully in mobile environments. We then conducted a preliminary user study to evaluate the effectiveness of PicMe compared to traditional 2D guidance methods. The results show that PicMe helps users reach their target images more accurately and quickly by giving participants more confidence in their tasks. | false | false | [
"Minju Kim",
"Jungjin Lee"
] | [
"BP"
] | [] | [] |
CHI | 2,019 | Ranked-List Visualization: A Graphical Perception Study | 10.1145/3290605.3300422 | Visualization of ranked lists is a common occurrence, but many in-the-wild solutions fly in the face of vision science and visualization wisdom. For example, treemaps and bubble charts are commonly used for this purpose, despite the fact that the data is not hierarchical and that length is easier to perceive than area. Furthermore, several new visual representations have recently been suggested in this area, including wrapped bars, packed bars, piled bars, and Zvinca plots. To quantify the differences and trade-offs for these ranked-list visualizations, we here report on a crowdsourced graphical perception study involving six such visual representations, including the ubiquitous scrolled barchart, in three tasks: ranking (assessing a single item), comparison (two items), and average (assessing global distribution). Results show that wrapped bars may be the best choice for visualizing ranked lists, and that treemaps are surprisingly accurate despite the use of area rather than length to represent value. | false | false | [
"Pranathi Mylavarapu",
"Adil Yalçin",
"Xan Gregg",
"Niklas Elmqvist"
] | [] | [] | [] |
CHI | 2,019 | Saliency Deficit and Motion Outlier Detection in Animated Scatterplots | 10.1145/3290605.3300771 | We report the results of a crowdsourced experiment that measured the accuracy of motion outlier detection in multivariate, animated scatterplots. The targets were outliers either in speed or direction of motion, and were presented with varying levels of saliency in dimensions that are irrelevant to the task of motion outlier detection (e.g., color, size, position). We found that participants had trouble finding the outlier when it lacked irrelevant salient features and that visual channels contribute unevenly to the odds of an outlier being correctly detected. Direction of motion contributes the most to accurate detection of speed outliers, and position contributes the most to accurate detection of direction outliers. We introduce the concept of saliency deficit in which item importance in the data space is not reflected in the visualization due to a lack of saliency. We conclude that motion outlier detection is not well supported in multivariate animated scatterplots. | false | false | [
"Rafael Veras",
"Christopher Collins 0001"
] | [
"HM"
] | [] | [] |
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