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 | 2,021 | AutoClips: An Automatic Approach to Video Generation from Data Facts | 10.1111/cgf.14324 | Data videos, a storytelling genre that visualizes data facts with motion graphics, are gaining increasing popularity among data journalists, non‐profits, and marketers to communicate data to broad audiences. However, crafting a data video is often time‐consuming and asks for various domain knowledge such as data visualization, animation design, and screenwriting. Existing authoring tools usually enable users to edit and compose a set of templates manually, which still cost a lot of human effort. To further lower the barrier of creating data videos, this work introduces a new approach, AutoClips, which can automatically generate data videos given the input of a sequence of data facts. We built AutoClips through two stages. First, we constructed a fact‐driven clip library where we mapped ten data facts to potential animated visualizations respectively by analyzing 230 online data videos and conducting interviews. Next, we constructed an algorithm that generates data videos from data facts through three steps: selecting and identifying the optimal clip for each of the data facts, arranging the clips into a coherent video, and optimizing the duration of the video. The results from two user studies indicated that the data videos generated by AutoClips are comprehensible, engaging, and have comparable quality with human‐made videos. | false | false | [
"D. Shi",
"F. Sun",
"X. Xu",
"Xingyu Lan",
"David Gotz",
"Nan Cao"
] | [] | [] | [] |
EuroVis | 2,021 | Automatic Improvement of Continuous Colormaps in Euclidean Colorspaces | 10.1111/cgf.14313 | Colormapping is one of the simplest and most widely used data visualization methods within and outside the visualization community. Uniformity, order, discriminative power, and smoothness of continuous colormaps are the most important criteria for evaluating and potentially improving colormaps. We present a local and a global automatic optimization algorithm in Euclidean color spaces for each of these design rules in this work. As a foundation for our optimization algorithms, we used the CCC‐Tool colormap specification (CMS); each algorithm has been implemented in this tool. In addition to synthetic examples that demonstrate each method's effect, we show the outcome of some of the methods applied to a typhoon simulation. | false | false | [
"Pascal Nardini",
"Min Chen 0001",
"Michael Böttinger",
"Gerik Scheuermann",
"Roxana Bujack"
] | [] | [] | [] |
EuroVis | 2,021 | Boundary Objects in Design Studies: Reflections on the Collaborative Creation of Isochrone Maps | 10.1111/cgf.14312 | We propose to take an artifact‐centric approach to design studies by leveraging the concept of boundary object. Design studies typically focus on processes and articulate design decisions in a project‐specific context with a goal of transferability. We argue that design studies could benefit from paying attention to the material conditions in which teams collaborate to reach design outcomes. We report on a design study of isochrone maps following cartographic generalization principles. Focusing on boundary objects enables us to characterize five categories of artifacts and tools that facilitated collaboration between actors involved in the design process (structured collections, structuring artifacts, process‐centric artifacts, generative artifacts, and bridging artifacts). We found that artifacts such as layered maps and map collections played a unifying role for our inter‐disciplinary team. We discuss how such artifacts can be pivotal in the design process. Finally, we discuss how considering boundary objects could improve the transferability of design study results, and support reflection on inter‐disciplinary collaboration in the domain of Information Visualization. | false | false | [
"Romain Vuillemot",
"Ph. Rivière",
"Anaëlle Beignon",
"Aurélien Tabard"
] | [] | [] | [] |
EuroVis | 2,021 | ClusterSets: Optimizing Planar Clusters in Categorical Point Data | 10.1111/cgf.14322 | In geographic data analysis, one is often given point data of different categories (such as facilities of a university categorized by department). Drawing upon recent research on set visualization, we want to visualize category membership by connecting points of the same category with visual links. Existing approaches that follow this path usually insist on connecting all members of a category, which may lead to many crossings and visual clutter. We propose an approach that avoids crossings between connections of different categories completely. Instead of connecting all data points of the same category, we subdivide categories into smaller, local clusters where needed. We do a case study comparing the legibility of drawings produced by our approach and those by existing approaches.In our problem formulation, we are additionally given a graph G on the data points whose edges express some sort of proximity. Our aim is to find a subgraph G′ of G with the following properties: (i) edges connect only data points of the same category, (ii) no two edges cross, and (iii) the number of connected components (clusters) is minimized. We then visualize the clusters in G′. For arbitrary graphs, the resulting optimization problem, Cluster Minimization, is NP‐hard (even to approximate). Therefore, we introduce two heuristics. We do an extensive benchmark test on real‐world data. Comparisons with exact solutions indicate that our heuristics do astonishing well for certain relative‐neighborhood graphs. | false | false | [
"Jakob Geiger",
"Sabine Cornelsen",
"Jan-Henrik Haunert",
"Philipp Kindermann",
"Tamara Mchedlidze",
"Martin Nöllenburg",
"Yoshio Okamoto",
"Alexander Wolff 0001"
] | [] | [] | [] |
EuroVis | 2,021 | Color Nameability Predicts Inference Accuracy in Spatial Visualizations | 10.1111/cgf.14288 | Color encoding is foundational to visualizing quantitative data. Guidelines for colormap design have traditionally emphasized perceptual principles, such as order and uniformity. However, colors also evoke cognitive and linguistic associations whose role in data interpretation remains underexplored. We study how two linguistic factors, name salience and name variation, affect people's ability to draw inferences from spatial visualizations. In two experiments, we found that participants are better at interpreting visualizations when viewing colors with more salient names (e.g., prototypical ‘blue’, ‘yellow’, and ‘red’ over ‘teal’, ‘beige’, and ‘maroon’). The effect was robust across four visualization types, but was more pronounced in continuous (e.g., smooth geographical maps) than in similar discrete representations (e.g., choropleths). Participants' accuracy also improved as the number of nameable colors increased, although the latter had a less robust effect. Our findings suggest that color nameability is an important design consideration for quantitative colormaps, and may even outweigh traditional perceptual metrics. In particular, we found that the linguistic associations of color are a better predictor of performance than the perceptual properties of those colors. We discuss the implications and outline research opportunities. The data and materials for this study are available at https://osf.io/asb7n | false | false | [
"Khairi Reda",
"Amey A. Salvi",
"Jack Gray",
"Michael E. Papka"
] | [
"BP"
] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "https://osf.io/wdvzt",
"icon": "paper"
}
] |
EuroVis | 2,021 | CommAID: Visual Analytics for Communication Analysis through Interactive Dynamics Modeling | 10.1111/cgf.14286 | Communication consists of both meta‐information as well as content. Currently, the automated analysis of such data often focuses either on the network aspects via social network analysis or on the content, utilizing methods from text‐mining. However, the first category of approaches does not leverage the rich content information, while the latter ignores the conversation environment and the temporal evolution, as evident in the meta‐information. In contradiction to communication research, which stresses the importance of a holistic approach, both aspects are rarely applied simultaneously, and consequently, their combination has not yet received enough attention in automated analysis systems. In this work, we aim to address this challenge by discussing the difficulties and design decisions of such a path as well as contribute CommAID, a blueprint for a holistic strategy to communication analysis. It features an integrated visual analytics design to analyze communication networks through dynamics modeling, semantic pattern retrieval, and a user‐adaptable and problem‐specific machine learning‐based retrieval system. An interactive multi‐level matrix‐based visualization facilitates a focused analysis of both network and content using inline visuals supporting cross‐checks and reducing context switches. We evaluate our approach in both a case study and through formative evaluation with eight law enforcement experts using a real‐world communication corpus. Results show that our solution surpasses existing techniques in terms of integration level and applicability. With this contribution, we aim to pave the path for a more holistic approach to communication analysis. | false | false | [
"Maximilian T. Fischer",
"Daniel Seebacher",
"Rita Sevastjanova",
"Daniel A. Keim",
"Mennatallah El-Assady"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2106.06334v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | Compressive Neural Representations of Volumetric Scalar Fields | 10.1111/cgf.14295 | We present an approach for compressing volumetric scalar fields using implicit neural representations. Our approach represents a scalar field as a learned function, wherein a neural network maps a point in the domain to an output scalar value. By setting the number of weights of the neural network to be smaller than the input size, we achieve compressed representations of scalar fields, thus framing compression as a type of function approximation. Combined with carefully quantizing network weights, we show that this approach yields highly compact representations that outperform state‐of‐the‐art volume compression approaches. The conceptual simplicity of our approach enables a number of benefits, such as support for time‐varying scalar fields, optimizing to preserve spatial gradients, and random‐access field evaluation. We study the impact of network design choices on compression performance, highlighting how simple network architectures are effective for a broad range of volumes. | false | false | [
"Yuzhe Lu",
"Kairong Jiang",
"Joshua A. Levine",
"Matthew Berger"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2104.04523v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | Daisen: A Framework for Visualizing Detailed GPU Execution | 10.1111/cgf.14303 | Graphics Processing Units (GPUs) have been widely used to accelerate artificial intelligence, physics simulation, medical imaging, and information visualization applications. To improve GPU performance, GPU hardware designers need to identify performance issues by inspecting a huge amount of simulator‐generated traces. Visualizing the execution traces can reduce the cognitive burden of users and facilitate making sense of behaviors of GPU hardware components. In this paper, we first formalize the process of GPU performance analysis and characterize the design requirements of visualizing execution traces based on a survey study and interviews with GPU hardware designers. We contribute data and task abstraction for GPU performance analysis. Based on our task analysis, we propose Daisen, a framework that supports data collection from GPU simulators and provides visualization of the simulator‐generated GPU execution traces. Daisen features a data abstraction and trace format that can record simulator‐generated GPU execution traces. Daisen also includes a web‐based visualization tool that helps GPU hardware designers examine GPU execution traces, identify performance bottlenecks, and verify performance improvement. Our qualitative evaluation with GPU hardware designers demonstrates that the design of Daisen reflects the typical workflow of GPU hardware designers. Using Daisen, participants were able to effectively identify potential performance bottlenecks and opportunities for performance improvement. The open‐sourced implementation of Daisen can be found at gitlab.com/akita/vis. Supplemental materials including a demo video, survey questions, evaluation study guide, and post‐study evaluation survey are available at osf.io/j5ghq. | false | false | [
"Yifan Sun 0002",
"Yixuan Zhang",
"Ali Mosallaei",
"Michael D. Shah",
"Cody Dunne",
"David R. Kaeli"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2104.00828v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | Data to Physicalization: A Survey of the Physical Rendering Process | 10.1111/cgf.14330 | Physical representations of data offer physical and spatial ways of looking at, navigating, and interacting with data. While digital fabrication has facilitated the creation of objects with data‐driven geometry, rendering data as a physically fabricated object is still a daunting leap for many physicalization designers. Rendering in the scope of this research refers to the back‐and‐forth process from digital design to digital fabrication and its specific challenges. We developed a corpus of example data physicalizations from research literature and physicalization practice. This survey then unpacks the “rendering” phase of the extended InfoVis pipeline in greater detail through these examples, with the aim of identifying ways that researchers, artists, and industry practitioners “render” physicalizations using digital design and fabrication tools. | false | false | [
"Hessam Djavaherpour",
"Faramarz F. Samavati",
"Ali Mahdavi-Amiri",
"Fatemeh Yazdanbakhsh",
"Samuel Huron",
"Richard Levy",
"Yvonne Jansen",
"Lora Oehlberg"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2102.11175v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | Design Patterns and Trade-Offs in Responsive Visualization for Communication | 10.1111/cgf.14321 | Increased access to mobile devices motivates the need to design communicative visualizations that are responsive to varying screen sizes. However, relatively little design guidance or tooling is currently available to authors. We contribute a detailed characterization of responsive visualization strategies in communication‐oriented visualizations, identifying 76 total strategies by analyzing 378 pairs of large screen (LS) and small screen (SS) visualizations from online articles and reports. Our analysis distinguishes between the Targets of responsive visualization, referring to what elements of a design are changed and Actions representing how targets are changed. We identify key trade‐offs related to authors' need to maintain graphical density, referring to the amount of information per pixel, while also maintaining the “message” or intended takeaways for users of a visualization. We discuss implications of our findings for future visualization tool design to support responsive transformation of visualization designs, including requirements for automated recommenders for communication‐oriented responsive visualizations. | false | false | [
"Hyeok Kim",
"Dominik Moritz",
"Jessica Hullman"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2104.07724v2",
"icon": "paper"
}
] |
EuroVis | 2,021 | Design Space of Origin-Destination Data Visualization | 10.1111/cgf.14310 | Visualization is an essential tool for observing and analyzing origin‐destination (OD) data, which encodes flows between geographic locations, e.g., in applications concerning commuting, migration, and transport of goods. However, depicting OD data often encounter issues of cluttering and occlusion. To address these issues, many visual designs feature data abstraction and visual abstraction, such as node aggregation and edge bundling, resulting in information loss. The recent theoretical and empirical developments in visualization have substantiated the merits of such abstraction, while confirming that viewers' knowledge can alleviate the negative impact due to information loss. It is thus desirable to map out different ways of losing and adding information in origin‐destination data visualization (ODDV). We therefore formulate a new design space of ODDV based on the categorization of informative operations on OD data in data abstraction and visual abstraction. We apply this design space to existing ODDV methods, outline strategies for exploring the design space, and suggest ideas for further exploration. | false | false | [
"Martijn Tennekes",
"Min Chen 0001"
] | [] | [] | [] |
EuroVis | 2,021 | Exploring Multi-dimensional Data via Subset Embedding | 10.1111/cgf.14290 | Multi‐dimensional data exploration is a classic research topic in visualization. Most existing approaches are designed for identifying record patterns in dimensional space or subspace. In this paper, we propose a visual analytics approach to exploring subset patterns. The core of the approach is a subset embedding network (SEN) that represents a group of subsets as uniformly‐formatted embeddings. We implement the SEN as multiple subnets with separate loss functions. The design enables to handle arbitrary subsets and capture the similarity of subsets on single features, thus achieving accurate pattern exploration, which in most cases is searching for subsets having similar values on few features. Moreover, each subnet is a fully‐connected neural network with one hidden layer. The simple structure brings high training efficiency. We integrate the SEN into a visualization system that achieves a 3‐step workflow. Specifically, analysts (1) partition the given dataset into subsets, (2) select portions in a projected latent space created using the SEN, and (3) determine the existence of patterns within selected subsets. Generally, the system combines visualizations, interactions, automatic methods, and quantitative measures to balance the exploration flexibility and operation efficiency, and improve the interpretability and faithfulness of the identified patterns. Case studies and quantitative experiments on multiple open datasets demonstrate the general applicability and effectiveness of our approach. | false | false | [
"Peng Xie",
"Wenyuan Tao",
"Jie Li 0006",
"Wentao Huang",
"Siming Chen 0001"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2104.11867v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | Guided Stable Dynamic Projections | 10.1111/cgf.14291 | Projections aim to convey the relationships and similarity of high‐dimensional data in a low‐dimensional representation. Most such techniques are designed for static data. When used for time‐dependent data, they usually fail to create a stable and suitable low dimensional representation. We propose two dynamic projection methods (PCD‐tSNE and LD‐tSNE) that use global guides to steer projection points. This avoids unstable movement that does not encode data dynamics while keeping t‐SNE's neighborhood preservation ability. PCD‐tSNE scores a good balance between stability, neighborhood preservation, and distance preservation, while LD‐tSNE allows creating stable and customizable projections. We compare our methods to 11 other techniques using quality metrics and datasets provided by a recent benchmark for dynamic projections. | false | false | [
"Eduardo Faccin Vernier",
"João Luiz Dihl Comba",
"Alexandru C. Telea"
] | [] | [] | [] |
EuroVis | 2,021 | Hornero: Thunderstorms Characterization using Visual Analytics | 10.1111/cgf.14308 | Analyzing the evolution of thunderstorms is critical in determining the potential for the development of severe weather events. Existing visualization systems for short‐term weather forecasting (nowcasting) allow for basic analysis and prediction of storm developments. However, they lack advanced visual features for efficient decision‐making. We developed a visual analytics tool for the detection of hazardous thunderstorms and their characterization, using a visual design centered on a reformulated expert task workflow that includes visual features to overview storms and quickly identify high‐impact weather events, a novel storm graph visualization to inspect and analyze the storm structure, as well as a set of interactive views for efficient identification of similar storm cells (known as analogs) in historical data and their use for nowcasting. Our tool was designed with and evaluated by meteorologists and expert forecasters working in short‐term operational weather forecasting of severe weather events. Results show that our solution suits the forecasters' workflow. Our visual design is expressive, easy to use, and effective for prompt analysis and quick decision‐making in the context of short‐range operational weather forecasting. | false | false | [
"Alexandra Diehl",
"Leandro Pelorosso",
"Juan Ruiz 0002",
"Renato Pajarola",
"M. Eduard Gröller",
"Stefan Bruckner"
] | [] | [] | [] |
EuroVis | 2,021 | Implicit Modeling of Patient-Specific Aortic Dissections with Elliptic Fourier Descriptors | 10.1111/cgf.14318 | Aortic dissection is a life‐threatening vascular disease characterized by abrupt formation of a new flow channel (false lumen) within the aortic wall. Survivors of the acute phase remain at high risk for late complications, such as aneurysm formation, rupture, and death. Morphologic features of aortic dissection determine not only treatment strategies in the acute phase (surgical vs. endovascular vs. medical), but also modulate the hemodynamics in the false lumen, ultimately responsible for late complications. Accurate description of the true and false lumen, any communications across the dissection membrane separating the two lumina, and blood supply from each lumen to aortic branch vessels is critical for risk prediction. Patient‐specific surface representations are also a prerequisite for hemodynamic simulations, but currently require time‐consuming manual segmentation of CT data. We present an aortic dissection cross‐sectional model that captures the varying aortic anatomy, allowing for reliable measurements and creation of high‐quality surface representations. In contrast to the traditional spline‐based cross‐sectional model, we employ elliptic Fourier descriptors, which allows users to control the accuracy of the cross‐sectional contour of a flow channel. We demonstrate (i) how our approach can solve the requirements for generating surface and wall representations of the flow channels, (ii) how any number of communications between flow channels can be specified in a consistent manner, and (iii) how well branches connected to the respective flow channels are handled. Finally, we discuss how our approach is a step forward to an automated generation of surface models for aortic dissections from raw 3D imaging segmentation masks. | false | false | [
"Gabriel Mistelbauer",
"Christian Rössl",
"Kathrin Bäumler",
"Bernhard Preim",
"Dominik Fleischmann"
] | [] | [] | [] |
EuroVis | 2,021 | iQUANT: Interactive Quantitative Investment Using Sparse Regression Factors | 10.1111/cgf.14299 | The model‐based investing using financial factors is evolving as a principal method for quantitative investment. The main challenge lies in the selection of effective factors towards excess market returns. Existing approaches, either hand‐picking factors or applying feature selection algorithms, do not orchestrate both human knowledge and computational power. This paper presents iQUANT, an interactive quantitative investment system that assists equity traders to quickly spot promising financial factors from initial recommendations suggested by algorithmic models, and conduct a joint refinement of factors and stocks for investment portfolio composition. We work closely with professional traders to assemble empirical characteristics of “good” factors and propose effective visualization designs to illustrate the collective performance of financial factors, stock portfolios, and their interactions. We evaluate iQUANT through a formal user study, two case studies, and expert interviews, using a real stock market dataset consisting of 3000 stocks × 6000 days × 56 factors. | false | false | [
"Xuanwu Yue",
"Qiao Gu",
"Deyun Wang",
"Huamin Qu",
"Yong Wang 0021"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2104.11485v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | Learning Contextualized User Preferences for Co-Adaptive Guidance in Mixed-Initiative Topic Model Refinement | 10.1111/cgf.14301 | Mixed‐initiative visual analytics systems support collaborative human‐machine decision‐making processes. However, many multi‐objective optimization tasks, such as topic model refinement, are highly subjective and context‐dependent. Hence, systems need to adapt their optimization suggestions throughout the interactive refinement process to provide efficient guidance. To tackle this challenge, we present a technique for learning context‐dependent user preferences and demonstrate its applicability to topic model refinement. We deploy agents with distinct associated optimization strategies that compete for the user's acceptance of their suggestions. To decide when to provide guidance, each agent maintains an intelligible, rule‐based classifier over context vectorizations that captures the development of quality metrics between distinct analysis states. By observing implicit and explicit user feedback, agents learn in which contexts to provide their specific guidance operation. An agent in topic model refinement might, for example, learn to react to declining model coherence by suggesting to split a topic. Our results confirm that the rules learned by agents capture contextual user preferences. Further, we show that the learned rules are transferable between similar datasets, avoiding common cold‐start problems and enabling a continuous refinement of agents across corpora. | false | false | [
"Fabian Sperrle",
"Hanna Schäfer",
"Daniel A. Keim",
"Mennatallah El-Assady"
] | [] | [] | [] |
EuroVis | 2,021 | Leveraging Topological Events in Tracking Graphs for Understanding Particle Diffusion | 10.1111/cgf.14304 | Single particle tracking (SPT) of fluorescent molecules provides significant insights into the diffusion and relative motion of tagged proteins and other structures of interest in biology. However, despite the latest advances in high‐resolution microscopy, individual particles are typically not distinguished from clusters of particles. This lack of resolution obscures potential evidence for how merging and splitting of particles affect their diffusion and any implications on the biological environment. The particle tracks are typically decomposed into individual segments at observed merge and split events, and analysis is performed without knowing the true count of particles in the resulting segments. Here, we address the challenges in analyzing particle tracks in the context of cancer biology. In particular, we study the tracks of KRAS protein, which is implicated in nearly 20% of all human cancers, and whose clustering and aggregation have been linked to the signaling pathway leading to uncontrolled cell growth. We present a new analysis approach for particle tracks by representing them as tracking graphs and using topological events – merging and splitting, to disambiguate the tracks. Using this analysis, we infer a lower bound on the count of particles as they cluster and create conditional distributions of diffusion speeds before and after merge and split events. Using thousands of time‐steps of simulated and in‐vitro SPT data, we demonstrate the efficacy of our method, as it offers the biologists a new, detailed look into the relationship between KRAS clustering and diffusion speeds. | false | false | [
"Torin McDonald",
"Rebika Shrestha",
"Xiyu Yi",
"Harsh Bhatia",
"De Chen",
"Debanjan Goswami",
"Valerio Pascucci",
"Thomas Turbyville",
"Peer-Timo Bremer"
] | [] | [] | [] |
EuroVis | 2,021 | Line Weaver: Importance-Driven Order Enhanced Rendering of Dense Line Charts | 10.1111/cgf.14316 | Line charts are an effective and widely used technique for visualizing series of ordered two‐dimensional data points. The relationship between consecutive points is indicated by connecting line segments, revealing potential trends or clusters in the underlying data. However, when dealing with an increasing number of lines, the render order substantially influences the resulting visualization. Rendering transparent lines can help but unfortunately the blending order is currently either ignored or naively used, for example, assuming it is implicitly given by the order in which the data was saved in a file. Due to the non‐commutativity of classic alpha blending, this results in contradicting visualizations of the same underlying data set, so‐called “hallucinators”. In this paper, we therefore present line weaver, a novel visualization technique for dense line charts. Using an importance function, we developed an approach that correctly considers the blending order independently of the render order and without any prior sorting of the data. We allow for importance functions which are either explicitly given or implicitly derived from the geometric properties of the data if no external data is available. The importance can then be applied globally to entire lines, or locally per pixel which simultaneously supports various types of user interaction. Finally, we discuss the potential of our contribution based on different synthetic and real‐world data sets where classic or naive approaches would fail. | false | false | [
"Thomas Trautner",
"Stefan Bruckner"
] | [] | [] | [] |
EuroVis | 2,021 | Local Extraction of 3D Time-Dependent Vector Field Topology | 10.1111/cgf.14293 | We present an approach to local extraction of 3D time‐dependent vector field topology. In this concept, Lagrangian coherent structures, which represent the separating manifolds in time‐dependent transport, correspond to generalized streak manifolds seeded along hyperbolic path surfaces (HPSs). Instead of expensive and numerically challenging direct computation of the HPSs by intersection of ridges in the forward and backward finite‐time Lyapunov exponent (FTLE) fields, our approach employs local extraction of respective candidates in the four‐dimensional space‐time domain. These candidates are subsequently refined toward the hyperbolic path surfaces, which provides unsteady equivalents of saddle‐type critical points, periodic orbits, and bifurcation lines from steady, traditional vector field topology. In contrast to FTLE‐based methods, we obtain an explicit geometric representation of the topological skeleton of the flow, which for steady flows coincides with the hyperbolic invariant manifolds of vector field topology. We evaluate our approach on analytical flows, as well as data from computational fluid dynamics, using the FTLE as a ground truth superset, i.e., we also show that FTLE ridges exhibit several types of false positives. | false | false | [
"Lutz Hofmann",
"Filip Sadlo"
] | [] | [] | [] |
EuroVis | 2,021 | Optimal Axes for Data Value Estimation in Star Coordinates and Radial Axes Plots | 10.1111/cgf.14323 | Radial axes plots are projection methods that represent high‐dimensional data samples as points on a two‐dimensional plane. These techniques define mappings through a set of axis vectors, each associated with a data variable, which users can manipulate interactively to create different plots and analyze data from multiple points of view. However, updating the direction and length of an axis vector is far from trivial. Users must consider the data analysis task, domain knowledge, the directions in which values should increase, the relative importance of each variable, or the correlations between variables, among other factors. Another issue is the difficulty to approximate high‐dimensional data values in the two‐dimensional visualizations, which can hamper searching for data with particular characteristics, analyzing the most common data values in clusters, inspecting outliers, etc. In this paper we present and analyze several optimization approaches for enhancing radial axes plots regarding their ability to represent high‐dimensional data values. The techniques can be used not only to approximate data values with greater accuracy, but also to guide users when updating axis vectors or extending visualizations with new variables, since they can reveal poor choices of axis vectors. The optimal axes can also be included in nonlinear plots. In particular, we show how they can be used within RadViz to assess the quality of a variable ordering. The in‐depth analysis carried out is useful for visualization designers developing radial axes techniques, or planning to incorporate axes into other visualization methods. | false | false | [
"Manuel Rubio-Sánchez",
"Dirk J. Lehmann",
"Alberto Sánchez 0001",
"José Luis Rojo-Álvarez"
] | [] | [] | [] |
EuroVis | 2,021 | Parameterized Splitting of Summed Volume Tables | 10.1111/cgf.14294 | Summed Volume Tables (SVTs) allow one to compute integrals over the data values in any cubical area of a three‐dimensional orthogonal grid in constant time, and they are especially interesting for building spatial search structures for sparse volumes. However, SVTs become extremely memory consuming due to the large values they need to store; for a dataset of n values an SVT requires 𝒪(n log n) bits. The 3D Fenwick tree allows recovering the integral values in 𝒪(log3 n) time, at a memory consumption of 𝒪(n) bits. We propose an algorithm that generates SVT representations that can flexibly trade speed for memory: From similar characteristics as SVTs, over equal memory consumption as 3D Fenwick trees at significantly lower computational complexity, to even further reduced memory consumption at the cost of raising computational complexity. For a 641 × 9601 × 9601 binary dataset, the algorithm can generate an SVT representation that requires 27.0GB and 46 · 8 data fetch operations to retrieve an integral value, compared to 27.5GB and 1521·8 fetches by 3D Fenwick trees, a decrease in fetches of 97%. A full SVT requires 247.6GB and 8 fetches per integral value. We present a novel hierarchical approach to compute and store intermediate prefix sums of SVTs, so that any prescribed memory consumption between 𝒪(n) bits and 𝒪(n log n) bits is achieved. We evaluate the performance of the proposed algorithm in a number of examples considering large volume data, and we perform comparisons to existing alternatives. | false | false | [
"Christian Reinbold",
"Rüdiger Westermann"
] | [] | [] | [] |
EuroVis | 2,021 | ParSetgnostics: Quality Metrics for Parallel Sets | 10.1111/cgf.14314 | While there are many visualization techniques for exploring numeric data, only a few work with categorical data. One prominent example is Parallel Sets, showing data frequencies instead of data points ‐ analogous to parallel coordinates for numerical data. As nominal data does not have an intrinsic order, the design of Parallel Sets is sensitive to visual clutter due to overlaps, crossings, and subdivision of ribbons hindering readability and pattern detection. In this paper, we propose a set of quality metrics, called ParSetgnostics (Parallel Sets diagnostics), which aim to improve Parallel Sets by reducing clutter. These quality metrics quantify important properties of Parallel Sets such as overlap, orthogonality, ribbon width variance, and mutual information to optimize the category and dimension ordering. By conducting a systematic correlation analysis between the individual metrics, we ensure their distinctiveness. Further, we evaluate the clutter reduction effect of ParSetgnostics by reconstructing six datasets from previous publications using Parallel Sets measuring and comparing their respective properties. Our results show that ParSetgostics facilitates multi‐dimensional analysis of categorical data by automatically providing optimized Parallel Set designs with a clutter reduction of up to 81% compared to the originally proposed Parallel Sets visualizations. | false | false | [
"Frederik L. Dennig",
"Maximilian T. Fischer",
"Michael Blumenschein",
"Johannes Fuchs 0001",
"Daniel A. Keim",
"Evanthia Dimara"
] | [] | [] | [] |
EuroVis | 2,021 | ProBGP: Progressive Visual Analytics of Live BGP Updates | 10.1111/cgf.14287 | The global routing network is the backbone of the Internet. However, it is quite vulnerable to attacks that cause major disruptions or routing manipulations. Prior related works have visualized routing path changes with node link diagrams, but it requires strong domain expertise to understand if a routing change between autonomous systems is suspicious. Geographic visualization has an advantage over conventional node‐link diagrams by helping uncover such suspicious routes as the user can immediately see if a path is the shortest path to the target or an unreasonable detour. In this paper, we present ProBGP, a web‐based progressive approach to visually analyze BGP update routes. We created a novel progressive data processing algorithm for the geographic approximation of autonomous systems and combined it with a progressively updating visualization. While the newest log data is continuously loaded, our approach also allows querying the entire log recordings since 1999. We present the usefulness of our approach with a real use case of a major route leak from June 2019. We report on multiple interviews with domain experts throughout the development. Finally, we evaluated our algorithm quantitatively against a public peering database and qualitatively against AS network maps. | false | false | [
"Alex Ulmer",
"David Sessler",
"Jörn Kohlhammer"
] | [] | [] | [] |
EuroVis | 2,021 | Public Data Visualization: Analyzing Local Running Statistics on Situated Displays | 10.1111/cgf.14297 | Popular sports tracking applications allow athletes to share and compare their personal performance data with others. Visualizing this data in relevant public settings can be beneficial in provoking novel types of opportunistic and communal sense‐making. We investigated this premise by situating an analytical visualization of running performances on two touch‐enabled public displays in proximity to a local community running trail. Using a rich mixed‐method evaluation protocol during a three‐week‐long in‐the‐wild deployment, we captured its social and analytical impact across 235 distinct interaction sessions. Our results show how our public analytical visualization supported passers‐by to create novel insights that were rather of casual nature. Several textual features that surrounded the visualization, such as titles that were framed as provocative hypotheses and predefined attention‐grabbing data queries, sparked interest and social debate, while a narrative tutorial facilitated more analytical interaction patterns. Our detailed mixed‐methods evaluation approach led to a set of actionable takeaways for public visualizations that allow novice audiences to engage with data analytical insights that have local relevance. | false | false | [
"Jorgos Coenen",
"Andrew Vande Moere"
] | [] | [] | [] |
EuroVis | 2,021 | Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization | 10.1111/cgf.14331 | In topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse–Smale complexes play an essential role in capturing the shape of scalar field data. We present a state‐of‐the‐art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time‐varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures. | false | false | [
"Lin Yan",
"Talha Bin Masood",
"Raghavendra Sridharamurthy",
"Farhan Rasheed",
"Vijay Natarajan",
"Ingrid Hotz",
"Bei Wang 0001"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2106.00157v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | SenVis: Interactive Tensor-based Sensitivity Visualization | 10.1111/cgf.14306 | Sobol's method is one of the most powerful and widely used frameworks for global sensitivity analysis, and it maps every possible combination of input variables to an associated Sobol index. However, these indices are often challenging to analyze in depth, due in part to the lack of suitable, flexible enough, and fast‐to‐query data access structures as well as visualization techniques. We propose a visualization tool that leverages tensor decomposition, a compressed data format that can quickly and approximately answer sophisticated queries over exponential‐sized sets of Sobol indices. This way, we are able to capture the complete global sensitivity information of high‐dimensional scalar models. Our application is based on a three‐stage visualization, to which variables to be analyzed can be added or removed interactively. It includes a novel hourglass‐like diagram presenting the relative importance for any single variable or combination of input variables with respect to any composition of the rest of the input variables. We showcase our visualization with a range of example models, whereby we demonstrate the high expressive power and analytical capability made possible with the proposed method. | false | false | [
"Haiyan Yang",
"Rafael Ballester-Ripoll",
"Renato Pajarola"
] | [] | [] | [] |
EuroVis | 2,021 | SumRe: Design and Evaluation of a Gist-based Summary Visualization for Incident Reports Triage | 10.1111/cgf.14305 | Incident report triage is a common endeavor in many industry sectors, often coupled with serious public safety implications. For example, at the US Food and Drug Administration (FDA), analysts triage an influx of incident reports to identify previously undiscovered drug safety problems. However, these analysts currently conduct this critical yet error‐prone incident report triage using a generic table‐based interface, with no formal support. Visualization design, task‐characterization methodologies, and evaluation models offer several possibilities for better supporting triage workflows, including those dealing with drug safety and beyond. In this work, we aim to elevate the work of triage through a task‐abstraction activity with FDA analysts. Second, we design an alternative gist‐based summary of text documents used in triage (SumRe). Third, we conduct a crowdsourced evaluation of SumRe with medical experts. Results of the crowdsourced study with medical experts (n = 20) suggest that SumRe better supports accuracy in understanding the gist of a given report, and in identifying important reports for followup activities. We discuss implications of these results, including design considerations for triage workflows beyond the drug domain, as well as methodologies for comparing visualization‐enabled text summaries. | false | false | [
"Tabassum Kakar",
"Xiao Qin 0003",
"Thang La",
"Sanjay K. Sahoo",
"Suranjan De",
"Elke A. Rundensteiner",
"Lane Harrison"
] | [] | [] | [] |
EuroVis | 2,021 | Texture Browser: Feature-based Texture Exploration | 10.1111/cgf.14292 | Texture is a key characteristic in the definition of the physical appearance of an object and a crucial element in the creation process of 3D artists. However, retrieving a texture that matches an intended look from an image collection is difficult. Contrary to most photo collections, for which object recognition has proven quite useful, syntactic descriptions of texture characteristics is not straightforward, and even creating appropriate metadata is a very difficult task. In this paper, we propose a system to help explore large unlabeled collections of texture images. The key insight is that spatially grouping textures sharing similar features can simplify navigation. Our system uses a pre‐trained convolutional neural network to extract high‐level semantic image features, which are then mapped to a 2‐dimensional location using an adaptation of t‐SNE, a dimensionality‐reduction technique. We describe an interface to visualize and explore the resulting distribution and provide a series of enhanced navigation tools, our prioritized t‐SNE, scalable clustering, and multi‐resolution embedding, to further facilitate exploration and retrieval tasks. Finally, we also present the results of a user evaluation that demonstrates the effectiveness of our solution. | false | false | [
"Xuejiao Luo",
"Leonardo Scandolo",
"Elmar Eisemann"
] | [] | [] | [] |
EuroVis | 2,021 | Thin-Volume Visualization on Curved Domains | 10.1111/cgf.14296 | Thin, curved structures occur in many volumetric datasets. Their analysis using classical volume rendering is difficult because parts of such structures can bend away or hide behind occluding elements. This problem cannot be fully compensated by effective navigation alone, as structure‐adapted navigation in the volume is cumbersome and only parts of the structure are visible in each view. We solve this problem by rendering a spatially transformed view of the volume so that an unobstructed visualization of the entire curved structure is obtained. As a result, simple and intuitive navigation becomes possible. The domain of the spatial transform is defined by a triangle mesh that is topologically equivalent to an open disc and that approximates the structure of interest. The rendering is based on ray‐casting, in which the rays traverse the original volume. In order to carve out volumes of varying thicknesses, the lengths of the rays as well as the positions of the mesh vertices can be easily modified by interactive painting under view control.We describe a prototypical implementation and demonstrate the interactive visual inspection of complex structures from digital humanities, biology, medicine, and material sciences. The visual representation of the structure as a whole allows for easy inspection of interesting substructures in their original spatial context. Overall, we show that thin, curved structures in volumetric data can be excellently visualized using ray‐casting‐based volume rendering of transformed views defined by guiding surface meshes, supplemented by interactive, local modifications of ray lengths and vertex positions. | false | false | [
"Felix Herter",
"Hans-Christian Hege",
"Markus Hadwiger",
"Verena Lepper",
"Daniel Baum"
] | [] | [] | [] |
EuroVis | 2,021 | Topography of Violence: Considerations for Ethical and Collaborative Visualization Design | 10.1111/cgf.14285 | Based on a collaborative visualization design process involving sensitive historical data and historiographical expertise, we investigate the relevance of ethical principles in visualization design. While fundamental ethical norms like truthfulness and accuracy are already well‐described and common goals in visualization design, datasets that are accompanied by specific ethical concerns need to be processed and visualized with an additional level of carefulness and thought. There has been little research on adequate visualization design incorporating such considerations. To address this gap we present insights from Topography of Violence, a visualization project with the Jewish Museum Berlin that focuses on a dataset of more than 4,500 acts of violence against Jews in Germany between 1930 and 1938. Drawing from the joint project, we develop an approach to the visualization of sensitive data, which features both conceptual and procedural considerations for visualization design. Our findings provide value for both visualization researchers and practitioners by highlighting challenges and opportunities for ethical data visualization. | false | false | [
"Fabian Ehmel",
"Viktoria Brüggemann",
"Marian Dörk"
] | [] | [] | [] |
EuroVis | 2,021 | TourVis: Narrative Visualization of Multi-Stage Bicycle Races | 10.1111/cgf.14327 | There are many multiple‐stage racing competitions in various sports such as swimming, running, or cycling. The wide availability of affordable tracking devices facilitates monitoring the position along with the race of all participants, even for non‐professional contests. Getting real‐time information of contenders is useful but also unleashes the possibility of creating more complex visualization systems that ease the understanding of the behavior of all participants during a simple stage or throughout the whole competition. In this paper we focus on bicycle races, which are highly popular, especially in Europe, being the Tour de France its greatest exponent. Current visualizations from TV broadcasting or real‐time tracking websites are useful to understand the current stage status, up to a certain extent. Unfortunately, still no current system exists that visualizes a whole multi‐stage contest in such a way that users can interactively explore the relevant events of a single stage (e.g. breakaways, groups, virtual leadership…), as well as the full competition. In this paper, we present an interactive system that is useful both for aficionados and professionals to visually analyze the development of multi‐stage cycling competitions. | false | false | [
"José Díaz 0003",
"Marta Fort",
"Pere-Pau Vázquez"
] | [] | [] | [] |
EuroVis | 2,021 | Uncertainty-aware Visualization in Medical Imaging - A Survey | 10.1111/cgf.14333 | Medical imaging (image acquisition, image transformation, and image visualization) is a standard tool for clinicians in order to make diagnoses, plan surgeries, or educate students. Each of these steps is affected by uncertainty, which can highly influence the decision‐making process of clinicians. Visualization can help in understanding and communicating these uncertainties. In this manuscript, we aim to summarize the current state‐of‐the‐art in uncertainty‐aware visualization in medical imaging. Our report is based on the steps involved in medical imaging as well as its applications. Requirements are formulated to examine the considered approaches. In addition, this manuscript shows which approaches can be combined to form uncertainty‐aware medical imaging pipelines. Based on our analysis, we are able to point to open problems in uncertainty‐aware medical imaging. | false | false | [
"Christina Gillmann",
"Dorothee Saur",
"Thomas Wischgoll",
"Gerik Scheuermann"
] | [] | [] | [] |
EuroVis | 2,021 | Uncertainty-aware Visualization of Regional Time Series Correlation in Spatio-temporal Ensembles | 10.1111/cgf.14326 | Given a time‐varying scalar field, the analysis of correlations between different spatial regions, i.e., the linear dependence of time series within these regions, provides insights into the structural properties of the data. In this context, regions are connected components of the spatial domain with high time series correlations. The detection and analysis of such regions is often performed globally, which requires pairwise correlation computations that are quadratic in the number of spatial data samples. Thus, operations based on all pairwise correlations are computationally demanding, especially when dealing with ensembles that model the uncertainty in the spatio‐temporal phenomena using multiple simulation runs. We propose a two‐step procedure: In a first step, we map the spatial samples to a 3D embedding based on a pairwise correlation matrix computed from the ensemble of time series. The 3D embedding allows for a one‐to‐one mapping to a 3D color space such that the outcome can be visually investigated by rendering the colors for all samples in the spatial domain. In a second step, we generate a hierarchical image segmentation based on the color images. From then on, we can visually analyze correlations of regions at all levels in the hierarchy within an interactive setting, which includes the uncertainty‐aware analysis of the region's time series correlation and respective time lags. | false | false | [
"Marina Evers",
"Karim Huesmann",
"Lars Linsen"
] | [] | [] | [] |
EuroVis | 2,021 | VEHICLE: Validation and Exploration of the Hierarchical Integration of Conflict Event Data | 10.1111/cgf.14284 | The exploration of large‐scale conflicts, as well as their causes and effects, is an important aspect of socio‐political analysis. Since event data related to major conflicts are usually obtained from different sources, researchers developed a semi‐automatic matching algorithm to integrate event data of different origins into one comprehensive dataset using hierarchical taxonomies. The validity of the corresponding integration results is not easy to assess since the results depend on user‐defined input parameters and the relationships between the original data sources. However, only rudimentary visualization techniques have been used so far to analyze the results, allowing no trustworthy validation or exploration of how the final dataset is composed. To overcome this problem, we developed VEHICLE, a web‐based tool to validate and explore the results of the hierarchical integration. For the design, we collaborated with a domain expert to identify the underlying domain problems and derive a task and workflow description. The tool combines both traditional and novel visual analysis techniques, employing statistical and map‐based depictions as well as advanced interaction techniques. We showed the usefulness of VEHICLE in two case studies and by conducting an evaluation together with conflict researchers, confirming domain hypotheses and generating new insights. | false | false | [
"Benedikt Mayer",
"Kai Lawonn",
"Karsten Donnay",
"Bernhard Preim",
"Monique Meuschke"
] | [] | [] | [] |
EuroVis | 2,021 | VICE: Visual Identification and Correction of Neural Circuit Errors | 10.1111/cgf.14320 | A connectivity graph of neurons at the resolution of single synapses provides scientists with a tool for understanding the nervous system in health and disease. Recent advances in automatic image segmentation and synapse prediction in electron microscopy (EM) datasets of the brain have made reconstructions of neurons possible at the nanometer scale. However, automatic segmentation sometimes struggles to segment large neurons correctly, requiring human effort to proofread its output. General proofreading involves inspecting large volumes to correct segmentation errors at the pixel level, a visually intensive and time‐consuming process. This paper presents the design and implementation of an analytics framework that streamlines proofreading, focusing on connectivity‐related errors. We accomplish this with automated likely‐error detection and synapse clustering that drives the proofreading effort with highly interactive 3D visualizations. In particular, our strategy centers on proofreading the local circuit of a single cell to ensure a basic level of completeness. We demonstrate our framework's utility with a user study and report quantitative and subjective feedback from our users. Overall, users find the framework more efficient for proofreading, understanding evolving graphs, and sharing error correction strategies. | false | false | [
"Felix Gonda",
"Xueying Wang",
"Johanna Beyer",
"Markus Hadwiger",
"Jeff W. Lichtman",
"Hanspeter Pfister"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2105.06861v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization | 10.1111/cgf.14300 | During the training phase of machine learning (ML) models, it is usually necessary to configure several hyperparameters. This process is computationally intensive and requires an extensive search to infer the best hyperparameter set for the given problem. The challenge is exacerbated by the fact that most ML models are complex internally, and training involves trial‐and‐error processes that could remarkably affect the predictive result. Moreover, each hyperparameter of an ML algorithm is potentially intertwined with the others, and changing it might result in unforeseeable impacts on the remaining hyperparameters. Evolutionary optimization is a promising method to try and address those issues. According to this method, performant models are stored, while the remainder are improved through crossover and mutation processes inspired by genetic algorithms. We present VisEvol, a visual analytics tool that supports interactive exploration of hyperparameters and intervention in this evolutionary procedure. In summary, our proposed tool helps the user to generate new models through evolution and eventually explore powerful hyperparameter combinations in diverse regions of the extensive hyperparameter space. The outcome is a voting ensemble (with equal rights) that boosts the final predictive performance. The utility and applicability of VisEvol are demonstrated with two use cases and interviews with ML experts who evaluated the effectiveness of the tool. | false | false | [
"Angelos Chatzimparmpas",
"Rafael Messias Martins",
"Kostiantyn Kucher",
"Andreas Kerren"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2012.01205v3",
"icon": "paper"
}
] |
EuroVis | 2,021 | Visual Analysis of Electronic Densities and Transitions in Molecules | 10.1111/cgf.14307 | The study of electronic transitions within a molecule connected to the absorption or emission of light is a common task in the process of the design of new materials. The transitions are complex quantum mechanical processes and a detailed analysis requires a breakdown of these processes into components that can be interpreted via characteristic chemical properties. We approach these tasks by providing a detailed analysis of the electron density field. This entails methods to quantify and visualize electron localization and transfer from molecular subgroups combining spatial and abstract representations. The core of our method uses geometric segmentation of the electronic density field coupled with a graph‐theoretic formulation of charge transfer between molecular subgroups. The design of the methods has been guided by the goal of providing a generic and objective analysis following fundamental concepts. We illustrate the proposed approach using several case studies involving the study of electronic transitions in different molecular systems. | false | false | [
"Talha Bin Masood",
"Signe Sidwall Thygesen",
"Mathieu Linares",
"Alexei I. Abrikosov",
"Vijay Natarajan",
"Ingrid Hotz"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2106.01215v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | Visual Analysis of Spatio-temporal Phenomena with 1D Projections | 10.1111/cgf.14311 | It is crucial to visually extrapolate the characteristics of their evolution to understand critical spatio‐temporal events such as earthquakes, fires, or the spreading of a disease. Animations embedded in the spatial context can be helpful for understanding details, but have proven to be less effective for overview and comparison tasks. We present an interactive approach for the exploration of spatio‐temporal data, based on a set of neighborhood‐preserving 1D projections which help identify patterns and support the comparison of numerous time steps and multivariate data. An important objective of the proposed approach is the visual description of local neighborhoods in the 1D projection to reveal patterns of similarity and propagation. As this locality cannot generally be guaranteed, we provide a selection of different projection techniques, as well as a hierarchical approach, to support the analysis of different data characteristics. In addition, we offer an interactive exploration technique to reorganize and improve the mapping locally to users' foci of interest. We demonstrate the usefulness of our approach with different real‐world application scenarios and discuss the feedback we received from domain and visualization experts. | false | false | [
"Max Franke",
"Henry Martin",
"Steffen Koch 0001",
"Kuno Kurzhals"
] | [] | [] | [] |
EuroVis | 2,021 | Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth | 10.1111/cgf.14332 | We present a state‐of‐the‐art report on visualization in astrophysics. We survey representative papers from both astrophysics and visualization and provide a taxonomy of existing approaches based on data analysis tasks. The approaches are classified based on five categories: data wrangling, data exploration, feature identification, object reconstruction, as well as education and outreach. Our unique contribution is to combine the diverse viewpoints from both astronomers and visualization experts to identify challenges and opportunities for visualization in astrophysics. The main goal is to provide a reference point to bring modern data analysis and visualization techniques to the rich datasets in astrophysics. | false | false | [
"Fangfei Lan",
"Michael Young",
"Lauren Anderson",
"Anders Ynnerman",
"Alexander Bock 0002",
"Michelle A. Borkin",
"Angus G. Forbes",
"Juna A. Kollmeier",
"Bei Wang 0001"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2106.00152v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | Visualizing Carotid Blood Flow Simulations for Stroke Prevention | 10.1111/cgf.14319 | In this work, we investigate how concepts from medical flow visualization can be applied to enhance stroke prevention diagnostics. Our focus lies on carotid stenoses, i.e., local narrowings of the major brain‐supplying arteries, which are a frequent cause of stroke. Carotid surgery can reduce the stroke risk associated with stenoses, however, the procedure entails risks itself. Therefore, a thorough assessment of each case is necessary. In routine diagnostics, the morphology and hemodynamics of an afflicted vessel are separately analyzed using angiography and sonography, respectively. Blood flow simulations based on computational fluid dynamics could enable the visual integration of hemodynamic and morphological information and provide a higher resolution on relevant parameters. We identify and abstract the tasks involved in the assessment of stenoses and investigate how clinicians could derive relevant insights from carotid blood flow simulations. We adapt and refine a combination of techniques to facilitate this purpose, integrating spatiotemporal navigation, dimensional reduction, and contextual embedding. We evaluated and discussed our approach with an interdisciplinary group of medical practitioners, fluid simulation and flow visualization researchers. Our initial findings indicate that visualization techniques could promote usage of carotid blood flow simulations in practice. | false | false | [
"Pepe Eulzer",
"Monique Meuschke",
"Carsten M. Klingner",
"Kai Lawonn"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2104.02654v1",
"icon": "paper"
}
] |
EuroVis | 2,021 | What are Table Cartograms Good for Anyway? An Algebraic Analysis | 10.1111/cgf.14289 | Unfamiliar or esoteric visual forms arise in many areas of visualization. While such forms can be intriguing, it can be unclear how to make effective use of them without long periods of practice or costly user studies. In this work we analyze the table cartogram—a graphic which visualizes tabular data by bringing the areas of a grid of quadrilaterals into correspondence with the input data, like a heat map that has been “area‐ed” rather than colored. Despite having existed for several years, little is known about its appropriate usage. We mend this gap by using Algebraic Visualization Design to show that they are best suited to relatively small tables with ordinal axes for some comparison and outlier identification tasks. In doing so we demonstrate a discount theory‐based analysis that can be used to cheaply determine best practices for unknown visualizations. | false | false | [
"Andrew M. McNutt"
] | [
"HM"
] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2104.04042v1",
"icon": "paper"
}
] |
CHI | 2,021 | [email protected]: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction | 10.1145/3411764.3445421 | Most mobile health apps employ data visualization to help people view their health and activity data, but these apps provide limited support for visual data exploration. Furthermore, despite its huge potential benefits, mobile visualization research in the personal data context is sparse. This work aims to empower people to easily navigate and compare their personal health data on smartphones by enabling flexible time manipulation with speech. We designed and developed Data@Hand, a mobile app that leverages the synergy of two complementary modalities: speech and touch. Through an exploratory study with 13 long-term Fitbit users, we examined how multimodal interaction helps participants explore their own health data. Participants successfully adopted multimodal interaction (i.e., speech and touch) for convenient and fluid data exploration. Based on the quantitative and qualitative findings, we discuss design implications and opportunities with multimodal interaction for better supporting visual data exploration on mobile devices. | false | false | [
"Young-Ho Kim",
"Bongshin Lee",
"Arjun Srinivasan",
"Eun Kyoung Choe"
] | [] | [] | [] |
CHI | 2,021 | A Review on Strategies for Data Collection, Reflection, and Communication in Eating Disorder Apps | 10.1145/3411764.3445670 | Eating disorders (EDs) constitute a mental illness with the highest mortality. Today, mobile health apps provide promising means to ED patients for managing their condition. Apps enable users to monitor their eating habits, thoughts, and feelings, and offer analytic insights for behavior change. However, not only have scholars critiqued the clinical validity of these apps, their underlying design principles are not well understood. Through a review of 34 ED apps, we uncovered 11 different data types ED apps collect, and 9 strategies they employ to support collection and reflection. Drawing upon personal health informatics and visualization frameworks, we found that most apps did not adhere to best practices on what and how data should be collected from and reflected to users, or how data-driven insights should be communicated. Our review offers suggestions for improving the design of ED apps such that they can be useful and meaningful in ED recovery. | false | false | [
"Anjali Devakumar",
"Jay Modh",
"Bahador Saket",
"Eric P. S. Baumer",
"Munmun De Choudhury"
] | [] | [] | [] |
CHI | 2,021 | A Visual Analytics Approach to Facilitate the Proctoring of Online Exams | 10.1145/3411764.3445294 | Online exams have become widely used to evaluate students’ performance in mastering knowledge in recent years, especially during the pandemic of COVID-19. However, it is challenging to conduct proctoring for online exams due to the lack of face-to-face interaction. Also, prior research has shown that online exams are more vulnerable to various cheating behaviors, which can damage their credibility. This paper presents a novel visual analytics approach to facilitate the proctoring of online exams by analyzing the exam video records and mouse movement data of each student. Specifically, we detect and visualize suspected head and mouse movements of students in three levels of detail, which provides course instructors and teachers with convenient, efficient and reliable proctoring for online exams. Our extensive evaluations, including usage scenarios, a carefully-designed user study and expert interviews, demonstrate the effectiveness and usability of our approach. | false | false | [
"Haotian Li 0001",
"Min Xu",
"Yong Wang 0021",
"Huan Wei",
"Huamin Qu"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2101.07990v1",
"icon": "paper"
}
] |
CHI | 2,021 | CakeVR: A Social Virtual Reality (VR) Tool for Co-designing Cakes | 10.1145/3411764.3445503 | Cake customization services allow clients to collaboratively personalize cakes with pastry chefs. However, remote (e.g., email) and in-person co-design sessions are prone to miscommunication, due to natural restrictions in visualizing cake size, decoration, and celebration context. This paper presents the design, implementation, and expert evaluation of a social VR application (CakeVR) that allows a client to remotely co-design cakes with a pastry chef, through real-time realistic 3D visualizations. Drawing on expert semi-structured interviews (4 clients, 5 pastry chefs), we distill and incorporate 8 design requirements into our CakeVR prototype. We evaluate CakeVR with 10 experts (6 clients, 4 pastry chefs) using cognitive walkthroughs, and find that it supports ideation and decision making through intuitive size manipulation, color/flavor selection, decoration design, and custom celebration theme fitting. Our findings provide recommendations for enabling co-design in social VR and highlight CakeVR’s potential to transform product design communication through remote interactive and immersive co-design. | false | false | [
"Yanni Mei",
"Jie Li 0064",
"Huib de Ridder",
"Pablo César"
] | [] | [] | [] |
CHI | 2,021 | Can Anthropographics Promote Prosociality?A Review and Large-Sample Study | 10.1145/3411764.3445637 | Visualizations designed to make readers compassionate with the persons whose data is represented have been called anthropographics and are commonly employed by practitioners. Empirical studies have recently examined whether anthropographics indeed promote empathy, compassion, or the likelihood of prosocial behavior, but findings have been inconclusive so far. This work contributes a detailed overview of past experiments, and two new experiments that use large samples and a combination of design strategies to maximize the possibility of finding an effect. We tested an information-rich anthropographic against a simple bar chart, asking participants to allocate hypothetical money in a crowdsourcing study. We found that the anthropographic had, at best, a small effect on money allocation. Such a small effect may be relevant for large-scale donation campaigns, but the large sample sizes required to observe an effect and the noise involved in measuring it make it very difficult to study in more depth. Data and code are available at https://osf.io/xqae2/. | false | false | [
"Luiz Augusto de Macêdo Morais",
"Yvonne Jansen",
"Nazareno Andrade",
"Pierre Dragicevic"
] | [] | [] | [] |
CHI | 2,021 | Collecting and Characterizing Natural Language Utterances for Specifying Data Visualizations | 10.1145/3411764.3445400 | Natural language interfaces (NLIs) for data visualization are becoming increasingly popular both in academic research and in commercial software. Yet, there is a lack of empirical understanding of how people specify visualizations through natural language. We conducted an online study (N = 102), showing participants a series of visualizations and asking them to provide utterances they would pose to generate the displayed charts. From the responses, we curated a dataset of 893 utterances and characterized the utterances according to (1) their phrasing (e.g., commands, queries, questions) and (2) the information they contained (e.g., chart types, data aggregations). To help guide future research and development, we contribute this utterance dataset and discuss its applications toward the creation and benchmarking of NLIs for visualization. | false | false | [
"Arjun Srinivasan",
"Nikhila Nyapathy",
"Bongshin Lee",
"Steven Mark Drucker",
"John T. Stasko"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2110.00680v1",
"icon": "paper"
}
] |
CHI | 2,021 | Communicating with Motion: A Design Space for Animated Visual Narratives in Data Videos | 10.1145/3411764.3445337 | Data videos are a genre of narrative visualization that communicates stories by combining data visualization and motion graphics. While data videos are increasingly gaining popularity, few systematic reviews or structured analyses exist for their design. In this work, we introduce a design space for animated visual narratives in data videos. The design space combines a dimension for animation techniques that are frequently used to facilitate data communication with one for visual narrative strategies served by such animation techniques to support story presentation. We derived our design space from the analysis of 82 high-quality data videos collected from online sources. We conducted a workshop with 20 participants to evaluate the effectiveness of our design space. Qualitative and quantitative feedback suggested that our design space is inspirational and useful for designing and creating data videos. | false | false | [
"Yang Shi 0007",
"Xingyu Lan",
"Jingwen Li",
"Zhaorui Li",
"Nan Cao 0001"
] | [] | [] | [] |
CHI | 2,021 | Comparison of Different Types of Augmented Reality Visualizations for Instructions | 10.1145/3411764.3445724 | Augmented Reality (AR) is increasingly being used for providing guidance and supporting troubleshooting in industrial settings. While the general application of AR has been shown to provide clear benefits regarding physical tasks, it is important to understand how different visualization types influence user’s performance during the execution of the tasks. Previous studies evaluating AR and user’s performance compared different media types or types of AR hardware as opposed to different types of visualization for the same hardware type. This paper provides details of our comparative study in which we identified the influence of visualization types on the performance of complex machine set-up processes. Although our results show clear advantages to using concrete rather than abstract visualizations, we also find abstract visualizations coupled with videos leads to similar user performance as with concrete visualizations. | false | false | [
"Florian Jasche",
"Sven Hoffmann",
"Thomas Ludwig 0005",
"Volker Wulf"
] | [] | [] | [] |
CHI | 2,021 | ConceptScope: Organizing and Visualizing Knowledge in Documents based on Domain Ontology | 10.1145/3411764.3445396 | Current text visualization techniques typically provide overviews of document content and structure using intrinsic properties such as term frequencies, co-occurrences, and sentence structures. Such visualizations lack conceptual overviews incorporating domain-relevant knowledge, needed when examining documents such as research articles or technical reports. To address this shortcoming, we present ConceptScope, a technique that utilizes a domain ontology to represent the conceptual relationships in a document in the form of a Bubble Treemap visualization. Multiple coordinated views of document structure and concept hierarchy with text overviews further aid document analysis. ConceptScope facilitates exploration and comparison of single and multiple documents respectively. We demonstrate ConceptScope by visualizing research articles and transcripts of technical presentations in computer science. In a comparative study with DocuBurst, a popular document visualization tool, ConceptScope was found to be more informative in exploring and comparing domain-specific documents, but less so when it came to documents that spanned multiple disciplines. | false | false | [
"Xiaoyu Zhang",
"Senthil K. Chandrasegaran",
"Kwan-Liu Ma"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2003.05108v2",
"icon": "paper"
}
] |
CHI | 2,021 | Data Animator: Authoring Expressive Animated Data Graphics | 10.1145/3411764.3445747 | Animation helps viewers follow transitions in data graphics. When authoring animations that incorporate data, designers must carefully coordinate the behaviors of visual objects such as entering, exiting, merging and splitting, and specify the temporal rhythms of transition through staging and staggering. We present Data Animator, a system for authoring animated data graphics without programming. Data Animator leverages the Data Illustrator framework to analyze and match objects between two static visualizations, and generates automated transitions by default. Designers have the flexibility to interpret and adjust the matching results through a visual interface. Data Animator also supports the division of a complex animation into stages through hierarchical keyframes, and uses data attributes to stagger the start time and vary the speed of animating objects through a novel timeline interface. We validate Data Animator’s expressiveness via a gallery of examples, and evaluate its usability in a re-creation study with designers. | false | false | [
"John R. Thompson 0002",
"Zhicheng Liu 0001",
"John T. Stasko"
] | [] | [] | [] |
CHI | 2,021 | Data Prophecy: Exploring the Effects of Belief Elicitation in Visual Analytics | 10.1145/3411764.3445798 | Interactive visualizations are widely used in exploratory data analysis, but existing systems provide limited support for confirmatory analysis. We introduce PredictMe, a tool for belief-driven visual analysis, enabling users to draw and test their beliefs against data, as an alternative to data-driven exploration. PredictMe combines belief elicitation with traditional visualization interactions to support mixed analysis styles. In a comparative study, we investigated how these affordances impact participants’ cognition. Results show that PredictMe prompts participants to incorporate their working knowledge more frequently in queries. Participants were more likely to attend to discrepancies between their mental models and the data. However, those same participants were also less likely to engage in interactions associated with exploration, and ultimately inspected fewer visualizations and made fewer discoveries. The results suggest that belief elicitation may moderate exploratory behaviors, instead nudging users to be more deliberate in their analysis. We discuss the implications for visualization design. | false | false | [
"Ratanond Koonchanok",
"Parul Baser",
"Abhinav Sikharam",
"Nirmal Kumar Raveendranath",
"Khairi Reda"
] | [] | [] | [] |
CHI | 2,021 | Design and Analysis of Intelligent Text Entry Systems with Function Structure Models and Envelope Analysis | 10.1145/3411764.3445566 | Designing intelligent interactive text entry systems often relies on factors that are difficult to estimate or assess using traditional HCI design and evaluation methods. We introduce a complementary approach by adapting function structure models from engineering design. We extend their use by extracting controllable and uncontrollable parameters from function structure models and visualizing their impact using envelope analysis. Function structure models allow designers to understand a system in terms of its functions and flows between functions and decouple functions from function carriers. Envelope analysis allows the designer to further study how parameters affect variables of interest, for example, accuracy, keystroke savings and other dependent variables. We provide examples of function structure models and illustrate a complete envelope analysis by investigating a parameterized function structure model of predictive text entry. We discuss the implications of this design approach for both text entry system design and for critique of system contributions. | false | false | [
"Per Ola Kristensson",
"Thomas Müllners"
] | [] | [] | [] |
CHI | 2,021 | Designing CAST: A Computer-Assisted Shadowing Trainer for Self-Regulated Foreign Language Listening Practice | 10.1145/3411764.3445190 | Shadowing, i.e., listening to recorded native speech and simultaneously vocalizing the words, is a popular language-learning technique that is known to improve listening skills. However, despite strong evidence for its efficacy as a listening exercise, existing shadowing systems do not adequately support listening-focused practice, especially in self-regulated learning environments with no external feedback. To bridge this gap, we introduce Computer-Assisted Shadowing Trainer (CAST), a shadowing system that makes self-regulation easy and effective through four novel design elements — (i) in-the-moment highlights for tracking and visualizing progress, (ii) contextual blurring for inducing self-reflection on misheard words, (iii) self-listening comparators for post-practice self-evaluation, and (iv) adjustable pause-handles for self-paced practice. We base CAST on a formative user study (N=15) that provides fresh empirical grounds on the needs and challenges of shadowers. We validate our design through a summative evaluation (N=12) that shows learners can successfully self-regulate their shadowing practice with CAST while retaining focus on listening. | false | false | [
"Mohi Reza",
"Dongwook Yoon"
] | [] | [] | [] |
CHI | 2,021 | Digital Transformations of Classrooms in Virtual Reality | 10.1145/3411764.3445596 | With rapid developments in consumer-level head-mounted displays and computer graphics, immersive VR has the potential to take online and remote learning closer to real-world settings. However, the effects of such digital transformations on learners, particularly for VR, have not been evaluated in depth. This work investigates the interaction-related effects of sitting positions of learners, visualization styles of peer-learners and teachers, and hand-raising behaviors of virtual peer-learners on learners in an immersive VR classroom, using eye tracking data. Our results indicate that learners sitting in the back of the virtual classroom may have difficulties extracting information. Additionally, we find indications that learners engage with lectures more efficiently if virtual avatars are visualized with realistic styles. Lastly, we find different eye movement behaviors towards different performance levels of virtual peer-learners, which should be investigated further. Our findings present an important baseline for design decisions for VR classrooms. | false | false | [
"Hong Gao 0008",
"Efe Bozkir",
"Lisa Hasenbein",
"Jens-Uwe Hahn",
"Richard Göllner",
"Enkelejda Kasneci"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2101.09576v2",
"icon": "paper"
}
] |
CHI | 2,021 | Does Interaction Improve Bayesian Reasoning with Visualization? | 10.1145/3411764.3445176 | Interaction enables users to navigate large amounts of data effectively, supports cognitive processing, and increases data representation methods. However, there have been few attempts to empirically demonstrate whether adding interaction to a static visualization improves its function beyond popular beliefs. In this paper, we address this gap. We use a classic Bayesian reasoning task as a testbed for evaluating whether allowing users to interact with a static visualization can improve their reasoning. Through two crowdsourced studies, we show that adding interaction to a static Bayesian reasoning visualization does not improve participants’ accuracy on a Bayesian reasoning task. In some cases, it can significantly detract from it. Moreover, we demonstrate that underlying visualization design modulates performance and that people with high versus low spatial ability respond differently to different interaction techniques and underlying base visualizations. Our work suggests that interaction is not as unambiguously good as we often believe; a well designed static visualization can be as, if not more, effective than an interactive one. | false | false | [
"Abigail Mosca",
"Alvitta Ottley",
"Remco Chang"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2103.01701v2",
"icon": "paper"
}
] |
CHI | 2,021 | Effect of Information Presentation on Fairness Perceptions of Machine Learning Predictors | 10.1145/3411764.3445365 | The uptake of artificial intelligence-based applications raises concerns about the fairness and transparency of AI behaviour. Consequently, the Computer Science community calls for the involvement of the general public in the design and evaluation of AI systems. Assessing the fairness of individual predictors is an essential step in the development of equitable algorithms. In this study, we evaluate the effect of two common visualisation techniques (text-based and scatterplot) and the display of the outcome information (i.e., ground-truth) on the perceived fairness of predictors. Our results from an online crowdsourcing study (N = 80) show that the chosen visualisation technique significantly alters people’s fairness perception and that the presented scenario, as well as the participant’s gender and past education, influence perceived fairness. Based on these results we draw recommendations for future work that seeks to involve non-experts in AI fairness evaluations. | false | false | [
"Niels van Berkel",
"Jorge Gonçalves 0001",
"Daniel Russo 0002",
"Simo Hosio",
"Mikael B. Skov"
] | [] | [] | [] |
CHI | 2,021 | Effects of Semantic Segmentation Visualization on Trust, Situation Awareness, and Cognitive Load in Highly Automated Vehicles | 10.1145/3411764.3445351 | Autonomous vehicles could improve mobility, safety, and inclusion in traffic. While this technology seems within reach, its successful introduction depends on the intended user’s acceptance. A substantial factor for this acceptance is trust in the autonomous vehicle’s capabilities. Visualizing internal information processed by an autonomous vehicle could calibrate this trust by enabling the perception of the vehicle’s detection capabilities (and its failures) while only inducing a low cognitive load. Additionally, the simultaneously raised situation awareness could benefit potential take-overs. We report the results of two comparative online studies on visualizing semantic segmentation information for the human user of autonomous vehicles. Effects on trust, cognitive load, and situation awareness were measured using a simulation (N=32) and state-of-the-art panoptic segmentation on a pre-recorded real-world video (N=41). Results show that the visualization using Augmented Reality increases situation awareness while remaining low cognitive load. | false | false | [
"Mark Colley",
"Benjamin Eder",
"Jan Ole Rixen",
"Enrico Rukzio"
] | [] | [] | [] |
CHI | 2,021 | Falx: Synthesis-Powered Visualization Authoring | 10.1145/3411764.3445249 | Modern visualization tools aim to allow data analysts to easily create exploratory visualizations. When the input data layout conforms to the visualization design, users can easily specify visualizations by mapping data columns to visual channels of the design. However, when there is a mismatch between data layout and the design, users need to spend significant effort on data transformation. We propose Falx, a synthesis-powered visualization tool that allows users to specify visualizations in a similarly simple way but without needing to worry about data layout. In Falx, users specify visualizations using examples of how concrete values in the input are mapped to visual channels, and Falx automatically infers the visualization specification and transforms the data to match the design. In a study with 33 data analysts on four visualization tasks involving data transformation, we found that users can effectively adopt Falx to create visualizations they otherwise cannot implement. | false | false | [
"Chenglong Wang",
"Yu Feng 0001",
"Rastislav Bodík",
"Isil Dillig",
"Alvin Cheung",
"Amy J. Ko"
] | [
"BP"
] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2102.01024v1",
"icon": "paper"
}
] |
CHI | 2,021 | FashionQ: An AI-Driven Creativity Support Tool for Facilitating Ideation in Fashion Design | 10.1145/3411764.3445093 | Recent research on creativity support tools (CST) adopts artificial intelligence (AI) that leverages big data and computational capabilities to facilitate creative work. Our work aims to articulate the role of AI in supporting creativity with a case study of an AI-based CST tool in fashion design based on theoretical groundings. We developed AI models by externalizing three cognitive operations (extending, constraining, and blending) that are associated with divergent and convergent thinking. We present FashionQ, an AI-based CST that has three interactive visualization tools (StyleQ, TrendQ, and MergeQ). Through interviews and a user study with 20 fashion design professionals (10 participants for the interviews and 10 for the user study), we demonstrate the effectiveness of FashionQ on facilitating divergent and convergent thinking and identify opportunities and challenges of incorporating AI in the ideation process. Our findings highlight the role and use of AI in each cognitive operation based on professionals’ expertise and suggest future implications of AI-based CST development. | false | false | [
"Youngseung Jeon",
"Seungwan Jin",
"Patrick C. Shih",
"Kyungsik Han"
] | [] | [] | [] |
CHI | 2,021 | Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop | 10.1145/3411764.3445775 | AutoML systems can speed up routine data science work and make machine learning available to those without expertise in statistics and computer science. These systems have gained traction in enterprise settings where pools of skilled data workers are limited. In this study, we conduct interviews with 29 individuals from organizations of different sizes to characterize how they currently use, or intend to use, AutoML systems in their data science work. Our investigation also captures how data visualization is used in conjunction with AutoML systems. Our findings identify three usage scenarios for AutoML that resulted in a framework summarizing the level of automation desired by data workers with different levels of expertise. We surfaced the tension between speed and human oversight and found that data visualization can do a poor job balancing the two. Our findings have implications for the design and implementation of human-in-the-loop visual analytics approaches. | false | false | [
"Anamaria Crisan",
"Brittany Fiore-Gartland"
] | [
"HM"
] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2101.04296v1",
"icon": "paper"
}
] |
CHI | 2,021 | From Detectables to Inspectables: Understanding Qualitative Analysis of Audiovisual Data | 10.1145/3411764.3445458 | Audiovisual recordings of user studies and interviews provide important data in qualitative HCI research. Even when a textual transcription is available, researchers frequently turn to these recordings due to their rich information content. However, the temporal, unstructured nature of audiovisual recordings makes them less efficient to work with than text. Through interviews and a survey, we explored how HCI researchers work with audiovisual recordings. We investigated researchers’ transcription and annotation practice, their overall analysis workflow, and the prevalence of direct analysis of audiovisual recordings. We found that a key task was locating and analyzing inspectables, interesting segments in recordings. Since locating inspectables can be time consuming, participants look for detectables, visual or auditory cues that indicate the presence of an inspectable. Based on our findings, we discuss the potential for automation in locating detectables in qualitative audiovisual analysis. | false | false | [
"Krishna Subramanian 0002",
"Johannes Maas",
"Jan O. Borchers",
"James D. Hollan"
] | [
"HM"
] | [] | [] |
CHI | 2,021 | GestureMap: Supporting Visual Analytics and Quantitative Analysis of Motion Elicitation Data by Learning 2D Embeddings | 10.1145/3411764.3445765 | This paper presents GestureMap, a visual analytics tool for gesture elicitation which directly visualises the space of gestures. Concretely, a Variational Autoencoder embeds gestures recorded as 3D skeletons on an interactive 2D map. GestureMap further integrates three computational capabilities to connect exploration to quantitative measures: Leveraging DTW Barycenter Averaging (DBA), we compute average gestures to 1) represent gesture groups at a glance; 2) compute a new consensus measure (variance around average gesture); and 3) cluster gestures with k-means. We evaluate GestureMap and its concepts with eight experts and an in-depth analysis of published data. Our findings show how GestureMap facilitates exploring large datasets and helps researchers to gain a visual understanding of elicited gesture spaces. It further opens new directions, such as comparing elicitations across studies. We discuss implications for elicitation studies and research, and opportunities to extend our approach to additional tasks in gesture elicitation. | false | false | [
"Hai Dang",
"Daniel Buschek"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2103.00912v1",
"icon": "paper"
}
] |
CHI | 2,021 | Grand Challenges in Immersive Analytics | 10.1145/3411764.3446866 | Immersive Analytics is a quickly evolving field that unites several areas such as visualisation, immersive environments, and human-computer interaction to support human data analysis with emerging technologies. This research has thrived over the past years with multiple workshops, seminars, and a growing body of publications, spanning several conferences. Given the rapid advancement of interaction technologies and novel application domains, this paper aims toward a broader research agenda to enable widespread adoption. We present 17 key research challenges developed over multiple sessions by a diverse group of 24 international experts, initiated from a virtual scientific workshop at ACM CHI 2020. These challenges aim to coordinate future work by providing a systematic roadmap of current directions and impending hurdles to facilitate productive and effective applications for Immersive Analytics. | false | false | [
"Barrett Ens",
"Benjamin Bach",
"Maxime Cordeil",
"Ulrich Engelke",
"Marcos Serrano",
"Wesley Willett",
"Arnaud Prouzeau",
"Christoph Anthes",
"Wolfgang Büschel",
"Cody Dunne",
"Tim Dwyer",
"Jens Grubert",
"Jason H. Haga",
"Nurit Kirshenbaum",
"Dylan Kobayashi",
"Tica Lin",
"Monsurat Olaosebikan",
"Fabian Pointecker",
"David Saffo",
"Nazmus Saquib",
"Dieter Schmalstieg",
"Danielle Albers Szafir",
"Matt Whitlock",
"Yalong Yang 0001"
] | [] | [] | [] |
CHI | 2,021 | Haptic and Visual Comprehension of a 2D Graph Layout Through Physicalisation | 10.1145/3411764.3445704 | Data physicalisations afford people the ability to directly interact with data using their hands, potentially achieving a more comprehensive understanding of a dataset. Due to their complex nature, the representation of graphs and networks could benefit from physicalisation, bringing the dataset from the digital world into the physical one. However, no empirical work exists investigating the effects physicalisations have upon comprehension as they relate to graph representations. In this work, we present initial design considerations for graph physicalisations, as well as an empirical study investigating differences in comprehension between virtual and physical representations. We found that participants perceived themselves as being more accurate via touch and sight (visual-haptic) than the graphical-only modality, and perceived a triangle count task as less difficult in visual-haptic than in the graphical-only modality. Additionally, we found that participants significantly preferred interacting with visual-haptic over other conditions, despite no significant effect on task time or error. | false | false | [
"Adam Drogemuller",
"Andrew Cunningham",
"James A. Walsh",
"James Baumeister",
"Ross T. Smith",
"Bruce H. Thomas"
] | [] | [] | [] |
CHI | 2,021 | IGScript: An Interaction Grammar for Scientific Data Presentation | 10.1145/3411764.3445535 | Most of the existing scientific visualizations toward interpretive grammar aim to enhance customizability in either the computation stage or the rendering stage or both, while few approaches focus on the data presentation stage. Besides, most of these approaches leverage the existing components from the general-purpose programming languages (GPLs) instead of developing a standalone compiler, which pose a great challenge about learning curves for the domain experts who have limited knowledge about programming. In this paper, we propose IGScript, a novel script-based interaction grammar tool, to help build scientific data presentation animations for communication. We design a dual-space interface and a compiler which converts natural language-like grammar statements or scripts into a data story animation to make an interactive customization on script-driven data presentations, and then develop a code generator (decompiler) to translate the interactive data exploration animations back into script codes to achieve statement parameters. IGScript makes the presentation animations editable, e.g., it allows to cut, copy, paste, append, or even delete some animation clips. We demonstrate the usability, customizability, and flexibility of IGScript by a user study, four case studies conducted by using four types of commonly-used scientific data, and performance evaluations. | false | false | [
"Richen Liu",
"Min Gao",
"Shunlong Ye",
"Jiang Zhang 0002"
] | [] | [] | [] |
CHI | 2,021 | Integrated Visualization Editing via Parameterized Declarative Templates | 10.1145/3411764.3445356 | Interfaces for creating visualizations typically embrace one of several common forms. Textual specification enables fine-grained control, shelf building facilitates rapid exploration, while chart choosing promotes immediacy and simplicity. Ideally these approaches could be unified to integrate the user- and usage-dependent benefits found in each modality, yet these forms remain distinct. We propose parameterized declarative templates, a simple abstraction mechanism over JSON-based visualization grammars, as a foundation for multimodal visualization editors. We demonstrate how templates can facilitate organization and reuse by factoring the more than 160 charts that constitute Vega-Lite’s example gallery into approximately 40 templates. We exemplify the pliability of abstracting over charting grammars by implementing—as a template—the functionality of the shelf builder Polestar (a simulacra of Tableau) and a set of templates that emulate the Google Sheets chart chooser. We show how templates support multimodal visualization editing by implementing a prototype and evaluating it through an approachability study. | false | false | [
"Andrew M. McNutt",
"Ravi Chugh"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2101.07902v2",
"icon": "paper"
}
] |
CHI | 2,021 | Interpreting the Effect of Embellishment on Chart Visualizations | 10.1145/3411764.3445739 | Infographics range from minimalism that aims to convey the raw data to elaborately decorated, or embellished, graphics that aim to engage readers by telling a story. Several studies have shown evidence to negative, but also positive, effects on embellishments. We conducted a set of experiments to gauge more precisely how embellishments affect how people relate to infographics and make sense of the conveyed story. By analyzing questionnaires, interviews, and eye-tracking data simplified by bundling, we show that, within bounds, embellishments have a positive effect on how users get engaged in understanding an infographic, with very limited downside. To our knowledge, our work is the first that fuses the aforementioned three information sources to understand infographics. Our findings can help to design more fine-grained studies to quantify the effects of embellishments and also to design infographics that effectively use the embellishments’ positive aspects identified. I think the contribution does not appear well in the abstract. It’s not just that the visual embellishments are positive. We show a methodology that allows us to see what these effects are (in addition to engagement, memorization and recall) at several levels (scales, interviews, eye tracking) which are therefore physiological and emotional. We could include this idea in the abstract? | false | false | [
"Tiffany Andry",
"Christophe Hurter",
"François Lambotte",
"Pierre Fastrez",
"Alexandru C. Telea"
] | [] | [] | [] |
CHI | 2,021 | Investigating the Impact of Real-World Environments on the Perception of 2D Visualizations in Augmented Reality | 10.1145/3411764.3445330 | In this work we report on two comprehensive user studies investigating the perception of Augmented Reality (AR) visualizations influenced by real-world backgrounds. Since AR is an emerging technology, it is important to also consider productive use cases, which is why we chose an exemplary and challenging industry 4.0 environment. Our basic perceptual research focuses on both the visual complexity of backgrounds as well as the influence of a secondary task. In contrast to our expectation, data of our 34 study participants indicate that the background has far less influence on the perception of AR visualizations. Moreover, we observed a mismatch between measured and subjectively reported performance. We discuss the importance of the background and recommendations for visual real-world augmentations. Overall, our results suggest that AR can be used in many visually challenging environments without losing the ability to productively work with the visualizations shown. | false | false | [
"Marc Satkowski",
"Raimund Dachselt"
] | [] | [] | [] |
CHI | 2,021 | It's a Wrap: Toroidal Wrapping of Network Visualisations Supports Cluster Understanding Tasks | 10.1145/3411764.3445439 | We explore network visualisation on a two-dimensional torus topology that continuously wraps when the viewport is panned. That is, links may be “wrapped” across the boundary, allowing additional spreading of node positions to reduce visual clutter. Recent work has investigated such pannable wrapped visualisations, finding them not worse than unwrapped drawings for small networks for path-following tasks. However, they did not evaluate larger networks nor did they consider whether torus-based layout might also better display high-level network structure like clusters. We offer two algorithms for improving toroidal layout that is completely autonomous and automatic panning of the viewport to minimiswe wrapping links. The resulting layouts afford fewer crossings, less stress, and greater cluster separation. In a study of 32 participants comparing performance in cluster understanding tasks, we find that toroidal visualisation offers significant benefits over standard unwrapped visualisation in terms of improvement in error by 62.7% and time by 32.3%. | false | false | [
"Kun-Ting Chen",
"Tim Dwyer",
"Benjamin Bach",
"Kim Marriott"
] | [] | [] | [] |
CHI | 2,021 | LaserFactory: A Laser Cutter-based Electromechanical Assembly and Fabrication Platform to Make Functional Devices & Robots | 10.1145/3411764.3445692 | LaserFactory is an integrated fabrication process that augments a commercially available fabrication machine to support the manufacture of fully functioning devices without human intervention. In addition to creating 2D and 3D mechanical structures, LaserFactory creates conductive circuit traces with arbitrary geometries, picks-and-places electronic and electromechanical components, and solders them in place. To enable this functionality, we make four contributions. First, we build a hardware add-on to the laser cutter head that can deposit silver circuit traces and assemble components. Second, we develop a new method to cure dispensed silver using a CO2 laser. Third, we build a motion-based signaling method that allows our system to be readily integrated with commercial laser cutters. Finally, we provide a design and visualization tool for making functional devices with LaserFactory. Having described the LaserFactory system, we demonstrate how it is used to fabricate devices such as a fully functioning quadcopter and a sensor-equipped wristband. Our evaluation shows that LaserFactory can assemble a variety of differently sized components (up to 65g), that these can be connected by narrow traces (down to 0.75mm) that become highly conductive after laser soldering (3.2Ω/m), and that our acceleration-based sensing scheme works reliably (to 99.5% accuracy). | false | false | [
"Martin Nisser",
"Christina Chen Liao",
"Yuchen Chai",
"Aradhana Adhikari",
"Steve Hodges 0001",
"Stefanie Müller 0001"
] | [] | [] | [] |
CHI | 2,021 | Little Road Driving HUD: Heads-Up Display Complexity Influences Drivers' Perceptions of Automated Vehicles | 10.1145/3411764.3445575 | Modern vehicles are using AI and increasingly sophisticated sensor suites to improve Advanced Driving Assistance Systems (ADAS) and support automated driving capabilities. Heads-Up-Displays (HUDs) provide an opportunity to visually inform drivers about vehicle perception and interpretation of the driving environment. One approach to HUD design may be to reveal to drivers the vehicle’s full contextual understanding, though it is not clear if the benefits of additional information outweigh the drawbacks of added complexity, or if this balance holds across drivers. We designed and tested an Augmented Reality (AR) HUD in an online study (N = 298), focusing on the influence of HUD visualizations on drivers’ situation awareness and perceptions. Participants viewed two driving scenes with one of three HUD conditions. Results were nuanced: situation awareness declined with increasing driving context complexity, and contrary to expectation, also declined with the presence of a HUD compared to no HUD. Significant differences were found by varying HUD complexity, which led us to explore different characterizations of complexity, including counts of scene items, item categories, and illuminated pixels. Our analysis finds that driving style interacts with driving context and HUD complexity, warranting further study. | false | false | [
"Rebecca Currano",
"So Yeon Park",
"Dylan James Moore",
"Kent Lyons",
"David Sirkin"
] | [] | [] | [] |
CHI | 2,021 | Locomotion Vault: the Extra Mile in Analyzing VR Locomotion Techniques | 10.1145/3411764.3445319 | Numerous techniques have been proposed for locomotion in virtual reality (VR). Several taxonomies consider a large number of attributes (e.g., hardware, accessibility) to characterize these techniques. However, finding the appropriate locomotion technique (LT) and identifying gaps for future designs in the high-dimensional space of attributes can be quite challenging. To aid analysis and innovation, we devised Locomotion Vault (https://locomotionvault.github.io/), a database and visualization of over 100 LTs from academia and industry. We propose similarity between LTs as a metric to aid navigation and visualization. We show that similarity based on attribute values correlates with expert similarity assessments (a method that does not scale). Our analysis also highlights an inherent trade-off between simulation sickness and accessibility across LTs. As such, Locomotion Vault shows to be a tool that unifies information on LTs and enables their standardization and large-scale comparison to help understand the space of possibilities in VR locomotion. | false | false | [
"Massimiliano Di Luca",
"Hasti Seifi",
"Simon Egan",
"Mar González-Franco"
] | [] | [] | [] |
CHI | 2,021 | Mapping the Landscape of COVID-19 Crisis Visualizations | 10.1145/3411764.3445381 | In response to COVID-19, a vast number of visualizations have been created to communicate information to the public. Information exposure in a public health crisis can impact people’s attitudes towards and responses to the crisis and risks, and ultimately the trajectory of a pandemic. As such, there is a need for work that documents, organizes, and investigates what COVID-19 visualizations have been presented to the public. We address this gap through an analysis of 668 COVID-19 visualizations. We present our findings through a conceptual framework derived from our analysis, that examines who, (uses) what data, (to communicate) what messages, in what form, under what circumstances in the context of COVID-19 crisis visualizations. We provide a set of factors to be considered within each component of the framework. We conclude with directions for future crisis visualization research. | false | false | [
"Yixuan Zhang 0001",
"Yifan Sun 0002",
"Lace M. K. Padilla",
"Sumit Barua",
"Enrico Bertini",
"Andrea G. Parker"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2101.04743v1",
"icon": "paper"
}
] |
CHI | 2,021 | MARVIS: Combining Mobile Devices and Augmented Reality for Visual Data Analysis | 10.1145/3411764.3445593 | We present Marvis, a conceptual framework that combines mobile devices and head-mounted Augmented Reality (AR) for visual data analysis. We propose novel concepts and techniques addressing visualization-specific challenges. By showing additional 2D and 3D information around and above displays, we extend their limited screen space. AR views between displays as well as linking and brushing are also supported, making relationships between separated visualizations plausible. We introduce the design process and rationale for our techniques. To validate Marvis’ concepts and show their versatility and widespread applicability, we describe six implemented example use cases. Finally, we discuss insights from expert hands-on reviews. As a result, we contribute to a better understanding of how the combination of one or more mobile devices with AR can benefit visual data analysis. By exploring this new type of visualization environment, we hope to provide a foundation and inspiration for future mobile data visualizations. | false | false | [
"Ricardo Langner",
"Marc Satkowski",
"Wolfgang Büschel",
"Raimund Dachselt"
] | [] | [] | [] |
CHI | 2,021 | MIRIA: A Mixed Reality Toolkit for the In-Situ Visualization and Analysis of Spatio-Temporal Interaction Data | 10.1145/3411764.3445651 | In this paper, we present MIRIA, a Mixed Reality Interaction Analysis toolkit designed to support the in-situ visual analysis of user interaction in mixed reality and multi-display environments. So far, there are few options to effectively explore and analyze interaction patterns in such novel computing systems. With MIRIA, we address this gap by supporting the analysis of user movement, spatial interaction, and event data by multiple, co-located users directly in the original environment. Based on our own experiences and an analysis of the typical data, tasks, and visualizations used in existing approaches, we identify requirements for our system. We report on the design and prototypical implementation of MIRIA, which is informed by these requirements and offers various visualizations such as 3D movement trajectories, position heatmaps, and scatterplots. To demonstrate the value of MIRIA for real-world analysis tasks, we conducted expert feedback sessions using several use cases with authentic study data. | false | false | [
"Wolfgang Büschel",
"Anke Lehmann",
"Raimund Dachselt"
] | [] | [] | [] |
CHI | 2,021 | Modeling and Leveraging Analytic Focus During Exploratory Visual Analysis | 10.1145/3411764.3445674 | Visual analytics systems enable highly interactive exploratory data analysis. Across a range of fields, these technologies have been successfully employed to help users learn from complex data. However, these same exploratory visualization techniques make it easy for users to discover spurious findings. This paper proposes new methods to monitor a user’s analytic focus during visual analysis of structured datasets and use it to surface relevant articles that contextualize the visualized findings. Motivated by interactive analyses of electronic health data, this paper introduces a formal model of analytic focus, a computational approach to dynamically update the focus model at the time of user interaction, and a prototype application that leverages this model to surface relevant medical publications to users during visual analysis of a large corpus of medical records. Evaluation results with 24 users show that the modeling approach has high levels of accuracy and is able to surface highly relevant medical abstracts. | false | false | [
"Zhilan Zhou",
"Ximing Wen",
"Yue Wang 0035",
"David Gotz"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2101.08856v1",
"icon": "paper"
}
] |
CHI | 2,021 | mTSeer: Interactive Visual Exploration of Models on Multivariate Time-series Forecast | 10.1145/3411764.3445083 | Time-series forecasting contributes crucial information to industrial and institutional decision-making with multivariate time-series input. Although various models have been developed to facilitate the forecasting process, they make inconsistent forecasts. Thus, it is critical to select the model appropriately. The existing selection methods based on the error measures fail to reveal deep insights into the model’s performance, such as the identification of salient features and the impact of temporal factors (e.g., periods). This paper introduces mTSeer, an interactive system for the exploration, explanation, and evaluation of multivariate time-series forecasting models. Our system integrates a set of algorithms to steer the process, and rich interactions and visualization designs to help interpret the differences between models in both model and instance level. We demonstrate the effectiveness of mTSeer through three case studies with two domain experts on real-world data, qualitative interviews with the two experts, and quantitative evaluation of the three case studies. | false | false | [
"Ke Xu",
"Jun Yuan",
"Yifang Wang 0001",
"Cláudio T. Silva",
"Enrico Bertini"
] | [] | [] | [] |
CHI | 2,021 | NBSearch: Semantic Search and Visual Exploration of Computational Notebooks | 10.1145/3411764.3445048 | Code search is an important and frequent activity for developers using computational notebooks (e.g., Jupyter). The flexibility of notebooks brings challenges for effective code search, where classic search interfaces for traditional software code may be limited. In this paper, we propose, NBSearch, a novel system that supports semantic code search in notebook collections and interactive visual exploration of search results. NBSearch leverages advanced machine learning models to enable natural language search queries and intuitive visualizations to present complicated intra- and inter-notebook relationships in the returned results. We developed NBSearch through an iterative participatory design process with two experts from a large software company. We evaluated the models with a series of experiments and the whole system with a controlled user study. The results indicate the feasibility of our analytical pipeline and the effectiveness of NBSearch to support code search in large notebook collections. | false | false | [
"Xingjun Li",
"Yuanxin Wang",
"Hong Wang",
"Yang Wang",
"Jian Zhao 0010"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2102.01275v1",
"icon": "paper"
}
] |
CHI | 2,021 | PriView- Exploring Visualisations to Support Users' Privacy Awareness | 10.1145/3411764.3445067 | We present PriView, a concept that allows privacy-invasive devices in the users’ vicinity to be visualised. PriView is motivated by an ever-increasing number of sensors in our environments tracking potentially sensitive data (e.g., audio and video). At the same time, users are oftentimes unaware of this, which violates their privacy. Knowledge about potential recording would enable users to avoid accessing such areas or not to disclose certain information. We built two prototypes: a) a mobile application capable of detecting smart devices in the environment using a thermal camera, and b) VR mockups of six scenarios where PriView might be useful (e.g., a rental apartment). In both, we included several types of visualisation. Results of our lab study (N=24) indicate that users prefer simple, permanent indicators while wishing for detailed visualisations on demand. Our exploration is meant to support future designs of privacy visualisations for varying smart environments. | false | false | [
"Sarah Prange",
"Ahmed Shams",
"Robin Piening",
"Yomna Abdelrahman",
"Florian Alt"
] | [] | [] | [] |
CHI | 2,021 | Quantitative Data Visualisation on Virtual Globes | 10.1145/3411764.3445152 | Geographic data visualisation on virtual globes is intuitive and widespread, but has not been thoroughly investigated. We explore two main design factors for quantitative data visualisation on virtual globes: i) commonly used primitives (2D bar, 3D bar, circle) and ii) the orientation of these primitives (tangential, normal, billboarded). We evaluate five distinctive visualisation idioms in a user study with 50 participants. The results show that aligning primitives tangentially on the globe’s surface decreases the accuracy of area-proportional circle visualisations, while the orientation does not have a significant effect on the accuracy of length-proportional bar visualisations. We also find that tangential primitives induce higher perceived mental load than other orientations. Guided by these results we design a novel globe visualisation idiom, Geoburst, that combines a virtual globe and a radial bar chart. A preliminary evaluation reports potential benefits and drawbacks of the Geoburst visualisation. | false | false | [
"Kadek Ananta Satriadi",
"Barrett Ens",
"Tobias Czauderna",
"Maxime Cordeil",
"Bernhard Jenny"
] | [] | [] | [] |
CHI | 2,021 | RCEA-360VR: Real-time, Continuous Emotion Annotation in 360° VR Videos for Collecting Precise Viewport-dependent Ground Truth Labels | 10.1145/3411764.3445487 | Precise emotion ground truth labels for 360° virtual reality (VR) video watching are essential for fine-grained predictions under varying viewing behavior. However, current annotation techniques either rely on post-stimulus discrete self-reports, or real-time, continuous emotion annotations (RCEA) but only for desktop/mobile settings. We present RCEA for 360° VR videos (RCEA-360VR), where we evaluate in a controlled study (N=32) the usability of two peripheral visualization techniques: HaloLight and DotSize. We furthermore develop a method that considers head movements when fusing labels. Using physiological, behavioral, and subjective measures, we show that (1) both techniques do not increase users’ workload, sickness, nor break presence (2) our continuous valence and arousal annotations are consistent with discrete within-VR and original stimuli ratings (3) users exhibit high similarity in viewing behavior, where fused ratings perfectly align with intended labels. Our work contributes usable and effective techniques for collecting fine-grained viewport-dependent emotion labels in 360° VR. | false | false | [
"Tong Xue",
"Abdallah El Ali",
"Tianyi Zhang",
"Gangyi Ding",
"Pablo César"
] | [] | [] | [] |
CHI | 2,021 | Reconfiguration Strategies with Composite Data Physicalizations | 10.1145/3411764.3445746 | Composite data physicalizations allow for the physical reconfiguration of data points, creating new opportunities for interaction and engagement. However, there is a lack of understanding of people’s strategies and behaviors when directly manipulating physical data objects. In this paper, we systematically characterize different reconfiguration strategies using six exemplar physicalizations. We asked 20 participants to reorganize these exemplars with two levels of restriction: changing a single data object versus changing multiple data objects. Our findings show that there were two main reconfiguration strategies used: changes in proximity and changes in atomic orientation. We further characterize these using concrete examples of participant actions in relation to the structure of the physicalizations. We contribute an overview of reconfiguration strategies, which informs the design of future manually reconfigurable and dynamic composite physicalizations. | false | false | [
"Kim Sauvé",
"David Verweij",
"Jason Alexander",
"Steven Houben"
] | [] | [] | [] |
CHI | 2,021 | reVISit: Looking Under the Hood of Interactive Visualization Studies | 10.1145/3411764.3445382 | Quantifying user performance with metrics such as time and accuracy does not show the whole picture when researchers evaluate complex, interactive visualization tools. In such systems, performance is often influenced by different analysis strategies that statistical analysis methods cannot account for. To remedy this lack of nuance, we propose a novel analysis methodology for evaluating complex interactive visualizations at scale. We implement our analysis methods in reVISit, which enables analysts to explore participant interaction performance metrics and responses in the context of users’ analysis strategies. Replays of participant sessions can aid in identifying usability problems during pilot studies and make individual analysis processes salient. To demonstrate the applicability of reVISit to visualization studies, we analyze participant data from two published crowdsourced studies. Our findings show that reVISit can be used to reveal and describe novel interaction patterns, to analyze performance differences between different analysis strategies, and to validate or challenge design decisions. | false | false | [
"Carolina Nobre",
"Dylan Wootton",
"Zach Cutler",
"Lane Harrison",
"Hanspeter Pfister",
"Alexander Lex"
] | [] | [] | [] |
CHI | 2,021 | Soloist: Generating Mixed-Initiative Tutorials from Existing Guitar Instructional Videos Through Audio Processing | 10.1145/3411764.3445162 | Learning musical instruments using online instructional videos has become increasingly prevalent. However, pre-recorded videos lack the instantaneous feedback and personal tailoring that human tutors provide. In addition, existing video navigations are not optimized for instrument learning, making the learning experience encumbered. Guided by our formative interviews with guitar players and prior literature, we designed Soloist, a mixed-initiative learning framework that automatically generates customizable curriculums from off-the-shelf guitar video lessons. Soloist takes raw videos as input and leverages deep-learning based audio processing to extract musical information. This back-end processing is used to provide an interactive visualization to support effective video navigation and real-time feedback on the user's performance, creating a guided learning experience. We demonstrate the capabilities and specific use-cases of Soloist within the domain of learning electric guitar solos using instructional YouTube videos. A remote user study, conducted to gather feedback from guitar players, shows encouraging results as the users unanimously preferred learning with Soloist over unconverted instructional videos. | false | false | [
"Bryan Wang",
"Mengyu Yang",
"Tovi Grossman"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2101.08846v1",
"icon": "paper"
}
] |
CHI | 2,021 | STREAM: Exploring the Combination of Spatially-Aware Tablets with Augmented Reality Head-Mounted Displays for Immersive Analytics | 10.1145/3411764.3445298 | Recent research in the area of immersive analytics demonstrated the utility of head-mounted augmented reality devices for visual data analysis. However, it can be challenging to use the by default supported mid-air gestures to interact with visualizations in augmented reality (e.g. due to limited precision). Touch-based interaction (e.g. via mobile devices) can compensate for these drawbacks, but is limited to two-dimensional input. In this work we present STREAM: Spatially-aware Tablets combined with Augmented Reality Head-Mounted Displays for the multimodal interaction with 3D visualizations. We developed a novel eyes-free interaction concept for the seamless transition between the tablet and the augmented reality environment. A user study reveals that participants appreciated the novel interaction concept, indicating the potential for spatially-aware tablets in augmented reality. Based on our findings, we provide design insights to foster the application of spatially-aware touch devices in augmented reality and research implications indicating areas that need further investigation. | false | false | [
"Sebastian Hubenschmid",
"Johannes Zagermann",
"Simon Butscher",
"Harald Reiterer"
] | [] | [] | [] |
CHI | 2,021 | Tele-Immersive Improv: Effects of Immersive Visualisations on Rehearsing and Performing Theatre Online | 10.1145/3411764.3445310 | Performers acutely need but lack tools to remotely rehearse and create live theatre, particularly due to global restrictions on social interactions during the Covid-19 pandemic. No studies, however, have heretofore examined how remote video-collaboration affects performance. This paper presents the findings of a field study with 16 domain experts over six weeks investigating how tele-immersion affects the rehearsal and performance of improvisational theatre. To conduct the study, an original media server was developed for co-locating remote performers into shared virtual 3D environments which were accessed through popular video conferencing software. The results of this qualitative study indicate that tele-immersive environments uniquely provide performers with a strong sense of co- presence, feelings of physical connection, and an increased ability to enter the social-flow states required for improvisational theatre. Based on our observations, we put forward design recommendations for video collaboration tools tailored to the unique demands of live performance. | false | false | [
"Boyd Branch",
"Christos Efstratiou",
"Piotr Mirowski",
"Kory W. Mathewson",
"Paul Allain"
] | [] | [] | [] |
CHI | 2,021 | The Public Life of Data: Investigating Reactions to Visualizations on Reddit | 10.1145/3411764.3445720 | This research investigates how people engage with data visualizations when commenting on the social platform Reddit. There has been considerable research on collaborative sensemaking with visualizations and the personal relation of people with data. Yet, little is known about how public audiences without specific expertise and shared incentives openly express their thoughts, feelings, and insights in response to data visualizations. Motivated by the extensive social exchange around visualizations in online communities, this research examines characteristics and motivations of people’s reactions to posts featuring visualizations. Following a Grounded Theory approach, we study 475 reactions from the /r/dataisbeautiful community, identify ten distinguishable reaction types, and consider their contribution to the discourse. A follow-up survey with 168 Reddit users clarified their intentions to react. Our results help understand the role of personal perspectives on data and inform future interfaces that integrate audience reactions into visualizations to foster a public discourse about data. | false | false | [
"Tobias Kauer",
"Marian Dörk",
"Arran L. Ridley",
"Benjamin Bach"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2103.08525v2",
"icon": "paper"
}
] |
CHI | 2,021 | Towards an Understanding of Situated AR Visualization for Basketball Free-Throw Training | 10.1145/3411764.3445649 | We present an observational study to compare co-located and situated real-time visualizations in basketball free-throw training. Our goal is to understand the advantages and concerns of applying immersive visualization to real-world skill-based sports training and to provide insights for designing AR sports training systems. We design both a situated 3D visualization on a head-mounted display and a 2D visualization on a co-located display to provide immediate visual feedback on a player’s shot performance. Using a within-subject study design with experienced basketball shooters, we characterize user goals, report on qualitative training experiences, and compare the quantitative training results. Our results show that real-time visual feedback helps athletes refine subsequent shots. Shooters in our study achieve greater angle consistency with our visual feedback. Furthermore, AR visualization promotes an increased focus on body form in athletes. Finally, we present suggestions for the design of future sports AR studies. | false | false | [
"Tica Lin",
"Rishi Singh",
"Yalong Yang 0001",
"Carolina Nobre",
"Johanna Beyer",
"Maurice A. Smith",
"Hanspeter Pfister"
] | [
"HM"
] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2104.04118v2",
"icon": "paper"
}
] |
CHI | 2,021 | Understanding Data Accessibility for People with Intellectual and Developmental Disabilities | 10.1145/3411764.3445743 | Using visualization requires people to read abstract visual imagery, estimate statistics, and retain information. However, people with Intellectual and Developmental Disabilities (IDD) often process information differently, which may complicate connecting abstract visual information to real-world quantities. This population has traditionally been excluded from visualization design, and often has limited access to data related to their well being. We explore how visualizations may better serve this population. We identify three visualization design elements that may improve data accessibility: chart type, chart embellishment, and data continuity. We evaluate these elements with populations both with and without IDD, measuring accuracy and efficiency in a web-based online experiment with time series and proportion data. Our study identifies performance patterns and subjective preferences for people with IDD when reading common visualizations. These findings suggest possible solutions that may break the cognitive barriers caused by conventional design guidelines. | false | false | [
"Keke Wu",
"Emma Petersen",
"Tahmina Ahmad",
"David Burlinson",
"Shea Tanis",
"Danielle Albers Szafir"
] | [
"BP"
] | [] | [] |
CHI | 2,021 | Understanding Narrative Linearity for Telling Expressive Time-Oriented Stories | 10.1145/3411764.3445344 | Creating expressive narrative visualization often requires choosing a well-planned narrative order that invites the audience in. The narrative can either follow the linear order of story events (chronology), or deviate from linearity (anachronies). While evidence exists that anachronies in novels and films can enhance story expressiveness, little is known about how they can be incorporated into narrative visualization. To bridge this gap, this work introduces the idea of narrative linearity to visualization and investigates how different narrative orders affect the expressiveness of time-oriented stories. First, we conducted preliminary interviews with seven experts to clarify the motivations and challenges of manipulating narrative linearity in time-oriented stories. Then, we analyzed a corpus of 80 time-oriented stories and identified six most salient patterns of narrative orders. Next, we conducted a crowdsourcing study with 221 participants. Results indicated that anachronies have the potential to make time-oriented stories more expressive without hindering comprehensibility. | false | false | [
"Xingyu Lan",
"Xinyue Xu",
"Nan Cao"
] | [] | [] | [] |
CHI | 2,021 | Understanding Trigger-Action Programs Through Novel Visualizations of Program Differences | 10.1145/3411764.3445567 | Trigger-action programming (if-this-then-that rules) empowers non-technical users to automate services and smart devices. As a user’s set of trigger-action programs evolves, the user must reason about behavior differences between similar programs, such as between an original program and several modification candidates, to select programs that meet their goals. To facilitate this process, we co-designed user interfaces and underlying algorithms to highlight differences between trigger-action programs. Our novel approaches leverage formal methods to efficiently identify and visualize differences in program outcomes or abstract properties. We also implemented a traditional interface that shows only syntax differences in the rules themselves. In a between-subjects online experiment with 107 participants, the novel interfaces better enabled participants to select trigger-action programs matching intended goals in complex, yet realistic, situations that proved very difficult when using traditional interfaces showing syntax differences. | false | false | [
"Valerie Zhao",
"Lefan Zhang",
"Bo Wang",
"Michael L. Littman",
"Shan Lu 0001",
"Blase Ur"
] | [
"HM"
] | [] | [] |
CHI | 2,021 | Viral Visualizations: How Coronavirus Skeptics Use Orthodox Data Practices to Promote Unorthodox Science Online | 10.1145/3411764.3445211 | Controversial understandings of the coronavirus pandemic have turned data visualizations into a battleground. Defying public health officials, coronavirus skeptics on US social media spent much of 2020 creating data visualizations showing that the government’s pandemic response was excessive and that the crisis was over. This paper investigates how pandemic visualizations circulated on social media, and shows that people who mistrust the scientific establishment often deploy the same rhetorics of data-driven decision-making used by experts, but to advocate for radical policy changes. Using a quantitative analysis of how visualizations spread on Twitter and an ethnographic approach to analyzing conversations about COVID data on Facebook, we document an epistemological gap that leads pro- and anti-mask groups to draw drastically different inferences from similar data. Ultimately, we argue that the deployment of COVID data visualizations reflect a deeper sociopolitical rift regarding the place of science in public life. | false | false | [
"Crystal Lee",
"Tanya Yang",
"Gabrielle D. Inchoco",
"Graham M. Jones",
"Arvind Satyanarayan"
] | [
"HM"
] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2101.07993v1",
"icon": "paper"
}
] |
CHI | 2,021 | Vis Ex Machina: An Analysis of Trust in Human versus Algorithmically Generated Visualization Recommendations | 10.1145/3411764.3445195 | More visualization systems are simplifying the data analysis process by automatically suggesting relevant visualizations. However, little work has been done to understand if users trust these automated recommendations. In this paper, we present the results of a crowd-sourced study exploring preferences and perceived quality of recommendations that have been positioned as either human-curated or algorithmically generated. We observe that while participants initially prefer human recommenders, their actions suggest an indifference for recommendation source when evaluating visualization recommendations. The relevance of presented information (e.g., the presence of certain data fields) was the most critical factor, followed by a belief in the recommender’s ability to create accurate visualizations. Our findings suggest a general indifference towards the provenance of recommendations, and point to idiosyncratic definitions of visualization quality and trustworthiness that may not be captured by simple measures. We suggest that recommendation systems should be tailored to the information-foraging strategies of specific users. | false | false | [
"Rachael Zehrung",
"Astha Singhal",
"Michael Correll",
"Leilani Battle"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2101.04251v2",
"icon": "paper"
}
] |
CHI | 2,021 | Visualizing Examples of Deep Neural Networks at Scale | 10.1145/3411764.3445654 | Many programmers want to use deep learning due to its superior accuracy in many challenging domains. Yet our formative study with ten programmers indicated that, when constructing their own deep neural networks (DNNs), they often had a difficult time choosing appropriate model structures and hyperparameter values. This paper presents ExampleNet—a novel interactive visualization system for exploring common and uncommon design choices in a large collection of open-source DNN projects. ExampleNet provides a holistic view of the distribution over model structures and hyperparameter settings in the corpus of DNNs, so users can easily filter the corpus down to projects tackling similar tasks and compare design choices made by others. We evaluated ExampleNet in a within-subjects study with sixteen participants. Compared with the control condition (i.e., online search), participants using ExampleNet were able to inspect more online examples, make more data-driven design decisions, and make fewer design mistakes. | false | false | [
"Litao Yan",
"Elena L. Glassman",
"Tianyi Zhang 0001"
] | [
"HM"
] | [] | [] |
CHI | 2,021 | What Players Want: Information Needs of Players on Post-Game Visualizations | 10.1145/3411764.3445174 | With the rise of competitive online gaming and esports, players’ ability to review, reflect upon, and improve their in-game performance has become important. Post-play visualizations are key for such improvements. Despite the increased interest in visualizations of gameplay, research specifically informing the design of player-centric visualizations is currently limited. As with all visualizations, their design should, however, be guided by a thorough understanding of the goals to be achieved and which information is important and why. This paper reports on a mixed-methods study exploring the information demands posed by players on post-play visualizations and the goals they pursue with such visualizations. We focused on three genres that enjoy great popularity within the competitive gaming scene. Our results provide useful guideposts on which data to focus on by offering an overview of the relevance of different in-game metrics across genres. Lastly, we outline high-level implications for the design of post-play visualizations. | false | false | [
"Günter Wallner",
"Marnix van Wijland",
"Regina Bernhaupt",
"Simone Kriglstein"
] | [] | [] | [] |
VAST | 2,020 | A Visual Analytics Approach for Ecosystem Dynamics based on Empirical Dynamic Modeling | 10.1109/TVCG.2020.3028956 | An important approach for scientific inquiry across many disciplines involves using observational time series data to understand the relationships between key variables to gain mechanistic insights into the underlying rules that govern the given system. In real systems, such as those found in ecology, the relationships between time series variables are generally not static; instead, these relationships are dynamical and change in a nonlinear or state-dependent manner. To further understand such systems, we investigate integrating methods that appropriately characterize these dynamics (i.e., methods that measure interactions as they change with time-varying system states) with visualization techniques that can help analyze the behavior of the system. Here, we focus on empirical dynamic modeling (EDM) as a state-of-the-art method that specifically identifies causal variables and measures changing state-dependent relationships between time series variables. Instead of using approaches centered on parametric equations, EDM is an equation-free approach that studies systems based on their dynamic attractors. We propose a visual analytics system to support the identification and mechanistic interpretation of system states using an EDM-constructed dynamic graph. This work, as detailed in four analysis tasks and demonstrated with a GUI, provides a novel synthesis of EDM and visualization techniques such as brush-link visualization and visual summarization to interpret dynamic graphs representing ecosystem dynamics. We applied our proposed system to ecological simulation data and real data from a marine mesocosm study as two key use cases. Our case studies show that our visual analytics tools support the identification and interpretation of the system state by the user, and enable us to discover both confirmatory and new findings in ecosystem dynamics. Overall, we demonstrated that our system can facilitate an understanding of how systems function beyond the intuitive analysis of high-dimensional information based on specific domain knowledge. | false | false | [
"Hiroaki Natsukawa",
"Ethan R. Deyle",
"Gerald M. Pao",
"Koji Koyamada",
"George Sugihara"
] | [] | [
"V"
] | [
{
"name": "Fast Forward",
"url": "https://youtu.be/6n0nG2FcZxA",
"icon": "video"
}
] |
VAST | 2,020 | A Visual Analytics Approach for Exploratory Causal Analysis: Exploration, Validation, and Applications | 10.1109/TVCG.2020.3028957 | Using causal relations to guide decision making has become an essential analytical task across various domains, from marketing and medicine to education and social science. While powerful statistical models have been developed for inferring causal relations from data, domain practitioners still lack effective visual interface for interpreting the causal relations and applying them in their decision-making process. Through interview studies with domain experts, we characterize their current decision-making workflows, challenges, and needs. Through an iterative design process, we developed a visualization tool that allows analysts to explore, validate, and apply causal relations in real-world decision-making scenarios. The tool provides an uncertainty-aware causal graph visualization for presenting a large set of causal relations inferred from high-dimensional data. On top of the causal graph, it supports a set of intuitive user controls for performing what-if analyses and making action plans. We report on two case studies in marketing and student advising to demonstrate that users can effectively explore causal relations and design action plans for reaching their goals. | false | false | [
"Xiao Xie",
"Fan Du",
"Yingcai Wu"
] | [] | [
"P",
"V"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2009.02458v1",
"icon": "paper"
},
{
"name": "Fast Forward",
"url": "https://youtu.be/hpNhFtKaSq8",
"icon": "video"
}
] |
VAST | 2,020 | A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems’ Worldviews | 10.1109/VAST50239.2020.00008 | Autonomous multi-robot systems, where a team of robots shares information to perform tasks that are beyond an individual robot’s abilities, hold great promise for a number of applications, such as planetary exploration missions. Each robot in a multi-robot system that uses the shared-world coordination paradigm autonomously schedules which robot should perform a given task, and when, using its worldview–the robot’s internal representation of its belief about both its own state, and other robots’ states. A key problem for operators is that robots’ worldviews can fall out of sync (often due to weak communication links), leading to desynchronization of the robots’ scheduling decisions and inconsistent emergent behavior (e.g., tasks not performed, or performed by multiple robots). Operators face the time-consuming and difficult task of making sense of the robots’ scheduling decisions, detecting de-synchronizations, and pinpointing the cause by comparing every robot’s worldview. To address these challenges, we introduce MOSAIC Viewer, a visual analytics system that helps operators (i) make sense of the robots’ schedules and (ii) detect and conduct a root cause analysis of the robots’ desynchronized worldviews. Over a year-long partnership with roboticists at the NASA Jet Propulsion Laboratory, we conduct a formative study to identify the necessary system design requirements and a qualitative evaluation with 12 roboticists. We find that MOSAIC Viewer is faster- and easier-to-use than the users’ current approaches, and it allows them to stitch low-level details to formulate a high-level understanding of the robots’ schedules and detect and pinpoint the cause of the desynchronized worldviews. | false | false | [
"Sandra Bae",
"Federico Rossi 0001",
"Joshua Vander Hook",
"Scott Davidoff",
"Kwan-Liu Ma"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/2009.01921v1",
"icon": "paper"
}
] |
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