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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 29	Award listlengths 0 2	Resources listlengths 0 5	ResourceLinks listlengths 0 10
CHI	2,020	How Visualizing Inferential Uncertainty Can Mislead Readers About Treatment Effects in Scientific Results	10.1145/3313831.3376454	When presenting visualizations of experimental results, scientists often choose to display either inferential uncertainty (e.g., uncertainty in the estimate of a population mean) or outcome uncertainty (e.g., variation of outcomes around that mean) about their estimates. How does this choice impact readers' beliefs abo...	false	false	[ "Jake M. Hofman", "Daniel G. Goldstein", "Jessica Hullman" ]	[ "HM" ]	[]	[]
CHI	2,020	InChorus: Designing Consistent Multimodal Interactions for Data Visualization on Tablet Devices	10.1145/3313831.3376782	While tablet devices are a promising platform for data visualization, supporting consistent interactions across different types of visualizations on tablets remains an open challenge. In this paper, we present multimodal interactions that function consistently across different visualizations, supporting common operatio...	false	false	[ "Arjun Srinivasan", "Bongshin Lee", "Nathalie Henry Riche", "Steven Mark Drucker", "Ken Hinckley" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2001.06423v1", "icon": "paper" } ]
CHI	2,020	Interacting with Literary Style through Computational Tools	10.1145/3313831.3376730	Style is an important aspect of writing, shaping how audiences interpret and engage with literary works. However, for most people style is difficult to articulate precisely. While users frequently interact with computational word processing tools with well-defined metrics, such as spelling and grammar checkers, style i...	false	false	[ "Sarah Sterman", "Evey Huang", "Vivian Liu", "Eric Paulos" ]	[]	[]	[]
CHI	2,020	Interaction Techniques for Visual Exploration Using Embedded Word-Scale Visualizations	10.1145/3313831.3376842	We describe a design space of view manipulation interactions for small data-driven contextual visualizations (word-scale visualizations). These interaction techniques support an active reading experience and engage readers through exploration of embedded visualizations whose placement and content connect them to specif...	false	false	[ "Pascal Goffin", "Tanja Blascheck", "Petra Isenberg", "Wesley Willett" ]	[]	[]	[]
CHI	2,020	Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning	10.1145/3313831.3376219	Machine learning (ML) models are now routinely deployed in domains ranging from criminal justice to healthcare. With this newfound ubiquity, ML has moved beyond academia and grown into an engineering discipline. To that end, interpretability tools have been designed to help data scientists and machine learning practiti...	false	false	[ "Harmanpreet Kaur", "Harsha Nori", "Samuel Jenkins", "Rich Caruana", "Hanna M. Wallach", "Jennifer Wortman Vaughan" ]	[ "HM" ]	[]	[]
CHI	2,020	Investigating Collaborative Exploration of Design Alternatives on a Wall-Sized Display	10.1145/3313831.3376736	Industrial design review is an iterative process which mainly relies on two steps involving many stakeholders: design discussion and CAD data adjustment. We investigate how a wall-sized display could be used to merge these two steps by allowing multidisciplinary collaborators to simultaneously generate and explore desi...	false	false	[ "Yujiro Okuya", "Olivier Gladin", "Nicolas Ladevèze", "Cédric Fleury", "Patrick Bourdot" ]	[]	[]	[]
CHI	2,020	MaraVis: Representation and Coordinated Intervention of Medical Encounters in Urban Marathon	10.1145/3313831.3376281	There is an increased use of Internet-of-Things and wearable sensing devices in the urban marathon to ensure effective response to unforeseen medical needs. However, the massive amount of real-time, heterogeneous movement and psychological data of runners impose great challenges on prompt medical incident analysis and ...	false	false	[ "Quan Li", "Huanbin Lin", "Xiguang Wei", "Yangkun Huang", "Lixin Fan", "Jian Du", "Xiaojuan Ma", "Tianjian Chen" ]	[]	[]	[]
CHI	2,020	Move Your Body: Engaging Museum Visitors with Human-Data Interaction	10.1145/3313831.3376186	Museums have embraced embodied interaction: its novelty generates buzz and excitement among their patrons, and it has enormous educational potential. Human-Data Interaction (HDI) is a class of embodied interactions that enables people to explore large sets of data using interactive visualizations that users control wit...	false	false	[ "Milka Trajkova", "A'aeshah Alhakamy", "Francesco Cafaro", "Rashmi Mallappa", "Sreekanth R. Kankara" ]	[]	[]	[]
CHI	2,020	MRAT: The Mixed Reality Analytics Toolkit	10.1145/3313831.3376330	Significant tool support exists for the development of mixed reality (MR) applications; however, there is a lack of tools for analyzing MR experiences. We elicit requirements for future tools through interviews with 8 university research, instructional, and media teams using AR/VR in a variety of domains. While we find...	false	false	[ "Michael Nebeling", "Maximilian Speicher", "Xizi Wang", "Shwetha Rajaram", "Brian D. Hall", "Zijian Xie", "Alexander R. E. Raistrick", "Michelle Aebersold", "Edward G. Happ", "Jiayin Wang", "Yanan Sun", "Lotus Zhang", "Leah E. Ramsier", "Rhea Kulkarni" ]	[ "BP" ]	[]	[]
CHI	2,020	Paths Explored, Paths Omitted, Paths Obscured: Decision Points & Selective Reporting in End-to-End Data Analysis	10.1145/3313831.3376533	Drawing reliable inferences from data involves many, sometimes arbitrary, decisions across phases of data collection, wrangling, and modeling. As different choices can lead to diverging conclusions, understanding how researchers make analytic decisions is important for supporting robust and replicable analysis. In this...	false	false	[ "Yang Liu 0136", "Tim Althoff", "Jeffrey Heer" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1910.13602v3", "icon": "paper" } ]
CHI	2,020	Prior Setting in Practice: Strategies and Rationales Used in Choosing Prior Distributions for Bayesian Analysis	10.1145/3313831.3376377	Bayesian statistical analysis is steadily growing in popularity and use. Choosing priors is an integral part of Bayesian inference. While there exist extensive normative recommendations for prior setting, little is known about how priors are chosen in practice. We conducted a survey (N = 50) and interviews (N = 9) wher...	false	false	[ "Abhraneel Sarma", "Matthew Kay 0001" ]	[]	[]	[]
CHI	2,020	Progression Maps: Conceptualizing Narrative Structure for Interaction Design Support	10.1145/3313831.3376527	Interactive narratives are frequently designed for learning and training applications, such as social training. In these contexts, designers may be inexperienced in storytelling and interaction design, and it may be difficult to quickly build an effective experience, even for experienced designers. Designers often appr...	false	false	[ "Elín Carstensdóttir", "Nathan Partlan", "Steven C. Sutherland", "Tyler Duke", "Erika Ferris", "Robin M. Richter", "Maria Jose Valladares", "Magy Seif El-Nasr" ]	[]	[]	[]
CHI	2,020	Projection Boxes: On-the-fly Reconfigurable Visualization for Live Programming	10.1145/3313831.3376494	Live programming is a regime in which the programming environment provides continual feedback, most often in the form of runtime values. In this paper, we present Projection Boxes, a novel visualization technique for displaying runtime values of programs. The key idea behind projection boxes is to start with a full sem...	false	false	[ "Sorin Lerner" ]	[]	[]	[]
CHI	2,020	Pushing the (Visual) Narrative: The Effects of Prior Knowledge Elicitation in Provocative Topics	10.1145/3313831.3376887	Narrative visualization is a popular style of data-driven storytelling. Authors use this medium to engage viewers with complex and sometimes controversial issues. A challenge for authors is to not only deliver new information, but to also overcome people's biases and misconceptions. We study how people adjust their att...	false	false	[ "Jeremy Heyer", "Nirmal Kumar Raveendranath", "Khairi Reda" ]	[]	[]	[]
CHI	2,020	QMaps: Engaging Students in Voluntary Question Generation and Linking	10.1145/3313831.3376882	Generating multiple-choice questions is known to improve students' critical thinking and deep learning. Visualizing relationships between concepts enhances meaningful learning, students' ability to relate new concepts to previously learned concepts. We designed and deployed a collaborative learning process through whic...	false	false	[ "Iman YeckehZaare", "Tirdad Barghi", "Paul Resnick" ]	[]	[]	[]
CHI	2,020	RunAhead: Exploring Head Scanning based Navigation for Runners	10.1145/3313831.3376828	Navigation systems for runners commonly provide turn-by-turn directions via voice and/or map-based visualizations. While voice directions require permanent attention, map-based guidance requires regular consultation. Both disrupt the running activity. To address this, we designed RunAhead, a navigation system using hea...	false	false	[ "Danilo Gallo", "Shreepriya Shreepriya", "Jutta Willamowski" ]	[]	[]	[]
CHI	2,020	See, Feel, Move: Player Behaviour Analysis through Combined Visualization of Gaze, Emotions, and Movement	10.1145/3313831.3376401	Playtesting of games often relies on a mixed-methods approach to obtain more holistic insights about and, in turn, improve the player experience. However, triangulating the different data sources and visualizing them in an integrated manner such that they contextualize each other still proves challenging. Despite its p...	false	false	[ "Daniel Kepplinger", "Günter Wallner", "Simone Kriglstein", "Michael Lankes" ]	[ "HM" ]	[]	[]
CHI	2,020	Surfacing Visualization Mirages	10.1145/3313831.3376420	Dirty data and deceptive design practices can undermine, invert, or invalidate the purported messages of charts and graphs. These failures can arise silently: a conclusion derived from a particular visualization may look plausible unless the analyst looks closer and discovers an issue with the backing data, visual spec...	false	false	[ "Andrew M. McNutt", "Gordon L. Kindlmann", "Michael Correll" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2001.02316v1", "icon": "paper" } ]
CHI	2,020	Tactile Presentation of Network Data: Text, Matrix or Diagram?	10.1145/3313831.3376367	Visualisations are commonly used to understand social, biological and other kinds of networks. Currently we do not know how to effectively present network data to people who are blind or have low-vision (BLV). We ran a controlled study with 8 BLV participants comparing four tactile representations: organic node-link di...	false	false	[ "Yalong Yang 0001", "Kim Marriott", "Matthew Butler 0002", "Cagatay Goncu", "Leona Holloway" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2003.14274v1", "icon": "paper" } ]
CHI	2,020	Techniques for Flexible Responsive Visualization Design	10.1145/3313831.3376777	Responsive visualizations adapt to effectively present information based on the device context. Such adaptations are essential for news content that is increasingly consumed on mobile devices. However, existing tools provide little support for responsive visualization design. We analyze a corpus of 231 responsive news ...	false	false	[ "Jane Hoffswell", "Wilmot Li", "Zhicheng Liu 0001" ]	[ "BP" ]	[]	[]
CHI	2,020	Toward Automated Feedback on Teacher Discourse to Enhance Teacher Learning	10.1145/3313831.3376418	Like anyone, teachers need feedback to improve. Due to the high cost of human classroom observation, teachers receive infrequent feedback which is often more focused on evaluating performance than on improving practice. To address this critical barrier to teacher learning, we aim to provide teachers with detailed and a...	false	false	[ "Emily Jensen", "Meghan Dale", "Patrick J. Donnelly", "Cathlyn Stone", "Sean Kelly", "Amanda Godley", "Sidney K. D'Mello" ]	[]	[]	[]
CHI	2,020	Towards an Understanding of Augmented Reality Extensions for Existing 3D Data Analysis Tools	10.1145/3313831.3376657	We present an observational study with domain experts to understand how augmented reality (AR) extensions to traditional PC-based data analysis tools can help particle physicists to explore and understand 3D data. Our goal is to allow researchers to integrate stereoscopic AR-based visual representations and interaction...	false	false	[ "Xiyao Wang", "Lonni Besançon", "David Rousseau", "Mickaël Sereno", "Mehdi Ammi", "Tobias Isenberg 0001" ]	[]	[]	[]
CHI	2,020	Truncating the Y-Axis: Threat or Menace?	10.1145/3313831.3376222	Bar charts with y-axes that don't begin at zero can visually exaggerate effect sizes. However, advice for whether or not to truncate the y-axis can be equivocal for other visualization types. In this paper we present examples of visualizations where this y-axis truncation can be beneficial as well as harmful, depending...	false	false	[ "Michael Correll", "Enrico Bertini", "Steven Franconeri" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.02035v2", "icon": "paper" } ]
CHI	2,020	Understanding and Visualizing Data Iteration in Machine Learning	10.1145/3313831.3376177	Successful machine learning (ML) applications require iterations on both modeling and the underlying data. While prior visualization tools for ML primarily focus on modeling, our interviews with 23 ML practitioners reveal that they improve model performance frequently by iterating on their data (e.g., collecting new da...	false	false	[ "Fred Hohman", "Kanit Wongsuphasawat", "Mary Beth Kery", "Kayur Patel" ]	[]	[]	[]
CHI	2,020	Unwind: Interactive Fish Straightening	10.1145/3313831.3376846	The ScanAllFish project is a large-scale effort to scan all the world's 33,100 known species of fishes. It has already generated thousands of volumetric CT scans of fish species which are available on open access platforms such as the Open Science Framework. To achieve a scanning rate required for a project of this mag...	false	false	[ "Francis Williams", "Alexander Bock 0002", "Harish Doraiswamy", "Cassandra M. Donatelli", "Kayla Hall", "Adam Summers", "Daniele Panozzo", "Cláudio T. Silva" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1904.04890v2", "icon": "paper" } ]
CHI	2,020	Watch+Strap: Extending Smartwatches with Interactive StrapDisplays	10.1145/3313831.3376199	While smartwatches are widely adopted these days, their input and output space remains fairly limited by their screen size. We present StrapDisplays-interactive watchbands with embedded display and touch technologies-that enhance commodity watches and extend their input and output capabilities. After introducing the ph...	false	false	[ "Konstantin Klamka", "Tom Horak", "Raimund Dachselt" ]	[]	[]	[]
CHI	2,020	What's Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities	10.1145/3313831.3376729	Computational notebooks - such as Azure, Databricks, and Jupyter - are a popular, interactive paradigm for data scientists to author code, analyze data, and interleave visualizations, all within a single document. Nevertheless, as data scientists incorporate more of their activities into notebooks, they encounter unexp...	false	false	[ "Souti Chattopadhyay", "Ishita Prasad", "Austin Z. Henley", "Anita Sarma", "Titus Barik" ]	[ "HM" ]	[]	[]
CHI	2,020	Would you do it?: Enacting Moral Dilemmas in Virtual Reality for Understanding Ethical Decision-Making	10.1145/3313831.3376788	A moral dilemma is a decision-making paradox without unambiguously acceptable or preferable options. This paper investigates if and how the virtual enactment of two renowned moral dilemmas---the Trolley and the Mad Bomber---influence decision-making when compared with mentally visualizing such situations. We conducted ...	false	false	[ "Evangelos Niforatos", "Adam Palma", "Roman Gluszny", "Athanasios Vourvopoulos", "Fotis Liarokapis" ]	[]	[]	[]
VAST	2,019	A Natural-language-based Visual Query Approach of Uncertain Human Trajectories	10.1109/TVCG.2019.2934671	Visual querying is essential for interactively exploring massive trajectory data. However, the data uncertainty imposes profound challenges to fulfill advanced analytics requirements. On the one hand, many underlying data does not contain accurate geographic coordinates, e.g., positions of a mobile phone only refer to ...	false	false	[ "Zhaosong Huang", "Ye Zhao 0003", "Wei Chen 0001", "Shengjie Gao", "Kejie Yu", "Weixia Xu", "MingJie Tang", "Min-Feng Zhu", "Mingliang Xu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00277v2", "icon": "paper" } ]
VAST	2,019	Ablate, Variate, and Contemplate: Visual Analytics for Discovering Neural Architectures	10.1109/TVCG.2019.2934261	The performance of deep learning models is dependent on the precise configuration of many layers and parameters. However, there are currently few systematic guidelines for how to configure a successful model. This means model builders often have to experiment with different configurations by manually programming differ...	false	false	[ "Dylan Cashman", "Adam Perer", "Remco Chang", "Hendrik Strobelt" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00387v1", "icon": "paper" } ]
VAST	2,019	AirVis: Visual Analytics of Air Pollution Propagation	10.1109/TVCG.2019.2934670	Air pollution has become a serious public health problem for many cities around the world. To find the causes of air pollution, the propagation processes of air pollutants must be studied at a large spatial scale. However, the complex and dynamic wind fields lead to highly uncertain pollutant transportation. The state-...	false	false	[ "Zikun Deng", "Di Weng", "Jiahui Chen", "Ren Liu", "Zhibin Wang", "Jie Bao 0003", "Yu Zheng 0004", "Yingcai Wu" ]	[]	[]	[]
VAST	2,019	CloudDet: Interactive Visual Analysis of Anomalous Performances in Cloud Computing Systems	10.1109/TVCG.2019.2934613	Detecting and analyzing potential anomalous performances in cloud computing systems is essential for avoiding losses to customers and ensuring the efficient operation of the systems. To this end, a variety of automated techniques have been developed to identify anomalies in cloud computing. These techniques are usually...	false	false	[ "Ke Xu", "Yun Wang 0012", "Leni Yang", "Yifang Wang 0001", "Bo Qiao 0001", "Si Qin", "Yong Xu", "Haidong Zhang", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.13187v1", "icon": "paper" } ]
VAST	2,019	CourtTime: Generating Actionable Insights into Tennis Matches Using Visual Analytics	10.1109/TVCG.2019.2934243	Tennis players and coaches of all proficiency levels seek to understand and improve their play. Summary statistics alone are inadequate to provide the insights players need to improve their games. Spatio-temporal data capturing player and ball movements is likely to provide the actionable insights needed to identify pl...	false	false	[ "Tom Polk", "Dominik Jäckle", "Johannes Häußler", "Jing Yang" ]	[]	[]	[]
VAST	2,019	Do What I Mean, Not What I Say! Design Considerations for Supporting Intent and Context in Analytical Conversation	10.1109/VAST47406.2019.8986918	Natural language can be a useful modality for creating and interacting with visualizations but users often have unrealistic expectations about the intelligence of natural language systems. The gulf between user expectations and system capabilities may lead to a disappointing user experience. So - if we want to engineer...	false	false	[ "Melanie Tory", "Vidya Setlur" ]	[]	[]	[]
VAST	2,019	EmoCo: Visual Analysis of Emotion Coherence in Presentation Videos	10.1109/TVCG.2019.2934656	Emotions play a key role in human communication and public presentations. Human emotions are usually expressed through multiple modalities. Therefore, exploring multimodal emotions and their coherence is of great value for understanding emotional expressions in presentations and improving presentation skills. However, ...	false	false	[ "Haipeng Zeng", "Xingbo Wang 0001", "Aoyu Wu", "Yong Wang 0021", "Quan Li", "Alex Endert", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.12918v2", "icon": "paper" } ]
VAST	2,019	Evaluating Perceptual Bias During Geometric Scaling of Scatterplots	10.1109/TVCG.2019.2934208	Scatterplots are frequently scaled to fit display areas in multi-view and multi-device data analysis environments. A common method used for scaling is to enlarge or shrink the entire scatterplot together with the inside points synchronously and proportionally. This process is called geometric scaling. However, geometri...	false	false	[ "Yating Wei", "Honghui Mei", "Ying Zhao 0001", "Shuyue Zhou", "Bingru Lin", "Haojing Jiang", "Wei Chen 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00403v2", "icon": "paper" } ]
VAST	2,019	explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning	10.1109/TVCG.2019.2934629	We propose a framework for interactive and explainable machine learning that enables users to (1) understand machine learning models; (2) diagnose model limitations using different explainable AI methods; as well as (3) refine and optimize the models. Our framework combines an iterative XAI pipeline with eight global m...	false	false	[ "Thilo Spinner", "Udo Schlegel", "Hanna Hauptmann", "Mennatallah El-Assady" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00087v2", "icon": "paper" } ]
VAST	2,019	Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics	10.1109/TVCG.2019.2934631	Machine learning models are currently being deployed in a variety of real-world applications where model predictions are used to make decisions about healthcare, bank loans, and numerous other critical tasks. As the deployment of artificial intelligence technologies becomes ubiquitous, it is unsurprising that adversari...	false	false	[ "Yuxin Ma", "Tiankai Xie", "Jundong Li", "Ross Maciejewski" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.07296v4", "icon": "paper" } ]
VAST	2,019	Exploranative Code Quality Documents	10.1109/TVCG.2019.2934669	Good code quality is a prerequisite for efficiently developing maintainable software. In this paper, we present a novel approach to generate exploranative (explanatory and exploratory) data-driven documents that report code quality in an interactive, exploratory environment. We employ a template-based natural language ...	false	false	[ "Haris Mumtaz", "Shahid Latif", "Fabian Beck 0001", "Daniel Weiskopf" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.11481v2", "icon": "paper" } ]
VAST	2,019	Facetto: Combining Unsupervised and Supervised Learning for Hierarchical Phenotype Analysis in Multi-Channel Image Data	10.1109/TVCG.2019.2934547	Facetto is a scalable visual analytics application that is used to discover single-cell phenotypes in high-dimensional multi-channel microscopy images of human tumors and tissues. Such images represent the cutting edge of digital histology and promise to revolutionize how diseases such as cancer are studied, diagnosed,...	false	false	[ "Robert Krüger", "Johanna Beyer", "Won-Dong Jang", "Nam Wook Kim", "Artem Sokolov", "Peter K. Sorger", "Hanspeter Pfister" ]	[]	[]	[]
VAST	2,019	FairSight: Visual Analytics for Fairness in Decision Making	10.1109/TVCG.2019.2934262	Data-driven decision making related to individuals has become increasingly pervasive, but the issue concerning the potential discrimination has been raised by recent studies. In response, researchers have made efforts to propose and implement fairness measures and algorithms, but those efforts have not been translated ...	false	false	[ "Yongsu Ahn", "Yu-Ru Lin" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00176v2", "icon": "paper" } ]
VAST	2,019	FAIRVIS: Visual Analytics for Discovering Intersectional Bias in Machine Learning	10.1109/VAST47406.2019.8986948	The growing capability and accessibility of machine learning has led to its application to many real-world domains and data about people. Despite the benefits algorithmic systems may bring, models can reflect, inject, or exacerbate implicit and explicit societal biases into their outputs, disadvantaging certain demogra...	false	false	[ "Ángel Alexander Cabrera", "Will Epperson", "Fred Hohman", "Minsuk Kahng", "Jamie Morgenstern", "Polo Chau" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1904.05419v4", "icon": "paper" } ]
VAST	2,019	FDive: Learning Relevance Models Using Pattern-based Similarity Measures	10.1109/VAST47406.2019.8986940	The detection of interesting patterns in large high-dimensional datasets is difficult because of their dimensionality and pattern complexity. Therefore, analysts require automated support for the extraction of relevant patterns. In this paper, we present FDive, a visual active learning system that helps to create visua...	false	false	[ "Frederik L. Dennig", "Tom Polk", "Zudi Lin", "Tobias Schreck", "Hanspeter Pfister", "Michael Behrisch 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.12489v3", "icon": "paper" } ]
VAST	2,019	FlowSense: A Natural Language Interface for Visual Data Exploration within a Dataflow System	10.1109/TVCG.2019.2934668	Dataflow visualization systems enable flexible visual data exploration by allowing the user to construct a dataflow diagram that composes query and visualization modules to specify system functionality. However learning dataflow diagram usage presents overhead that often discourages the user. In this work we design Flo...	false	false	[ "Bowen Yu 0004", "Cláudio T. Silva" ]	[ "BP" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.00681v2", "icon": "paper" } ]
VAST	2,019	Galex: Exploring the Evolution and Intersection of Disciplines	10.1109/TVCG.2019.2934667	Revealing the evolution of science and the intersections among its sub-fields is extremely important to understand the characteristics of disciplines, discover new topics, and predict the future. The current work focuses on either building the skeleton of science, lacking interaction, detailed exploration and interpret...	false	false	[ "Zeyu Li 0003", "Changhong Zhang", "Shichao Jia", "Jiawan Zhang" ]	[]	[]	[]
VAST	2,019	GPGPU Linear Complexity t-SNE Optimization	10.1109/TVCG.2019.2934307	In recent years the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm has become one of the most used and insightful techniques for exploratory data analysis of high-dimensional data. It reveals clusters of high-dimensional data points at different scales while only requiring minimal tuning of its parameter...	false	false	[ "Nicola Pezzotti", "Julian Thijssen", "Alexander Mordvintsev", "Thomas Höllt", "Baldur van Lew", "Boudewijn P. F. Lelieveldt", "Elmar Eisemann", "Anna Vilanova" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1805.10817v2", "icon": "paper" } ]
VAST	2,019	GUIRO: User-Guided Matrix Reordering	10.1109/TVCG.2019.2934300	Matrix representations are one of the main established and empirically proven to be effective visualization techniques for relational (or network) data. However, matrices—similar to node-link diagrams—are most effective if their layout reveals the underlying data topology. Given the many developed algorithms, a practic...	false	false	[ "Michael Behrisch 0001", "Tobias Schreck", "Hanspeter Pfister" ]	[]	[]	[]
VAST	2,019	ICE: An Interactive Configuration Explorer for High Dimensional Categorical Parameter Spaces	10.1109/VAST47406.2019.8986923	There are many applications where users seek to explore the impact of the settings of several categorical variables with respect to one dependent numerical variable. For example, a computer systems analyst might want to study how the type of file system or storage device affects system performance. A usual choice is th...	false	false	[ "Anjul Tyagi", "Zhen Cao", "Tyler Estro", "Erez Zadok", "Klaus Mueller 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.12627v2", "icon": "paper" } ]
VAST	2,019	Influence Flowers of Academic Entities	10.1109/VAST47406.2019.8986934	We present the Influence Flower, a new visual metaphor for the influence profile of academic entities, including people, projects, institutions, conferences, and journals. While many tools quantify influence, we aim to expose the flow of influence between entities. The Influence Flower is an ego-centric graph, with a q...	false	false	[ "Minjeong Shin", "Alexander Soen", "Benjamin T. Readshaw", "Steve Blackburn", "Mitchell Whitelaw", "Lexing Xie" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.12748v1", "icon": "paper" } ]
VAST	2,019	Interactive Correction of Mislabeled Training Data	10.1109/VAST47406.2019.8986943	In this paper, we develop a visual analysis method for interactively improving the quality of labeled data, which is essential to the success of supervised and semi-supervised learning. The quality improvement is achieved through the use of user-selected trusted items. We employ a bi-level optimization model to accurat...	false	false	[ "Shouxing Xiang", "Xi Ye", "Jiazhi Xia", "Jing Wu 0004", "Yang Chen", "Shixia Liu" ]	[]	[]	[]
VAST	2,019	Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awareness	10.1109/TVCG.2019.2934614	Various domain users are increasingly leveraging real-time social media data to gain rapid situational awareness. However, due to the high noise in the deluge of data, effectively determining semantically relevant information can be difficult, further complicated by the changing definition of relevancy by each end user...	false	false	[ "Luke S. Snyder", "Yi-Shan Lin", "Morteza Karimzadeh", "Dan Goldwasser", "David S. Ebert" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1908.02588v2", "icon": "paper" } ]
VAST	2,019	LightGuider: Guiding Interactive Lighting Design using Suggestions, Provenance, and Quality Visualization	10.1109/TVCG.2019.2934658	LightGuider is a novel guidance-based approach to interactive lighting design, which typically consists of interleaved 3D modeling operations and light transport simulations. Rather than having designers use a trial-and-error approach to match their illumination constraints and aesthetic goals, LightGuider supports the...	false	false	[ "Andreas Walch", "Michael Schwärzler", "Christian Luksch", "Elmar Eisemann", "Theresia Gschwandtner" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.08553v2", "icon": "paper" } ]
VAST	2,019	MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety Agencies	10.1109/TVCG.2019.2934603	Evaluating employee performance in organizations with varying workloads and tasks is challenging. Specifically, it is important to understand how quantitative measurements of employee achievements relate to supervisor expectations, what the main drivers of good performance are, and how to combine these complex and flex...	false	false	[ "Jieqiong Zhao", "Morteza Karimzadeh", "Luke S. Snyder", "Chittayong Surakitbanharn", "Cheryl Z. Qian", "David S. Ebert" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.13601v3", "icon": "paper" } ]
VAST	2,019	Motion Browser: Visualizing and Understanding Complex Upper Limb Movement Under Obstetrical Brachial Plexus Injuries	10.1109/TVCG.2019.2934280	The brachial plexus is a complex network of peripheral nerves that enables sensing from and control of the movements of the arms and hand. Nowadays, the coordination between the muscles to generate simple movements is still not well understood, hindering the knowledge of how to best treat patients with this type of per...	false	false	[ "Gromit Yeuk-Yin Chan", "Luis Gustavo Nonato", "Alice Chu", "Preeti Raghavan", "Viswanath Aluru", "Cláudio T. Silva" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.09146v1", "icon": "paper" } ]
VAST	2,019	NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation	10.1109/TVCG.2019.2934591	Complex computational models are often designed to simulate real-world physical phenomena in many scientific disciplines. However, these simulation models tend to be computationally very expensive and involve a large number of simulation input parameters, which need to be analyzed and properly calibrated before the mod...	false	false	[ "Subhashis Hazarika", "Haoyu Li", "Ko-Chih Wang", "Han-Wei Shen", "Ching-Shan Chou" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1904.09044v3", "icon": "paper" } ]
VAST	2,019	OD Morphing: Balancing Simplicity with Faithfulness for OD Bundling	10.1109/TVCG.2019.2934657	OD bundling is a promising method to identify key origin-destination (OD) patterns, but the bundling can mislead the interpretation of actual trajectories traveled. We present OD Morphing, an interactive OD bundling technique that improves geographical faithfulness to actual trajectories while preserving visual simplic...	false	false	[ "Yan Lyu", "Xu Liu 0014", "Hanyi Chen", "Arpan Mangal", "Kai Liu 0001", "Chao Chen 0004", "Brian Y. Lim" ]	[]	[]	[]
VAST	2,019	Origraph: Interactive Network Wrangling	10.1109/VAST47406.2019.8986909	Networks are a natural way of thinking about many datasets. The data on which a network is based, however, is rarely collected in a form that suits the analysis process, making it necessary to create and reshape networks. Data wrangling is widely acknowledged to be a critical part of the data analysis pipeline, yet int...	false	false	[ "Alex Bigelow", "Carolina Nobre", "Miriah D. Meyer", "Alexander Lex" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1812.06337v3", "icon": "paper" } ]
VAST	2,019	PlanningVis: A Visual Analytics Approach to Production Planning in Smart Factories	10.1109/TVCG.2019.2934275	Production planning in the manufacturing industry is crucial for fully utilizing factory resources (e.g., machines, raw materials and workers) and reducing costs. With the advent of industry 4.0, plenty of data recording the status of factory resources have been collected and further involved in production planning, wh...	false	false	[ "Dong Sun 0001", "Renfei Huang", "Yuanzhe Chen", "Yong Wang 0021", "Jia Zeng", "Mingxuan Yuan", "Ting-Chuen Pong", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.12201v3", "icon": "paper" } ]
VAST	2,019	ProtoSteer: Steering Deep Sequence Model with Prototypes	10.1109/TVCG.2019.2934267	Recently we have witnessed growing adoption of deep sequence models (e.g. LSTMs) in many application domains, including predictive health care, natural language processing, and log analysis. However, the intricate working mechanism of these models confines their accessibility to the domain experts. Their black-box natu...	false	false	[ "Yao Ming", "Panpan Xu", "Furui Cheng", "Huamin Qu", "Ren Liu" ]	[]	[]	[]
VAST	2,019	R-Map: A Map Metaphor for Visualizing Information Reposting Process in Social Media	10.1109/TVCG.2019.2934263	We propose R-Map (Reposting Map), a visual analytical approach with a map metaphor to support interactive exploration and analysis of the information reposting process in social media. A single original social media post can cause large cascades of repostings (i.e., retweets) on online networks, involving thousands, ev...	false	false	[ "Shuai Chen 0001", "Sihang Li", "Siming Chen 0001", "Xiaoru Yuan" ]	[]	[]	[]
VAST	2,019	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications	10.1109/TVCG.2019.2934594	With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization. First, the utilization of black box models (e.g., deep neural networks) calls for advanced techniques in exploring and interpreting model behavio...	false	false	[ "Shusen Liu", "Jim Gaffney", "Jayson Luc Peterson", "Peter B. Robinson", "Harsh Bhatia", "Valerio Pascucci", "Brian K. Spears", "Peer-Timo Bremer", "Di Wang", "Dan Maljovec", "Rushil Anirudh", "Jayaraman J. Thiagarajan", "Sam Ade Jacobs", "Brian Van Essen", "David Hysom", "Jae-Seung Ye...	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1907.08325v1", "icon": "paper" } ]
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" } ]

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