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train · 6.09k rows

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
VAST	2,019	Selection Bias Tracking and Detailed Subset Comparison for High-Dimensional Data	10.1109/TVCG.2019.2934209	The collection of large, complex datasets has become common across a wide variety of domains. Visual analytics tools increasingly play a key role in exploring and answering complex questions about these large datasets. However, many visualizations are not designed to concurrently visualize the large number of dimension...	false	false	[ "David Borland", "Wenyuan Wang", "Jonathan Zhang", "Joshua Shrestha", "David Gotz" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1906.07625v3", "icon": "paper" } ]
VAST	2,019	Semantic Concept Spaces: Guided Topic Model Refinement using Word-Embedding Projections	10.1109/TVCG.2019.2934654	We present a framework that allows users to incorporate the semantics of their domain knowledge for topic model refinement while remaining model-agnostic. Our approach enables users to (1) understand the semantic space of the model, (2) identify regions of potential conflicts and problems, and (3) readjust the semantic...	false	false	[ "Mennatallah El-Assady", "Rebecca Kehlbeck", "Christopher Collins 0001", "Daniel A. Keim", "Oliver Deussen" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00475v1", "icon": "paper" } ]
VAST	2,019	sPortfolio: Stratified Visual Analysis of Stock Portfolios	10.1109/TVCG.2019.2934660	Quantitative Investment, built on the solid foundation of robust financial theories, is at the center stage in investment industry today. The essence of quantitative investment is the multi-factor model, which explains the relationship between the risk and return of equities. However, the multi-factor model generates e...	false	false	[ "Xuanwu Yue", "Jiaxin Bai", "Qinhan Liu", "Yiyang Tang", "Abishek Puri", "Ke Li", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1910.05536v1", "icon": "paper" } ]
VAST	2,019	STBins: Visual Tracking and Comparison of Multiple Data Sequences Using Temporal Binning	10.1109/TVCG.2019.2934289	While analyzing multiple data sequences, the following questions typically arise: how does a single sequence change over time, how do multiple sequences compare within a period, and how does such comparison change over time. This paper presents a visual technique named STBins to answer these questions. STBins is design...	false	false	[ "Ji Qi", "Vincent Bloemen", "Shihan Wang 0001", "Jarke J. van Wijk", "Huub van de Wetering" ]	[]	[]	[]
VAST	2,019	Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations	10.1109/TVCG.2019.2934659	Deep learning is increasingly used in decision-making tasks. However, understanding how neural networks produce final predictions remains a fundamental challenge. Existing work on interpreting neural network predictions for images often focuses on explaining predictions for single images or neurons. As predictions are ...	false	false	[ "Fred Hohman", "Haekyu Park", "Caleb Robinson", "Polo Chau" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1904.02323v3", "icon": "paper" } ]
VAST	2,019	Supporting Analysis of Dimensionality Reduction Results with Contrastive Learning	10.1109/TVCG.2019.2934251	Dimensionality reduction (DR) is frequently used for analyzing and visualizing high-dimensional data as it provides a good first glance of the data. However, to interpret the DR result for gaining useful insights from the data, it would take additional analysis effort such as identifying clusters and understanding thei...	false	false	[ "Takanori Fujiwara", "Oh-Hyun Kwon", "Kwan-Liu Ma" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1905.03911v3", "icon": "paper" } ]
VAST	2,019	Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis	10.1109/TVCG.2019.2934630	Simulative analysis in competitive sports can provide prospective insights, which can help improve the performance of players in future matches. However, adequately simulating the complex competition process and effectively explaining the simulation result to domain experts are typically challenging. This work presents...	false	false	[ "Jiachen Wang", "Kejian Zhao", "Dazhen Deng", "Anqi Cao", "Xiao Xie", "Zheng Zhou", "Hui Zhang 0051", "Yingcai Wu" ]	[]	[]	[]
VAST	2,019	The Validity, Generalizability and Feasibility of Summative Evaluation Methods in Visual Analytics	10.1109/TVCG.2019.2934264	Many evaluation methods have been used to assess the usefulness of Visual Analytics (VA) solutions. These methods stem from a variety of origins with different assumptions and goals, which cause confusion about their proofing capabilities. Moreover, the lack of discussion about the evaluation processes may limit our po...	false	false	[ "Mosab Khayat", "Morteza Karimzadeh", "David S. Ebert", "Arif Ghafoor" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.13314v2", "icon": "paper" } ]
VAST	2,019	The What-If Tool: Interactive Probing of Machine Learning Models	10.1109/TVCG.2019.2934619	A key challenge in developing and deploying Machine Learning (ML) systems is understanding their performance across a wide range of inputs. To address this challenge, we created the What-If Tool, an open-source application that allows practitioners to probe, visualize, and analyze ML systems, with minimal coding. The W...	false	false	[ "James Wexler", "Mahima Pushkarna", "Tolga Bolukbasi", "Martin Wattenberg", "Fernanda B. Viégas", "Jimbo Wilson" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.04135v2", "icon": "paper" } ]
VAST	2,019	TopicSifter: Interactive Search Space Reduction through Targeted Topic Modeling	10.1109/VAST47406.2019.8986922	Topic modeling is commonly used to analyze and understand large document collections. However, in practice, users want to focus on specific aspects or “targets” rather than the entire corpus. For example, given a large collection of documents, users may want only a smaller subset which more closely aligns with their in...	false	false	[ "Hannah Kim", "Dongjin Choi", "Barry L. Drake", "Alex Endert", "Haesun Park" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.12079v1", "icon": "paper" } ]
VAST	2,019	Understanding the Role of Alternatives in Data Analysis Practices	10.1109/TVCG.2019.2934593	Data workers are people who perform data analysis activities as a part of their daily work but do not formally identify as data scientists. They come from various domains and often need to explore diverse sets of hypotheses and theories, a variety of data sources, algorithms, methods, tools, and visual designs. Taken t...	false	false	[ "Jiali Liu", "Nadia Boukhelifa", "James R. Eagan" ]	[]	[]	[]
VAST	2,019	VASABI: Hierarchical User Profiles for Interactive Visual User Behaviour Analytics	10.1109/TVCG.2019.2934609	User behaviour analytics (UBA) systems offer sophisticated models that capture users' behaviour over time with an aim to identify fraudulent activities that do not match their profiles. Motivated by the challenges in the interpretation of UBA models, this paper presents a visual analytics approach to help analysts gain...	false	false	[ "Phong H. Nguyen", "Rafael Henkin", "Siming Chen 0001", "Natalia V. Andrienko", "Gennady L. Andrienko", "Olivier Thonnard", "Cagatay Turkay" ]	[]	[]	[]
VAST	2,019	VASSL: A Visual Analytics Toolkit for Social Spambot Labeling	10.1109/TVCG.2019.2934266	Social media platforms are filled with social spambots. Detecting these malicious accounts is essential, yet challenging, as they continually evolve to evade detection techniques. In this article, we present VASSL, a visual analytics system that assists in the process of detecting and labeling spambots. Our tool enhanc...	false	false	[ "Mosab Khayat", "Morteza Karimzadeh", "Jieqiong Zhao", "David S. Ebert" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.13319v2", "icon": "paper" } ]
VAST	2,019	VIANA: Visual Interactive Annotation of Argumentation	10.1109/VAST47406.2019.8986917	Argumentation Mining addresses the challenging tasks of identifying boundaries of argumentative text fragments and extracting their relationships. Fully automated solutions do not reach satisfactory accuracy due to their insufficient incorporation of semantics and domain knowledge. Therefore, experts currently rely on ...	false	false	[ "Fabian Sperrle", "Rita Sevastjanova", "Rebecca Kehlbeck", "Mennatallah El-Assady" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.12413v1", "icon": "paper" } ]
VAST	2,019	Visual Analysis of High-Dimensional Event Sequence Data via Dynamic Hierarchical Aggregation	10.1109/TVCG.2019.2934661	Temporal event data are collected across a broad range of domains, and a variety of visual analytics techniques have been developed to empower analysts working with this form of data. These techniques generally display aggregate statistics computed over sets of event sequences that share common patterns. Such technique...	false	false	[ "David Gotz", "Jonathan Zhang", "Wenyuan Wang", "Joshua Shrestha", "David Borland" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1906.07617v2", "icon": "paper" } ]
VAST	2,019	Visual Analytics for Electromagnetic Situation Awareness in Radio Monitoring and Management	10.1109/TVCG.2019.2934655	Traditional radio monitoring and management largely depend on radio spectrum data analysis, which requires considerable domain experience and heavy cognition effort and frequently results in incorrect signal judgment and incomprehensive situation awareness. Faced with increasingly complicated electromagnetic environmen...	false	false	[ "Ying Zhao 0001", "Xiaobo Luo", "Xiaoru Lin", "Hairong Wang", "Xiaoyan Kui", "Fangfang Zhou", "Jinsong Wang", "Yi Chen 0007", "Wei Chen 0001" ]	[]	[]	[]
VAST	2,019	Visual Interaction with Deep Learning Models through Collaborative Semantic Inference	10.1109/TVCG.2019.2934595	Automation of tasks can have critical consequences when humans lose agency over decision processes. Deep learning models are particularly susceptible since current black-box approaches lack explainable reasoning. We argue that both the visual interface and model structure of deep learning systems need to take into acco...	false	false	[ "Sebastian Gehrmann", "Hendrik Strobelt", "Robert Krüger", "Hanspeter Pfister", "Alexander M. Rush" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.10739v1", "icon": "paper" } ]
VAST	2,019	You can't always sketch what you want: Understanding Sensemaking in Visual Query Systems	10.1109/TVCG.2019.2934666	Visual query systems (VQSs) empower users to interactively search for line charts with desired visual patterns, typically specified using intuitive sketch-based interfaces. Despite decades of past work on VQSs, these efforts have not translated to adoption in practice, possibly because VQSs are largely evaluated in unr...	false	false	[ "Doris Jung Lin Lee", "John Lee 0005", "Tarique Siddiqui", "Jaewoo Kim", "Karrie Karahalios", "Aditya G. Parameswaran" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1710.00763v7", "icon": "paper" } ]
SciVis	2,019	A Structural Average of Labeled Merge Trees for Uncertainty Visualization	10.1109/TVCG.2019.2934242	Physical phenomena in science and engineering are frequently modeled using scalar fields. In scalar field topology, graph-based topological descriptors such as merge trees, contour trees, and Reeb graphs are commonly used to characterize topological changes in the (sub)level sets of scalar fields. One of the biggest ch...	false	false	[ "Lin Yan", "Yusu Wang 0001", "Elizabeth Munch", "Ellen Gasparovic", "Bei Wang 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00113v2", "icon": "paper" } ]
SciVis	2,019	Accelerated Monte Carlo Rendering of Finite-Time Lyapunov Exponents	10.1109/TVCG.2019.2934313	Time-dependent fluid flows often contain numerous hyperbolic Lagrangian coherent structures, which act as transport barriers that guide the advection. The finite-time Lyapunov exponent is a commonly-used approximation to locate these repelling or attracting structures. Especially on large numerical simulations, the FTL...	false	false	[ "Irene Baeza Rojo", "Markus H. Gross", "Tobias Günther" ]	[]	[]	[]
SciVis	2,019	Analysis of the Near-Wall Flow in a Turbine Cascade by Splat Visualization	10.1109/TVCG.2019.2934367	Turbines are essential components of jet planes and power plants. Therefore, their efficiency and service life are of central engineering interest. In the case of jet planes or thermal power plants, the heating of the turbines due to the hot gas flow is critical. Besides effective cooling, it is a major goal of enginee...	false	false	[ "Baldwin Nsonga", "Gerik Scheuermann", "Stefan Gumhold", "Jordi Ventosa-Molina", "Denis Koschichow", "Jochen Fröhlich" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.09904v1", "icon": "paper" } ]
SciVis	2,019	Artifact-Based Rendering: Harnessing Natural and Traditional Visual Media for More Expressive and Engaging 3D Visualizations	10.1109/TVCG.2019.2934260	We introduce Artifact-Based Rendering (ABR), a framework of tools, algorithms, and processes that makes it possible to produce real, data-driven 3D scientific visualizations with a visual language derived entirely from colors, lines, textures, and forms created using traditional physical media or found in nature. A the...	false	false	[ "Seth Johnson", "Francesca Samsel", "Greg Abram", "Daniel Olson", "Andrew J. Solis", "Bridger Herman", "Phillip J. Wolfram", "Christophe Lenglet", "Daniel F. Keefe" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.13178v2", "icon": "paper" } ]
SciVis	2,019	Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration	10.1109/TVCG.2019.2934546	We describe a visual computing approach to radiation therapy (RT) planning, based on spatial similarity within a patient cohort. In radiotherapy for head and neck cancer treatment, dosage to organs at risk surrounding a tumor is a large cause of treatment toxicity. Along with the availability of patient repositories, t...	false	false	[ "Andrew Wentzel", "Peter Hanula", "Timothy Luciani", "Baher Elgohari", "Hesham Elhalawani", "Guadalupe Canahuate", "David M. Vock", "Clifton D. Fuller", "G. Elisabeta Marai" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.05919v2", "icon": "paper" } ]
SciVis	2,019	Deadeye Visualization Revisited: Investigation of Preattentiveness and Applicability in Virtual Environments	10.1109/TVCG.2019.2934370	Visualizations rely on highlighting to attract and guide our attention. To make an object of interest stand out independently from a number of distractors, the underlying visual cue, e.g., color, has to be preattentive. In our prior work, we introduced Deadeye as an instantly recognizable highlighting technique that wo...	false	false	[ "Andrey Krekhov", "Sebastian Cmentowski", "Andre Waschk", "Jens H. Krüger" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.04702v1", "icon": "paper" } ]
SciVis	2,019	DeepOrganNet: On-the-Fly Reconstruction and Visualization of 3D / 4D Lung Models from Single-View Projections by Deep Deformation Network	10.1109/TVCG.2019.2934369	This paper introduces a deep neural network based method, i.e., DeepOrganNet, to generate and visualize fully high-fidelity 3D / 4D organ geometric models from single-view medical images with complicated background in real time. Traditional 3D / 4D medical image reconstruction requires near hundreds of projections, whi...	false	false	[ "Yifan Wang", "Zichun Zhong", "Jing Hua 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.09375v1", "icon": "paper" } ]
SciVis	2,019	Dynamic Nested Tracking Graphs	10.1109/TVCG.2019.2934368	This work describes an approach for the interactive visual analysis of large-scale simulations, where numerous superlevel set components and their evolution are of primary interest. The approach first derives, at simulation runtime, a specialized Cinema database that consists of images of component groups, and topologi...	false	false	[ "Jonas Lukasczyk", "Christoph Garth", "Gunther H. Weber", "Tim Biedert", "Ross Maciejewski", "Heike Leitte" ]	[]	[]	[]
SciVis	2,019	Extraction and Visual Analysis of Potential Vorticity Banners around the Alps	10.1109/TVCG.2019.2934310	Potential vorticity is among the most important scalar quantities in atmospheric dynamics. For instance, potential vorticity plays a key role in particularly strong wind peaks in extratropical cyclones and it is able to explain the occurrence of frontal rain bands. Potential vorticity combines the key quantities of atm...	false	false	[ "Robin Bader", "Michael Sprenger", "Nikolina Ban", "Stefan Rüdisühli", "Christoph Schär", "Tobias Günther" ]	[]	[]	[]
SciVis	2,019	High-throughput feature extraction for measuring attributes of deforming open-cell foams	10.1109/TVCG.2019.2934620	Metallic open-cell foams are promising structural materials with applications in multifunctional systems such as biomedical implants, energy absorbers in impact, noise mitigation, and batteries. There is a high demand for means to understand and correlate the design space of material performance metrics to the material...	false	false	[ "Steve Petruzza", "Attila Gyulassy", "Samuel Leventhal", "John J. Baglino", "Michael Czabaj", "Ashley D. Spear", "Valerio Pascucci" ]	[]	[]	[]
SciVis	2,019	InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations	10.1109/TVCG.2019.2934312	We propose InSituNet, a deep learning based surrogate model to support parameter space exploration for ensemble simulations that are visualized in situ. In situ visualization, generating visualizations at simulation time, is becoming prevalent in handling large-scale simulations because of the I/O and storage constrain...	false	false	[ "Wenbin He", "Junpeng Wang", "Hanqi Guo 0001", "Ko-Chih Wang", "Han-Wei Shen", "Mukund Raj", "Youssef S. G. Nashed", "Tom Peterka" ]	[ "BP" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00407v3", "icon": "paper" } ]
SciVis	2,019	LassoNet: Deep Lasso-Selection of 3D Point Clouds	10.1109/TVCG.2019.2934332	Selection is a fundamental task in exploratory analysis and visualization of 3D point clouds. Prior researches on selection methods were developed mainly based on heuristics such as local point density, thus limiting their applicability in general data. Specific challenges root in the great variabilities implied by poi...	false	false	[ "Zhutian Chen", "Wei Zeng 0004", "Zhiguang Yang", "Lingyun Yu 0005", "Chi-Wing Fu", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.13538v3", "icon": "paper" } ]
SciVis	2,019	Multi-Scale Procedural Animations of Microtubule Dynamics Based on Measured Data	10.1109/TVCG.2019.2934612	Biologists often use computer graphics to visualize structures, which due to physical limitations are not possible to image with a microscope. One example for such structures are microtubules, which are present in every eukaryotic cell. They are part of the cytoskeleton maintaining the shape of the cell and playing a k...	false	false	[ "Tobias Klein", "Ivan Viola", "M. Eduard Gröller", "Peter Mindek" ]	[]	[]	[]
SciVis	2,019	Multi-Scale Topological Analysis of Asymmetric Tensor Fields on Surfaces	10.1109/TVCG.2019.2934314	Asymmetric tensor fields have found applications in many science and engineering domains, such as fluid dynamics. Recent advances in the visualization and analysis of 2D asymmetric tensor fields focus on pointwise analysis of the tensor field and effective visualization metaphors such as colors, glyphs, and hyperstream...	false	false	[ "Fariba Khan", "Lawrence Roy", "Eugene Zhang", "Botong Qu", "Shih-Hsuan Hung", "Harry Yeh", "Robert S. Laramee", "Yue Zhang 0009" ]	[]	[]	[]
SciVis	2,019	Multiscale Visual Drilldown for the Analysis of Large Ensembles of Multi-Body Protein Complexes	10.1109/TVCG.2019.2934333	When studying multi-body protein complexes, biochemists use computational tools that can suggest hundreds or thousands of their possible spatial configurations. However, it is not feasible to experimentally verify more than only a very small subset of them. In this paper, we propose a novel multiscale visual drilldown ...	false	false	[ "Katarína Furmanová", "Adam Jurcík", "Barbora Kozlíková", "Helwig Hauser", "Jan Byska" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.04112v1", "icon": "paper" } ]
SciVis	2,019	OpenSpace: A System for Astrographics	10.1109/TVCG.2019.2934259	Human knowledge about the cosmos is rapidly increasing as instruments and simulations are generating new data supporting the formation of theory and understanding of the vastness and complexity of the universe. OpenSpace is a software system that takes on the mission of providing an integrated view of all these sources...	false	false	[ "Alexander Bock 0002", "Anders Ynnerman", "Emil Axelsson", "Jonathas Costa", "Gene Payne", "Micah Acinapura", "Vivian Trakinski", "Carter Emmart", "Cláudio T. Silva", "Charles D. Hansen" ]	[]	[]	[]
SciVis	2,019	Progressive Wasserstein Barycenters of Persistence Diagrams	10.1109/TVCG.2019.2934256	This paper presents an efficient algorithm for the progressive approximation of Wasserstein barycenters of persistence diagrams, with applications to the visual analysis of ensemble data. Given a set of scalar fields, our approach enables the computation of a persistence diagram which is representative of the set, and ...	false	false	[ "Jules Vidal", "Joseph Budin", "Julien Tierny" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.04565v2", "icon": "paper" } ]
SciVis	2,019	Scale Trotter: Illustrative Visual Travels Across Negative Scales	10.1109/TVCG.2019.2934334	We present ScaleTrotter, a conceptual framework for an interactive, multi-scale visualization of biological mesoscale data and, specifically, genome data. ScaleTrotter allows viewers to smoothly transition from the nucleus of a cell to the atomistic composition of the DNA, while bridging several orders of magnitude in ...	false	false	[ "Sarkis Halladjian", "Haichao Miao", "David Kouril", "M. Eduard Gröller", "Ivan Viola", "Tobias Isenberg 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.12352v1", "icon": "paper" } ]
SciVis	2,019	Scale-Space Splatting: Reforming Spacetime for Cross-Scale Exploration of Integral Measures in Molecular Dynamics	10.1109/TVCG.2019.2934258	Understanding large amounts of spatiotemporal data from particle-based simulations, such as molecular dynamics, often relies on the computation and analysis of aggregate measures. These, however, by virtue of aggregation, hide structural information about the space/time localization of the studied phenomena. This leads...	false	false	[ "Juraj Pálenik", "Jan Byska", "Stefan Bruckner", "Helwig Hauser" ]	[]	[]	[]
SciVis	2,019	Temporal Views of Flattened Mitral Valve Geometries	10.1109/TVCG.2019.2934337	The mitral valve, one of the four valves in the human heart, controls the bloodflow between the left atrium and ventricle and may suffer from various pathologies. Malfunctioning valves can be treated by reconstructive surgeries, which have to be carefully planned and evaluated. While current research focuses on the mod...	false	false	[ "Pepe Eulzer", "Sandy Engelhardt", "Nils Lichtenberg", "Raffaele De Simone", "Kai Lawonn" ]	[]	[]	[]
SciVis	2,019	The Effect of Data Transformations on Scalar Field Topological Analysis of High-Order FEM Solutions	10.1109/TVCG.2019.2934338	High-order finite element methods (HO-FEM) are gaining popularity in the simulation community due to their success in solving complex flow dynamics. There is an increasing need to analyze the data produced as output by these simulations. Simultaneously, topological analysis tools are emerging as powerful methods for in...	false	false	[ "Ashok Jallepalli", "Joshua A. Levine", "Robert M. Kirby" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.07224v1", "icon": "paper" } ]
SciVis	2,019	Toward Localized Topological Data Structures: Querying the Forest for the Tree	10.1109/TVCG.2019.2934257	Topological approaches to data analysis can answer complex questions about the number, connectivity, and scale of intrinsic features in scalar data. However, the global nature of many topological structures makes their computation challenging at scale, and thus often limits the size of data that can be processed. One k...	false	false	[ "Pavol Klacansky", "Attila Gyulassy", "Peer-Timo Bremer", "Valerio Pascucci" ]	[ "HM" ]	[]	[]
SciVis	2,019	TSR-TVD: Temporal Super-Resolution for Time-Varying Data Analysis and Visualization	10.1109/TVCG.2019.2934255	We present TSR-TVD, a novel deep learning framework that generates temporal super-resolution (TSR) of time-varying data (TVD) using adversarial learning. TSR-TVD is the first work that applies the recurrent generative network (RGN), a combination of the recurrent neural network (RNN) and generative adversarial network ...	false	false	[ "Jun Han 0010", "Chaoli Wang 0001" ]	[]	[]	[]
SciVis	2,019	Vector Field Topology of Time-Dependent Flows in a Steady Reference Frame	10.1109/TVCG.2019.2934375	The topological analysis of unsteady vector fields remains to this day one of the largest challenges in flow visualization. We build up on recent work on vortex extraction to define a time-dependent vector field topology for 2D and 3D flows. In our work, we split the vector field into two components: a vector field in ...	false	false	[ "Irene Baeza Rojo", "Tobias Günther" ]	[]	[]	[]
SciVis	2,019	Void-and-Cluster Sampling of Large Scattered Data and Trajectories	10.1109/TVCG.2019.2934335	We propose a data reduction technique for scattered data based on statistical sampling. Our void-and-cluster sampling technique finds a representative subset that is optimally distributed in the spatial domain with respect to the blue noise property. In addition, it can adapt to a given density function, which we use t...	false	false	[ "Tobias Rapp", "Christoph Peters 0002", "Carsten Dachsbacher" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.05073v2", "icon": "paper" } ]
InfoVis	2,019	A Comparative Evaluation of Animation and Small Multiples for Trend Visualization on Mobile Phones	10.1109/TVCG.2019.2934397	We compare the efficacy of animated and small multiples variants of scatterplots on mobile phones for comparing trends in multivariate datasets. Visualization is increasingly prevalent in mobile applications and mobile-first websites, yet there is little prior visualization research dedicated to small displays. In this...	false	false	[ "Matthew Brehmer", "Bongshin Lee", "Petra Isenberg", "Eun Kyoung Choe" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.03919v2", "icon": "paper" } ]
InfoVis	2,019	A Comparison of Radial and Linear Charts for Visualizing Daily Patterns	10.1109/TVCG.2019.2934784	Radial charts are generally considered less effective than linear charts. Perhaps the only exception is in visualizing periodical time-dependent data, which is believed to be naturally supported by the radial layout. It has been demonstrated that the drawbacks of radial charts outweigh the benefits of this natural mapp...	false	false	[ "Manuela Waldner", "Alexandra Diehl", "Denis Gracanin", "Rainer Splechtna", "Claudio Delrieux", "Kresimir Matkovic" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.13534v1", "icon": "paper" } ]
InfoVis	2,019	A Comparison of Visualizations for Identifying Correlation over Space and Time	10.1109/TVCG.2019.2934807	Observing the relationship between two or more variables over space and time is essential in many domains. For instance, looking, for different countries, at the evolution of both the life expectancy at birth and the fertility rate will give an overview of their demographics. The choice of visual representation for suc...	false	false	[ "Vanessa Peña Araya", "Emmanuel Pietriga", "Anastasia Bezerianos" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.06399v2", "icon": "paper" } ]
InfoVis	2,019	A Deep Generative Model for Graph Layout	10.1109/TVCG.2019.2934396	Different layouts can characterize different aspects of the same graph. Finding a “good” layout of a graph is thus an important task for graph visualization. In practice, users often visualize a graph in multiple layouts by using different methods and varying parameter settings until they find a layout that best suits ...	false	false	[ "Oh-Hyun Kwon", "Kwan-Liu Ma" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1904.12225v7", "icon": "paper" } ]
InfoVis	2,019	A Recursive Subdivision Technique for Sampling Multi-class Scatterplots	10.1109/TVCG.2019.2934541	We present a non-uniform recursive sampling technique for multi-class scatterplots, with the specific goal of faithfully presenting relative data and class densities, while preserving major outliers in the plots. Our technique is based on a customized binary kd-tree, in which leaf nodes are created by recursively subdi...	false	false	[ "Xin Chen", "Tong Ge", "Jian Zhang 0070", "Baoquan Chen", "Chi-Wing Fu", "Oliver Deussen", "Yunhai Wang" ]	[]	[]	[]
InfoVis	2,019	An Incremental Dimensionality Reduction Method for Visualizing Streaming Multidimensional Data	10.1109/TVCG.2019.2934433	Dimensionality reduction (DR) methods are commonly used for analyzing and visualizing multidimensional data. However, when data is a live streaming feed, conventional DR methods cannot be directly used because of their computational complexity and inability to preserve the projected data positions at previous time poin...	false	false	[ "Takanori Fujiwara", "Jia-Kai Chou", "Shilpika", "Panpan Xu", "Ren Liu", "Kwan-Liu Ma" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1905.04000v3", "icon": "paper" } ]
InfoVis	2,019	BarcodeTree: Scalable Comparison of Multiple Hierarchies	10.1109/TVCG.2019.2934535	We propose BarcodeTree (BCT), a novel visualization technique for comparing topological structures and node attribute values of multiple trees. BCT can provide an overview of one hundred shallow and stable trees simultaneously, without aggregating individual nodes. Each BCT is shown within a single row using a style si...	false	false	[ "Guozheng Li 0002", "Yu Zhang 0043", "Yu Dong", "Christy Jie Liang", "Jinson Zhang", "Jinsong Wang", "Michael J. McGuffin", "Xiaoru Yuan" ]	[]	[]	[]
InfoVis	2,019	Biased Average Position Estimates in Line and Bar Graphs: Underestimation, Overestimation, and Perceptual Pull	10.1109/TVCG.2019.2934400	In visual depictions of data, position (i.e., the vertical height of a line or a bar) is believed to be the most precise way to encode information compared to other encodings (e.g., hue). Not only are other encodings less precise than position, but they can also be prone to systematic biases (e.g., color category bound...	false	false	[ "Cindy Xiong", "Cristina R. Ceja", "Casimir J. H. Ludwig", "Steven Franconeri" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00073v1", "icon": "paper" } ]
InfoVis	2,019	CerebroVis: Designing an Abstract yet Spatially Contextualized Cerebral Artery Network Visualization	10.1109/TVCG.2019.2934402	Blood circulation in the human brain is supplied through a network of cerebral arteries. If a clinician suspects a patient has a stroke or other cerebrovascular condition, they order imaging tests. Neuroradiologists visually search the resulting scans for abnormalities. Their visual search tasks correspond to the abstr...	false	false	[ "Aditeya Pandey", "Harsh Shukla", "Geoffrey S. Young", "Lei Qin", "Amir A. Zamani", "Liangge Hsu", "Raymond Huang", "Cody Dunne", "Michelle Borkin" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "https://osf.io/63y5c", "icon": "paper" } ]
InfoVis	2,019	Color Crafting: Automating the Construction of Designer Quality Color Ramps	10.1109/TVCG.2019.2934284	Visualizations often encode numeric data using sequential and diverging color ramps. Effective ramps use colors that are sufficiently discriminable, align well with the data, and are aesthetically pleasing. Designers rely on years of experience to create high-quality color ramps. However, it is challenging for novice v...	false	false	[ "Stephen Smart", "Keke Wu", "Danielle Albers Szafir" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00629v1", "icon": "paper" } ]
InfoVis	2,019	Common Fate for Animated Transitions in Visualization	10.1109/TVCG.2019.2934288	The Law of Common Fate from Gestalt psychology states that visual objects moving with the same velocity along parallel trajectories will be perceived by a human observer as grouped. However, the concept of common fate is much broader than mere velocity; in this paper we explore how common fate results from coordinated ...	false	false	[ "Amira Chalbi", "Jacob Ritchie", "Deok Gun Park 0001", "Jungu Choi", "Nicolas Roussel 0001", "Niklas Elmqvist", "Fanny Chevalier" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00661v1", "icon": "paper" } ]
InfoVis	2,019	Construct-A-Vis: Exploring the Free-Form Visualization Processes of Children	10.1109/TVCG.2019.2934804	Building data analysis skills is part of modern elementary school curricula. Recent research has explored how to facilitate children's understanding of visual data representations through completion exercises which highlight links between concrete and abstract mappings. This approach scaffolds visualization activities ...	false	false	[ "Fearn Bishop", "Johannes Zagermann", "Ulrike Pfeil", "Gemma Sanderson", "Harald Reiterer", "Uta Hinrichs" ]	[]	[]	[]
InfoVis	2,019	Criteria for Rigor in Visualization Design Study	10.1109/TVCG.2019.2934539	We develop a new perspective on research conducted through visualization design study that emphasizes design as a method of inquiry and the broad range of knowledge-contributions achieved through it as multiple, subjective, and socially constructed. From this interpretivist position we explore the nature of visualizati...	false	false	[ "Miriah D. Meyer", "Jason Dykes" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.08495v2", "icon": "paper" } ]
InfoVis	2,019	Critical Reflections on Visualization Authoring Systems	10.1109/TVCG.2019.2934281	An emerging generation of visualization authoring systems support expressive information visualization without textual programming. As they vary in their visualization models, system architectures, and user interfaces, it is challenging to directly compare these systems using traditional evaluative methods. Recognizing...	false	false	[ "Arvind Satyanarayan", "Bongshin Lee", "Donghao Ren", "Jeffrey Heer", "John T. Stasko", "John Thompson 0002", "Matthew Brehmer", "Zhicheng Liu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.13568v1", "icon": "paper" } ]
InfoVis	2,019	Data by Proxy — Material Traces as Autographic Visualizations	10.1109/TVCG.2019.2934788	Information visualization limits itself, per definition, to the domain of symbolic information. This paper discusses arguments why the field should also consider forms of data that are not symbolically encoded, including physical traces and material indicators. Continuing a provocation presented by Pat Hanrahan in his ...	false	false	[ "Dietmar Offenhuber" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.05454v1", "icon": "paper" } ]
InfoVis	2,019	Data Changes Everything: Challenges and Opportunities in Data Visualization Design Handoff	10.1109/TVCG.2019.2934538	Complex data visualization design projects often entail collaboration between people with different visualization-related skills. For example, many teams include both designers who create new visualization designs and developers who implement the resulting visualization software. We identify gaps between data character...	false	false	[ "Jagoda Walny", "Christian Frisson", "Mieka West", "Doris Kosminsky", "Søren Knudsen", "Sheelagh Carpendale", "Wesley Willett" ]	[ "BP" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00192v1", "icon": "paper" } ]
InfoVis	2,019	Data Sampling in Multi-view and Multi-class Scatterplots via Set Cover Optimization	10.1109/TVCG.2019.2934799	We present a method for data sampling in scatterplots by jointly optimizing point selection for different views or classes. Our method uses space-filling curves (Z-order curves) that partition a point set into subsets that, when covered each by one sample, provide a sampling or coreset with good approximation guarantee...	false	false	[ "Ruizhen Hu", "Tingkai Sha", "Oliver van Kaick", "Oliver Deussen", "Hui Huang 0004" ]	[]	[]	[]
InfoVis	2,019	DataShot: Automatic Generation of Fact Sheets from Tabular Data	10.1109/TVCG.2019.2934398	Fact sheets with vivid graphical design and intriguing statistical insights are prevalent for presenting raw data. They help audiences understand data-related facts effectively and make a deep impression. However, designing a fact sheet requires both data and design expertise and is a laborious and time-consuming proce...	false	false	[ "Yun Wang 0012", "Zhida Sun", "Haidong Zhang", "Weiwei Cui", "Ke Xu", "Xiaojuan Ma", "Dongmei Zhang 0001" ]	[]	[]	[]
InfoVis	2,019	Decoding a Complex Visualization in a Science Museum – An Empirical Study	10.1109/TVCG.2019.2934401	This study describes a detailed analysis of museum visitors' decoding process as they used a visualization designed to support exploration of a large, complex dataset. Quantitative and qualitative analyses revealed that it took, on average, 43 seconds for visitors to decode enough of the visualization to see patterns a...	false	false	[ "Joyce Ma", "Kwan-Liu Ma", "Jennifer Frazier" ]	[]	[]	[]
InfoVis	2,019	DeepDrawing: A Deep Learning Approach to Graph Drawing	10.1109/TVCG.2019.2934798	Node-link diagrams are widely used to facilitate network explorations. However, when using a graph drawing technique to visualize networks, users often need to tune different algorithm-specific parameters iteratively by comparing the corresponding drawing results in order to achieve a desired visual effect. This trial ...	false	false	[ "Yong Wang 0021", "Zhihua Jin", "Qianwen Wang", "Weiwei Cui", "Tengfei Ma 0001", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.11040v3", "icon": "paper" } ]
InfoVis	2,019	Design by Immersion: A Transdisciplinary Approach to Problem-Driven Visualizations	10.1109/TVCG.2019.2934790	While previous work exists on how to conduct and disseminate insights from problem-driven visualization projects and design studies, the literature does not address how to accomplish these goals in transdisciplinary teams in ways that advance all disciplines involved. In this paper we introduce and define a new methodo...	false	false	[ "Kyle Wm. Hall", "Adam James Bradley", "Uta Hinrichs", "Samuel Huron", "Jo Wood", "Christopher Collins 0001", "Sheelagh Carpendale" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00559v2", "icon": "paper" } ]
InfoVis	2,019	Designing for Mobile and Immersive Visual Analytics in the Field	10.1109/TVCG.2019.2934282	Data collection and analysis in the field is critical for operations in domains such as environmental science and public safety. However, field workers currently face data- and platform-oriented issues in efficient data collection and analysis in the field, such as limited connectivity, screen space, and attentional re...	false	false	[ "Matt Whitlock", "Keke Wu", "Danielle Albers Szafir" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00680v1", "icon": "paper" } ]
InfoVis	2,019	Discriminability Tests for Visualization Effectiveness and Scalability	10.1109/TVCG.2019.2934432	The scalability of a particular visualization approach is limited by the ability for people to discern differences between plots made with different datasets. Ideally, when the data changes, the visualization changes in perceptible ways. This relation breaks down when there is a mismatch between the encoding and the ch...	false	false	[ "Rafael Veras", "Christopher Collins 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.11358v1", "icon": "paper" } ]
InfoVis	2,019	Estimating Color-Concept Associations from Image Statistics	10.1109/TVCG.2019.2934536	To interpret the meanings of colors in visualizations of categorical information, people must determine how distinct colors correspond to different concepts. This process is easier when assignments between colors and concepts in visualizations match people's expectations, making color palettes semantically interpretabl...	false	false	[ "Ragini Rathore", "Zachary Leggon", "Laurent Lessard", "Karen B. Schloss" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00220v2", "icon": "paper" } ]
InfoVis	2,019	Evaluating an Immersive Space-Time Cube Geovisualization for Intuitive Trajectory Data Exploration	10.1109/TVCG.2019.2934415	A Space-Time Cube enables analysts to clearly observe spatio-temporal features in movement trajectory datasets in geovisualization. However, its general usability is impacted by a lack of depth cues, a reported steep learning curve, and the requirement for efficient 3D navigation. In this work, we investigate a Space-T...	false	false	[ "Jorge A. Wagner Filho", "Wolfgang Stuerzlinger", "Luciana Porcher Nedel" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00580v2", "icon": "paper" } ]
InfoVis	2,019	GenerativeMap: Visualization and Exploration of Dynamic Density Maps via Generative Learning Model	10.1109/TVCG.2019.2934806	The density map is widely used for data sampling, time-varying detection, ensemble representation, etc. The visualization of dynamic evolution is a challenging task when exploring spatiotemporal data. Many approaches have been provided to explore the variation of data patterns over time, which commonly need multiple pa...	false	false	[ "Chen Chen", "Changbo Wang", "Xue Bai", "Peiying Zhang", "Chenhui Li" ]	[]	[]	[]
InfoVis	2,019	Illusion of Causality in Visualized Data	10.1109/TVCG.2019.2934399	Students who eat breakfast more frequently tend to have a higher grade point average. From this data, many people might confidently state that a before-school breakfast program would lead to higher grades. This is a reasoning error, because correlation does not necessarily indicate causation – X and Y can be correlated...	false	false	[ "Cindy Xiong", "Joel Shapiro", "Jessica Hullman", "Steven Franconeri" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00215v1", "icon": "paper" } ]
InfoVis	2,019	Improving the Robustness of Scagnostics	10.1109/TVCG.2019.2934796	In this paper, we examine the robustness of scagnostics through a series of theoretical and empirical studies. First, we investigate the sensitivity of scagnostics by employing perturbing operations on more than 60M synthetic and real-world scatterplots. We found that two scagnostic measures, Outlying and Clumpy, are o...	false	false	[ "Yunhai Wang", "Zeyu Wang 0005", "Tingting Liu", "Michael Correll", "Zhanglin Cheng", "Oliver Deussen", "Michael Sedlmair" ]	[]	[]	[]
InfoVis	2,019	Interactive Structure-aware Blending of Diverse Edge Bundling Visualizations	10.1109/TVCG.2019.2934805	Many edge bundling techniques (i.e., data simplification as a support for data visualization and decision making) exist but they are not directly applicable to any kind of dataset and their parameters are often too abstract and difficult to set up. As a result, this hinders the user ability to create efficient aggregat...	false	false	[ "Yunhai Wang", "Mingliang Xue", "Yanyan Wang", "Xinyuan Yan", "Baoquan Chen", "Chi-Wing Fu", "Christophe Hurter" ]	[]	[]	[]
InfoVis	2,019	Investigating Direct Manipulation of Graphical Encodings as a Method for User Interaction	10.1109/TVCG.2019.2934534	We investigate direct manipulation of graphical encodings as a method for interacting with visualizations. There is an increasing interest in developing visualization tools that enable users to perform operations by directly manipulating graphical encodings rather than external widgets such as checkboxes and sliders. D...	false	false	[ "Bahador Saket", "Samuel Huron", "Charles Perin", "Alex Endert" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00679v1", "icon": "paper" } ]
InfoVis	2,019	Measures of the Benefit of Direct Encoding of Data Deltas for Data Pair Relation Perception	10.1109/TVCG.2019.2934801	The power of data visualization is not to convey absolute values of individual data points, but to allow the exploration of relations (increases or decreases in a data value) among them. One approach to highlighting these relations is to explicitly encode the numeric differences (deltas) between data values. Because th...	false	false	[ "Christine Nothelfer", "Steven Franconeri" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "https://osf.io/jup9a", "icon": "paper" } ]
InfoVis	2,019	OntoPlot: A Novel Visualisation for Non-hierarchical Associations in Large Ontologies	10.1109/TVCG.2019.2934557	Ontologies are formal representations of concepts and complex relationships among them. They have been widely used to capture comprehensive domain knowledge in areas such as biology and medicine, where large and complex ontologies can contain hundreds of thousands of concepts. Especially due to the large size of ontolo...	false	false	[ "Ying Yang", "Michael Wybrow", "Yuan-Fang Li", "Tobias Czauderna", "Yongqun He" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00688v2", "icon": "paper" } ]
InfoVis	2,019	P5: Portable Progressive Parallel Processing Pipelines for Interactive Data Analysis and Visualization	10.1109/TVCG.2019.2934537	We present P5, a web-based visualization toolkit that combines declarative visualization grammar and GPU computing for progressive data analysis and visualization. To interactively analyze and explore big data, progressive analytics and visualization methods have recently emerged. Progressive visualizations of incremen...	false	false	[ "Jianping Kelvin Li", "Kwan-Liu Ma" ]	[]	[]	[]
InfoVis	2,019	Pattern-Driven Navigation in 2D Multiscale Visualizations with Scalable Insets	10.1109/TVCG.2019.2934555	We present Scalable Insets, a technique for interactively exploring and navigating large numbers of annotated patterns in multiscale visualizations such as gigapixel images, matrices, or maps. Exploration of many but sparsely-distributed patterns in multiscale visualizations is challenging as visual representations cha...	false	false	[ "Fritz Lekschas", "Michael Behrisch 0001", "Benjamin Bach", "Peter Kerpedjiev", "Nils Gehlenborg", "Hanspeter Pfister" ]	[]	[]	[]
InfoVis	2,019	Persistent Homology Guided Force-Directed Graph Layouts	10.1109/TVCG.2019.2934802	Graphs are commonly used to encode relationships among entities, yet their abstractness makes them difficult to analyze. Node-link diagrams are popular for drawing graphs, and force-directed layouts provide a flexible method for node arrangements that use local relationships in an attempt to reveal the global shape of ...	false	false	[ "Ashley Suh", "Mustafa Hajij", "Bei Wang 0001", "Carlos Scheidegger", "Paul Rosen 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1712.05548v4", "icon": "paper" } ]
InfoVis	2,019	RSATree: Distribution-Aware Data Representation of Large-Scale Tabular Datasets for Flexible Visual Query	10.1109/TVCG.2019.2934800	Analysts commonly investigate the data distributions derived from statistical aggregations of data that are represented by charts, such as histograms and binned scatterplots, to visualize and analyze a large-scale dataset. Aggregate queries are implicitly executed through such a process. Datasets are constantly extreme...	false	false	[ "Honghui Mei", "Wei Chen 0001", "Yating Wei", "Yuanzhe Hu", "Shuyue Zhou", "Bingru Lin", "Ying Zhao 0001", "Jiazhi Xia" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.02005v2", "icon": "paper" } ]
InfoVis	2,019	Searching the Visual Style and Structure of D3 Visualizations	10.1109/TVCG.2019.2934431	We present a search engine for D3 visualizations that allows queries based on their visual style and underlying structure. To build the engine we crawl a collection of 7860 D3 visualizations from the Web and deconstruct each one to recover its data, its data-encoding marks and the encodings describing how the data is m...	false	false	[ "Enamul Hoque", "Maneesh Agrawala" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.11265v2", "icon": "paper" } ]
InfoVis	2,019	Separating the Wheat from the Chaff: Comparative Visual Cues for Transparent Diagnostics of Competing Models	10.1109/TVCG.2019.2934540	Experts in data and physical sciences have to regularly grapple with the problem of competing models. Be it analytical or physics-based models, a cross-cutting challenge for experts is to reliably diagnose which model outcomes appropriately predict or simulate real-world phenomena. Expert judgment involves reconciling ...	false	false	[ "Aritra Dasgupta", "Hong Wang", "Nancy O'Brien", "Susannah Burrows" ]	[]	[]	[]
InfoVis	2,019	ShapeWordle: Tailoring Wordles using Shape-aware Archimedean Spirals	10.1109/TVCG.2019.2934783	We present a new technique to enable the creation of shape-bounded Wordles, we call ShapeWordle, in which we fit words to form a given shape. To guide word placement within a shape, we extend the traditional Archimedean spirals to be shape-aware by formulating the spirals in a differential form using the distance field...	false	false	[ "Yunhai Wang", "Xiaowei Chu", "Kaiyi Zhang", "Chen Bao", "Xiaotong Li", "Jian Zhang 0070", "Chi-Wing Fu", "Christophe Hurter", "Bongshin Lee", "Oliver Deussen" ]	[]	[]	[]
InfoVis	2,019	SmartCube: An Adaptive Data Management Architecture for the Real-Time Visualization of Spatiotemporal Datasets	10.1109/TVCG.2019.2934434	Interactive visualization and exploration of large spatiotemporal data sets is difficult without carefully-designed data pre-processing and management tools. We propose a novel architecture for spatiotemporal data management. The architecture can dynamically update itself based on user queries. Datasets is stored in a ...	false	false	[ "Can Liu 0004", "Cong Wu 0004", "Hanning Shao", "Xiaoru Yuan" ]	[]	[]	[]
InfoVis	2,019	Text-to-Viz: Automatic Generation of Infographics from Proportion-Related Natural Language Statements	10.1109/TVCG.2019.2934785	Combining data content with visual embellishments, infographics can effectively deliver messages in an engaging and memorable manner. Various authoring tools have been proposed to facilitate the creation of infographics. However, creating a professional infographic with these authoring tools is still not an easy task, ...	false	false	[ "Weiwei Cui", "Xiaoyu Zhang", "Yun Wang 0012", "He Huang", "Bei Chen", "Lei Fang 0004", "Haidong Zhang", "Jian-Guang Lou", "Dongmei Zhang 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.09091v1", "icon": "paper" } ]
InfoVis	2,019	The Impact of Immersion on Cluster Identification Tasks	10.1109/TVCG.2019.2934395	Recent developments in technology encourage the use of head-mounted displays (HMDs) as a medium to explore visualizations in virtual realities (VRs). VR environments (VREs) enable new, more immersive visualization design spaces compared to traditional computer screens. Previous studies in different domains, such as med...	false	false	[ "Matthias Kraus", "Niklas Weiler", "Daniela Oelke", "Johannes Kehrer", "Daniel A. Keim", "Johannes Fuchs 0001" ]	[]	[]	[]
InfoVis	2,019	The Perceptual Proxies of Visual Comparison	10.1109/TVCG.2019.2934786	Perceptual tasks in visualizations often involve comparisons. Of two sets of values depicted in two charts, which set had values that were the highest overall? Which had the widest range? Prior empirical work found that the performance on different visual comparison tasks (e.g., “biggest delta”, “biggest correlation”) ...	false	false	[ "Nicole Jardine", "Brian D. Ondov", "Niklas Elmqvist", "Steven Franconeri" ]	[ "HM" ]	[]	[]
InfoVis	2,019	The Role of Latency and Task Complexity in Predicting Visual Search Behavior	10.1109/TVCG.2019.2934556	Latency in a visualization system is widely believed to affect user behavior in measurable ways, such as requiring the user to wait for the visualization system to respond, leading to interruption of the analytic flow. While this effect is frequently observed and widely accepted, precisely how latency affects different...	false	false	[ "Leilani Battle", "R. Jordan Crouser", "Audace Nakeshimana", "Ananda Montoly", "Remco Chang", "Michael Stonebraker" ]	[]	[]	[]
InfoVis	2,019	There Is No Spoon: Evaluating Performance, Space Use, and Presence with Expert Domain Users in Immersive Analytics	10.1109/TVCG.2019.2934803	Immersive analytics turns the very space surrounding the user into a canvas for data analysis, supporting human cognitive abilities in myriad ways. We present the results of a design study, contextual inquiry, and longitudinal evaluation involving professional economists using a Virtual Reality (VR) system for multidim...	false	false	[ "Andrea Batch", "Andrew Cunningham", "Maxime Cordeil", "Niklas Elmqvist", "Tim Dwyer", "Bruce H. Thomas", "Kim Marriott" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "https://osf.io/wzqbu", "icon": "paper" } ]
InfoVis	2,019	Toward Objective Evaluation of Working Memory in Visualizations: A Case Study Using Pupillometry and a Dual-Task Paradigm	10.1109/TVCG.2019.2934286	Cognitive science has established widely used and validated procedures for evaluating working memory in numerous applied domains, but surprisingly few studies have employed these methodologies to assess claims about the impacts of visualizations on working memory. The lack of information visualization research that use...	false	false	[ "Lace M. K. Padilla", "Spencer C. Castro", "P. Samuel Quinan", "Ian T. Ruginski", "Sarah H. Creem-Regehr" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "https://osf.io/zj6tp", "icon": "paper" } ]
InfoVis	2,019	Towards Automated Infographic Design: Deep Learning-based Auto-Extraction of Extensible Timeline	10.1109/TVCG.2019.2934810	Designers need to consider not only perceptual effectiveness but also visual styles when creating an infographic. This process can be difficult and time consuming for professional designers, not to mention non-expert users, leading to the demand for automated infographics design. As a first step, we focus on timeline i...	false	false	[ "Zhutian Chen", "Yun Wang 0012", "Qianwen Wang", "Yong Wang 0021", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.13550v3", "icon": "paper" } ]
InfoVis	2,019	Uncertainty-Aware Principal Component Analysis	10.1109/TVCG.2019.2934812	We present a technique to perform dimensionality reduction on data that is subject to uncertainty. Our method is a generalization of traditional principal component analysis (PCA) to multivariate probability distributions. In comparison to non-linear methods, linear dimensionality reduction techniques have the advantag...	false	false	[ "Jochen Görtler", "Thilo Spinner", "Dirk Streeb", "Daniel Weiskopf", "Oliver Deussen" ]	[]	[]	[]
InfoVis	2,019	VisTA: Integrating Machine Intelligence with Visualization to Support the Investigation of Think-Aloud Sessions	10.1109/TVCG.2019.2934797	Think-aloud protocols are widely used by user experience (UX) practitioners in usability testing to uncover issues in user interface design. It is often arduous to analyze large amounts of recorded think-aloud sessions and few UX practitioners have an opportunity to get a second perspective during their analysis due to...	false	false	[ "Mingming Fan 0001", "Ke Wu", "Jian Zhao 0010", "Yue Li", "Winter Wei", "Khai N. Truong" ]	[]	[]	[]
InfoVis	2,019	Visualizing a Moving Target: A Design Study on Task Parallel Programs in the Presence of Evolving Data and Concerns	10.1109/TVCG.2019.2934285	Common pitfalls in visualization projects include lack of data availability and the domain users' needs and focus changing too rapidly for the design process to complete. While it is often prudent to avoid such projects, we argue it can be beneficial to engage them in some cases as the visualization process can help re...	false	false	[ "Katy Williams", "Alex Bigelow", "Katherine E. Isaacs" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1905.13135v4", "icon": "paper" } ]
InfoVis	2,019	What is Interaction for Data Visualization?	10.1109/TVCG.2019.2934283	Interaction is fundamental to data visualization, but what “interaction” means in the context of visualization is ambiguous and confusing. We argue that this confusion is due to a lack of consensual definition. To tackle this problem, we start by synthesizing an inclusive view of interaction in the visualization commun...	false	false	[ "Evanthia Dimara", "Charles Perin" ]	[]	[]	[]
InfoVis	2,019	Why Authors Don't Visualize Uncertainty	10.1109/TVCG.2019.2934287	Clear presentation of uncertainty is an exception rather than rule in media articles, data-driven reports, and consumer applications, despite proposed techniques for communicating sources of uncertainty in data. This work considers, Why do so many visualization authors choose not to visualize uncertainty? I contribute ...	false	false	[ "Jessica Hullman" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.01697v1", "icon": "paper" } ]
InfoVis	2,019	Winglets: Visualizing Association with Uncertainty in Multi-class Scatterplots	10.1109/TVCG.2019.2934811	This work proposes Winglets, an enhancement to the classic scatterplot to better perceptually pronounce multiple classes by improving the perception of association and uncertainty of points to their related cluster. Designed as a pair of dual-sided strokes belonging to a data point, Winglets leverage the Gestalt princi...	false	false	[ "Min Lu 0002", "Shuaiqi Wang", "Joel Lanir", "Noa Fish", "Yang Yue", "Daniel Cohen-Or", "Hui Huang 0004" ]	[]	[]	[]
EuroVis	2,019	A framework for GPU-accelerated exploration of massive time-varying rectilinear scalar volumes	10.1111/cgf.13671	We introduce a novel flexible approach to spatiotemporal exploration of rectilinear scalar volumes. Our out‐of‐core representation, based on per‐frame levels of hierarchically tiled non‐redundant 3D grids, efficiently supports spatiotemporal random access and streaming to the GPU in compressed formats. A novel low‐bitr...	false	false	[ "Fabio Marton", "Marco Agus", "Enrico Gobbetti" ]	[ "HM" ]	[]	[]
EuroVis	2,019	A Geometric Optimization Approach for the Detection and Segmentation of Multiple Aneurysms	10.1111/cgf.13699	We present a method for detecting and segmenting aneurysms in blood vessels that facilitates the assessment of risks associated with the aneurysms. The detection and analysis of aneurysms is important for medical diagnosis as aneurysms bear the risk of rupture with fatal consequences for the patient. For risk assessmen...	false	false	[ "Kai Lawonn", "Monique Meuschke", "Ralph Wickenhöfer", "Bernhard Preim", "Klaus Hildebrandt" ]	[]	[]	[]
EuroVis	2,019	A Random Sampling O(n) Force-calculation Algorithm for Graph Layouts	10.1111/cgf.13724	This paper proposes a linear‐time repulsive‐force‐calculation algorithm with sub‐linear auxiliary space requirements, achieving an asymptotic improvement over the Barnes‐Hut and Fast Multipole Method force‐calculation algorithms. The algorithm, named random vertex sampling (RVS), achieves its speed by updating a random...	false	false	[ "Robert Gove" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "https://osf.io/2vpe4", "icon": "paper" } ]
EuroVis	2,019	A Review of Guidance Approaches in Visual Data Analysis: A Multifocal Perspective	10.1111/cgf.13730	Visual data analysis can be envisioned as a collaboration of the user and the computational system with the aim of completing a given task. Pursuing an effective system‐user integration, in which the system actively helps the user to reach his/her analysis goal has been focus of visualization research for quite some ti...	false	false	[ "Davide Ceneda", "Theresia Gschwandtner", "Silvia Miksch" ]	[]	[]	[]

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