anchor.diff:  TVCG,TVCG,Smart Brushing for Parallel Coordinates,T),"Richard Roberts, Robert S Laramee, Gary A Smith, Paul Brookes, Tony D'Cruze",http://cs.swan.ac.uk/~csbob/research/callCenter/brushing/roberts18smart.pdf,"The Parallel Coordinates plot is a popular tool for the visualization of high-dimensional data. One of the main challenges when using parallel coordinates is occlusion and overplotting resulting from large data sets. Brushing is a popular approach to address these challenges. Since its conception, limited improvements have been made to brushing both in the form of visual design and functional interaction. We present a set of novel, smart brushing techniques that enhance the standard interactive brushing of a parallel coordinates plot. We introduce two new interaction concepts: Higher-order, sketch-based brushing, and smart, data-driven brushing. Higher-order brushes support interactive, flexible, n-dimensional pattern searches involving an arbitrary number of dimensions. Smart, data-driven brushing provides interactive, real-time guidance to the user during the brushing process based on derived meta-data. In addition, we implement a selection of novel enhancements and user options that complement the two techniques as well as enhance the exploration and analytical ability of the user. We demonstrate the utility and evaluate the results using a case study with a large, high-dimensional, real-world telecommunication data set and we report domain expert feedback from the data suppliers.",,,,,vimeo 289789480,10.1109/tvcg.2018.2808969,2018,2018,InfoVis,Estrel Hall C,Thursday,Interaction,25-Oct,11:40 AM,12:00 PM
   TVCG,TVCG,"Multidimensional Projection for Visual Analytics: Linking Techniques with Distortions, Tasks, and Layout Enrichment ",T),Luis Gustavo Nonato and Michael Aupetit,http://www.lcad.icmc.usp.br/~nonato/pubs/mdp-survey.pdf,"Visual analysis of multidimensional data requires expressive and effective ways to reduce data dimensionality to encode them visually. Multidimensional projections (MDP) figure among the most important visualization techniques in this context, transforming multidimensional data into scatter plots whose visual patterns reflect some notion of similarity in the original data. However, MDP come with distortions that make these visual patterns not trustworthy, hindering users to infer actual data characteristics. Moreover, the patterns present in the scatter plots might not be enough to allow a clear understanding of multidimensional data, motivating the development of layout enrichment methodologies to operate together with MDP. This survey attempts to cover the main aspects of MDP as a visualization and visual analytic tool. It provides detailed analysis and taxonomies as to the organization of MDP techniques according to their main properties and traits, discussing the impact of such properties for visual perception and other human factors. The survey also approaches the different types of distortions that can result from MDP mappings and it overviews existing mechanisms to quantitatively evaluate such distortions. A qualitative analysis of the impact of distortions on the different analytic tasks performed by users when exploring multidimensional data through MDP is also presented. Guidelines for choosing the best MDP for an intended task are also provided as a result of this analysis. Finally, layout enrichment schemes to debunk MDP distortions and/or reveal relevant information not directly inferable from the scatter plot are reviewed and discussed in the light of new taxonomies. We conclude the survey providing future research axes to fill discovered gaps in this domain.",,,,,vimeo 289789153,10.1109/tvcg.2018.2846735,2018,2018,InfoVis,Estrel Hall C,Thursday,Interaction,25-Oct,12:00 PM,12:20 PM
   TVCG,TVCG,Exploration Strategies for Discovery of Interactivity in Visualizations,T),"Tanja Blascheck, Lindsay MacDonald Vermeulen, Jo Vermeulen, Charles Perin, Wesley Willett, Thomas Ertl, Sheelagh Carpendale",https://hal.archives-ouvertes.fr/hal-01705792/document,"We investigate how people discover the functionality of an interactive visualization that was designed for the general public. While interactive visualizations are increasingly available for public use, we still know little about how the general public discovers what they can do with these visualizations and what interactions are available. Developing a better understanding of this discovery process can help inform the design of visualizations for the general public, which in turn can help make data more accessible. To unpack this problem, we conducted a lab study in which participants were free to use their own methods to discover the functionality of a connected set of interactive visualizations of public energy data. We collected eye movement data and interaction logs as well as video and audio recordings. By analyzing this combined data, we extract exploration strategies that the participants employed to discover the functionality in these interactive visualizations. These exploration strategies illuminate possible design directions for improving the discoverability of a visualization's functionality.",,,http://innovis.cpsc.ucalgary.ca/supplemental/Exploration-Strategies/#data,,vimeo 289789025,10.1109/tvcg.2018.2802520,2018,2018,InfoVis,Estrel Hall C,Thursday,Interaction,25-Oct,12:20 PM,12:40 PM
  -CG&A,CGA,OpenSpace: Changing the Narrative of Public Dissemination in Astronomical Visualization from What to How,,"Alexander Bock, Emil Axelsson, Carter Emmart, Masha Kuznetsova, Charles Hansen, Anders Ynnerman",,,,,,,vimeo 289785793,10.1109/mcg.2018.032421653,2018,2018,Other,Room III,Thursday,CG&A Session 2,25-Oct,11:00 AM,11:20 AM
  +CG&A,CGA,OpenSpace: Changing the Narrative of Public Dissemination in Astronomical Visualization from What to How,,"Alexander Bock, Emil Axelsson, Carter Emmart, Masha Kuznetsova, Charles Hansen, Anders Ynnerman",http://www.sci.utah.edu/publications/Boc2018a/08370192.pdf,"This article presents the development of open-source software called OpenSpace that bridges the gap between scientific discoveries and public dissemination and thus paves the way for the next generation of science communication and data exploration. The article describes how the platform enables interactive presentations of dynamic and timevarying processes by domain experts to the general public. The concepts are demonstrated through four cases: Image acquisitions of the New Horizons and Rosetta spacecraft, the dissemination of space weather phenomena, and the display of highresolution planetary images. Each case has been presented at public events with great success. These cases highlight the details of data acquisition, rather than presenting the final results, showing the audience the value of supporting the efforts of the scientific discovery. ",,,,,vimeo 289785793,10.1109/mcg.2018.032421653,2018,2018,Other,Room III,Thursday,CG&A Session 2,25-Oct,11:00 AM,11:20 AM
   CG&A,CGA,Belle2VR: A Virtual-Reality Visualization of Subatomic Particle Physics in the Belle II Experiment,,"Zach Duer, Leo Piilonen, and George Glasson",,,,,,,vimeo 289785809,10.1109/mcg.2018.032421652,2018,2018,Other,Room III,Thursday,CG&A Session 2,25-Oct,11:20 AM,11:40 AM
   CG&A,CGA,Application-Driven Design: Help Students Understand Employment and See the “Big Picture”,,"Li Liu, Deborah Silver, Karen Bemis",,,,,,,vimeo 289785826,10.1109/mcg.2018.032421656,2018,2018,Other,Room III,Thursday,CG&A Session 2,25-Oct,11:40 AM,12:00 PM
   CG&A,CGA,Management of Cerebral Aneurysm Descriptors based on an Automatic Ostium Extraction,,"Monique Meuschke, Tobias Günther, Ralph Wickenhöfer, Markus Gross, Bernhard Preim, Kai Lawonn",https://cgl.ethz.ch/Downloads/Publications/Papers/2018/Meu18a/Meu18a.pdf,"We present a framework to manage cerebral aneurysms. Rupture risk evaluation is based on manually extracted descriptors, which is timeconsuming. Thus, we provide an automatic solution by considering several questions: How can expert knowledge be integrated? How should metadata be defined? Which interaction techniques are needed for data exploration?",,,,,vimeo 289785840,10.1109/mcg.2018.032421654,2018,2018,Other,Room III,Thursday,CG&A Session 2,25-Oct,12:00 PM,12:20 PM
  -CG&A,CGA,Toward a Multimodal Diagnostic Exploratory Visualization of Focal Cortical Dysplasia,,"Shin-Ting Wu, Raphael Voltoline, Wallace S. Loos, J.A. Iván Rubianes, Lionis S. Watanabe, Bárbara J. Amorim, A. Carolina Coan, Fernando Cendes, Clarissa L. Yasuda",,,,,,,vimeo 289785856,10.1109/mcg.2018.032421655,2018,2018,Other,Room III,Thursday,CG&A Session 2,25-Oct,12:20 PM,12:40 PM
  +CG&A,CGA,Toward a Multimodal Diagnostic Exploratory Visualization of Focal Cortical Dysplasia,,"Shin-Ting Wu, Raphael Voltoline, Wallace S. Loos, J.A. Iván Rubianes, Lionis S. Watanabe, Bárbara J. Amorim, A. Carolina Coan, Fernando Cendes, Clarissa L. Yasuda",http://www.dca.fee.unicamp.br/projects/prosim/publications/journals/wu-loos-voltoline-rubianes-2017-3dmediv-draft.pdf,"Focal cortical dysplasia (FCD) is a malformation of cortical development and a common cause of pharmacoresistant epilepsy. Resective surgery of clear-cut lesions may be curative. However, the localization of the seizure focus and the evaluation of its spatial extent can be challenging in many situations. For concordance assessment, medical studies show the relevance of accurate correlation of multi-source imaging sequences. to improve the sensitivity and specificity of the evaluation. In this paper, we share the process we went through to reach our simple, but effective, solution for integrating multi-volume rendering into an exploratory visualization environment for the diagnosis of FCD. We focus on fetching of multiple data assigned to a sample when they are rendered. Knowing that the major diagnostic role of multiple volumes is to complement information, we demonstrate that appropriate geometric transformations in the texture space are sufficient for accomplishing this task. This allows us to fully implement our proposal in the OpenGL rendering pipeline and to easily integrate it into the existing visual diagnostic application. Both time performance and the visual quality of our proposal were evaluated with a set of clinical data volumes for assessing the potential practical impact of our solution in routine diagnostic use. ",,,,,vimeo 289785856,10.1109/mcg.2018.032421655,2018,2018,Other,Room III,Thursday,CG&A Session 2,25-Oct,12:20 PM,12:40 PM
   VAST,TVCG,ViBr: Visualizing Bipartite Relations at Scale with the Minimum Description Length Principle,J),"Gromit Yeuk-Yin Chan, Panpan Xu, Zeng Dai, Liu Ren",https://vgc.poly.edu/~yychan/papers/chan-vast2018.pdf,"Bipartite graphs model the key relations in many large scale real-world data: customers purchasing items, legislators voting for bills, people’s affiliation with different social groups, faults occurring in vehicles, etc. However, it is challenging to visualize large scale bipartite graphs with tens of thousands or even more nodes or edges. In this paper, we propose a novel visual summarization technique for bipartite graphs based on the minimum description length (MDL) principle. The method simultaneously groups the two different set of nodes and constructs aggregated bipartite relations with balanced granularity and precision. It addresses the key trade-off that often occurs for visualizing large scale and noisy data: acquiring a clear and uncluttered overview while maximizing the information content in it. We formulate the visual summarization task as a co-clustering problem and propose an efficient algorithm based on locality sensitive hashing (LSH) that can easily scale to large graphs under reasonable interactive time constraints that previous related methods cannot satisfy. The method leads to the opportunity of introducing a visual analytics framework with multiple levels-of-detail to facilitate interactive data exploration. In the framework, we also introduce a compact visual design inspired by adjacency list representation of graphs as the building block for a small multiples display to compare the bipartite relations for different subsets of data. We showcase the applicability and effectiveness of our approach by applying it on synthetic data with ground truth and performing case studies on real-world datasets from two application domains including roll-call vote record analysis and vehicle fault pattern analysis. Interviews with experts in the political science community and the automotive industry further highlight the benefits of our approach.",,,,,vimeo 289787354,10.1109/TVCG.2018.2864826,2018,2018,VAST,"Convention Hall 1, Section C",Thursday,Graph and Image,25-Oct,2:20 PM,2:40 PM
   VAST,VAST,Segue: Overviewing Evolution Patterns of Egocentric Networks by Interactive Construction of Spatial Layouts,C),"Po-Ming Law, Yanhong Wu, Rahul Basole",https://terrancelaw.github.io/publications/segue_vast18.pdf,"Getting the overall picture of how a large number of ego-networks evolve is a common yet challenging task. Existing techniques often require analysts to inspect the evolution patterns of ego-networks one after another. In this study, we explore an approach that allows analysts to interactively create spatial layouts in which each dot is a dynamic ego-network. These spatial layouts provide overviews of the evolution patterns of ego-networks, thereby revealing different global patterns such as trends, clusters and outliers in evolution patterns. To let analysts interactively construct interpretable spatial layouts, we propose a data transformation pipeline, with which analysts can adjust the spatial layouts and convert dynamic egonetworks into event sequences to aid interpretations of the spatial positions. Based on this transformation pipeline, we develop Segue, a visual analysis system that supports thorough exploration of the evolution patterns of ego-networks. Through two usage scenarios, we demonstrate how analysts can gain insights into the overall evolution patterns of a large collection of ego-networks by interactively creating different spatial layouts.",,,,,vimeo 289788023,,2018,2018,VAST,"Convention Hall 1, Section C",Thursday,Graph and Image,25-Oct,2:40 PM,3:00 PM
   VAST,TVCG,A Visual Analytics Framework for Spatiotemporal Trade Network Analysis,J),"Hong Wang, Yafeng Lu, Shade Shutters, Michael Steptoe, Feng Wang, Steven Landis, Ross Maciejewski",http://www.public.asu.edu/~hxwang/trade.pdf,"Economic globalization is increasing connectedness among regions of the world, creating complex interdependencies within various supply chains. Recent studies have indicated that changes and disruptions within such networks can serve as indicators for increased risks of violence and armed conflicts. This is especially true of countries that may not be able to compete for scarce commodities during supply shocks. Thus, network-induced vulnerability to supply disruption is typically exported from wealthier populations to disadvantaged populations. As such, researchers and stakeholders concerned with supply chains, political science, environmental studies, etc. need tools to explore the complex dynamics within global trade networks and how the structure of these networks relates to regional instability. However, the multivariate, spatiotemporal nature of the network structure creates a bottleneck in the extraction and analysis of correlations and anomalies for exploratory data analysis and hypothesis generation. Working closely with experts in political science and sustainability, we have developed a highly coordinated, multi-view framework that utilizes anomaly detection, network analytics, and spatiotemporal visualization methods for exploring the relationship between global trade networks and regional instability. Requirements for analysis and initial research questions to be investigated are elicited from domain experts, and a variety of visual encoding techniques for rapid assessment of analysis and correlations between trade goods, network patterns, and time series signatures are explored. We demonstrate the application of our framework through case studies focusing on armed conflicts in Africa, regional instability measures, and their relationship to international global trade.",,,,,vimeo 289787400,10.1109/TVCG.2018.2864844,2018,2018,VAST,"Convention Hall 1, Section C",Thursday,Graph and Image,25-Oct,3:00 PM,3:20 PM
  
positive.code: TVCG,TVCG,Decal-Lenses: Interactive Lenses on Surfaces for Multivariate Visualization,T),"Allan Rocha, Julio Daniel Silva, Usman R. Alim, Sheelagh Carpendale, Mario Costa Sousa",http://pages.cpsc.ucalgary.ca/~acarocha/projects/decal_lenses/files/camera_ready.pdf,"We present decal-lenses, a new interaction technique that extends the concept of magic lenses to augment and manage multivariate visualizations on arbitrary surfaces. Our object-space lenses follow the surface geometry and allow the user to change the point of view during data exploration while maintaining a spatial reference to positions where one or more lenses were placed. Each lens delimits specific regions of the surface where one or more attributes can be selected or combined. Similar to 2D lenses, the user interacts with our lenses in real-time, switching between different attributes within the lens context. The user can also visualize the surface data representations from the point of view of each lens by using local cameras. To place lenses on surfaces of intricate geometry, such as the human brain, we introduce the concept of support surfaces for designing interaction techniques. Support surfaces provide a way to place and interact with the lenses while avoiding holes and occluded regions during data exploration. We further extend decal-lenses to arbitrary regions using brushing and lassoing operations. We discuss the applicability of our technique and present several examples where our lenses can be useful to create a customized exploration of multivariate data on surfaces. ",,,,,vimeo 295735599,10.1109/tvcg.2018.2850781,2018,2018,SciVis,Estrel Hall A+B,Thursday,Interaction and Multivariate Data,25-Oct,5:40 PM,6:00 PM
  SciVis,SciVis,Cluster-Based Visualization for Merger Tree Data: The Challenge of Missing Expectations,,"Annie Preston, Kwan-Liu Ma",,,,,,,vimeo 290328886,,2018,2018,SciVis Short Papers,Estrel Hall C,Thursday,"Flow, Astrophysics, and Computationally Intensive Data Visualization",25-Oct,4:20 PM,4:32 PM
  SciVis,SciVis,Visualization of Uncertainty for Computationally Intensive Simulations Using High Fidelity Emulators,,"Ayan Biswas, Earl Lawrence, James Ahrens",http://ayanbiswas.net/vis18m-sub1022-cam-i7.pdf,"Visualization of high-fidelity scientific simulations with high-dimensional inputs and outputs is an important task. Existing high-dimensional data visualization approaches generally assume a substantial amount of data are available or can be generated as needed. However, many of these simulations can be very computationally intensive, taking minutes or hours to run. Analysis and visualization of such expensive simulations poses a challenge. Statistical emulators are frequently used to approximate simulations for statistical analyses. In this work, we propose a visualization tool for an emulator of the simulator and describe how emulators can be used to create effective visualization systems. We choose Gaussian process emulators for this purpose as they enable fast and accurate prediction with uncertainty information. Using these predictions, we design a system that enables visualization of high-dimensional input and output spaces of complex physics simulations. Users of our system can get a detailed understanding of the uncertainties associated with the emulator predictions in both input and output space for a high-dimensional simulation.",,,,,vimeo 290328642,,2018,2018,SciVis Short Papers,Estrel Hall C,Thursday,"Flow, Astrophysics, and Computationally Intensive Data Visualization",25-Oct,4:32 PM,4:44 PM
  SciVis,SciVis,A Lagrangian Method for Extracting Eddy Boundaries in the Red Sea and the Gulf of Aden,,"Anke Friederici, Habib Toye, Ibrahim Hoteit, Tino Weinkauf, Holger Theisel, Markus Hadwiger",http://www.medvis-award.de/visual/files/publications/2018/Friederici_2018_VIS_paper.pdf,"Mesoscale ocean eddies play a major role for both the intermixing of water and the transport of biological mass. This makes the identification and tracking of their shape, location and deformation over time highly important for a number of applications. While eddies maintain a roughly circular shape in the free ocean, the narrow basins of the Red Sea and Gulf of Aden lead to the formation of irregular eddy shapes that existing methods struggle to identify. We propose the following model: Inside an eddy, particles rotate around a common core and thereby remain at a constant distance under a certain parametrization. The transition to the more unpredictable flow on the outside can thus be identified as the eddy boundary. We apply this algorithm on a realistic simulation of the Red Sea circulation, where we are able to identify the shape of irregular eddies robustly and more coherently than previous methods. We visualize the eddies as tubes in space-time to enable the analysis of their movement and deformation over several weeks.",,,,,http://vccvisualization.org/publications/2018_friederici_redseaeddies.mp4,,2018,2018,SciVis Short Papers,Estrel Hall C,Thursday,"Flow, Astrophysics, and Computationally Intensive Data Visualization",25-Oct,4:45 PM,4:57 PM
  SciVis,SciVis,FTLE Ridge Lines for Long Integration Times,,"Thomas Wilde, Christian Rössl, Holger Theisel",http://www.medvis-award.de/visual/files/publications/2018/Wilde_2018_VISb.pdf,"We present an approach to the extraction of FTLE ridges for 2D unsteady vector fields under long integration times. This is a hard problem because such FTLE ridges tend to be sharp and close to each other. The main feature of our approach is that it does not only use an FTLE sampling at the desired final integration time but incorporates samples from prior integration times as well. With this additional information, the new method produces more and finer ridge lines than previous approaches. Based on this output, we can consider FTLE ridge statistics. We test the approach on synthetic benchmarks and real-world data sets.",,,,,vimeo 290328753,,2018,2018,SciVis Short Papers,Estrel Hall C,Thursday,"Flow, Astrophysics, and Computationally Intensive Data Visualization",25-Oct,4:57 PM,5:09 PM
  SciVis,SciVis,Ocean Current Segmentation at Different Depths and Correlation with Temperature in a MPAS-Ocean Simulation,,"Petra Gospodnetic, Divya Banesh, Philip Wolfram, Mark Petersen, Hans Hagen, James Ahrens, Markus Rauhut",,,,,,,vimeo 290328665,,2018,2018,SciVis Short Papers,Estrel Hall C,Thursday,"Flow, Astrophysics, and Computationally Intensive Data Visualization",25-Oct,5:10 PM,5:22 PM
  SciVis,SciVis,"TimeTubes: Automatic Extraction of Observable Blazar Features from Long-Term, Multi-Dimensional Datasets",,"Naoko Sawada, Masanori Nakayama, Makoto Uemura, Issei Fujishiro",,,,,,,vimeo 290328934,,2018,2018,SciVis Short Papers,Estrel Hall C,Thursday,"Flow, Astrophysics, and Computationally Intensive Data Visualization",25-Oct,5:22 PM,5:34 PM
  
negative.code: SciVis,TVCG,Dynamic Volume Lines: Visual Comparison of 3D Volumes through Space-filling Curves,J),"Johannes Weissenböck, Bernhard Fröhler, Eduard Gröller, Johann Kastner, Christoph Heinzl",,,,,,,vimeo 290325634,10.1109/tvcg.2018.2864510,2018,2018,SciVis,Estrel Hall A+B,Wednesday,Volume Visualization,24-Oct,11:20 AM,11:40 AM
  SciVis,TVCG,A Declarative Grammar of Flexible Volume Visualization Pipelines,J),"Min Shih, Charles Rozhon, Kwan-Liu Ma",,,,,,,vimeo 290327611,10.1109/tvcg.2018.2864841,2018,2018,SciVis,Estrel Hall A+B,Wednesday,Volume Visualization,24-Oct,11:40 AM,12:00 PM
  TVCG,TVCG,Multi-Material Volume Rendering with a Physically-Based Surface Reflection Model,T),"Oleg Igouchkine, Yubo Zhang, Kwan-Liu Ma",,,,,,,vimeo 289789120,10.1109/tvcg.2017.2784830,2018,2018,SciVis,Estrel Hall A+B,Wednesday,Volume Visualization,24-Oct,12:00 PM,12:20 PM
  TVCG,TVCG,A Generative Model for Volume Rendering,T),"Matthew Berger, Jixian Li, Joshua A. Levine",https://arxiv.org/pdf/1710.09545.pdf,"We present a technique to synthesize and analyze volume-rendered images using generative models. We use the Generative Adversarial Network (GAN) framework to compute a model from a large collection of volume renderings, conditioned on (1) viewpoint and (2) transfer functions for opacity and color. Our approach facilitates tasks for volume analysis that are challenging to achieve using existing rendering techniques such as ray casting or texture-based methods. We show how to guide the user in transfer function editing by quantifying expected change in the output image. Additionally, the generative model transforms transfer functions into a view-invariant latent space specifically designed to synthesize volume-rendered images. We use this space directly for rendering, enabling the user to explore the space of volume-rendered images. As our model is independent of the choice of volume rendering process, we show how to analyze volume-rendered images produced by direct and global illumination lighting, for a variety of volume datasets.",,,,,vimeo 289789468,10.1109/tvcg.2018.2816059,2018,2018,SciVis,Estrel Hall A+B,Wednesday,Volume Visualization,24-Oct,12:20 PM,12:40 PM
  InfoVis,TVCG,Vistrates: A Component Model for Ubiquitous Analytics,J),"Sriram Karthik Badam, Andreas Mathisen, Roman Rädle, Clemens Nylandsted Klokmose, Niklas Elmqvist",http://users.umiacs.umd.edu/~elm/projects/vistrates/vistrates.pdf,"Visualization tools are often specialized for specific tasks, which turns the user's analytical workflow into a fragmented process performed across many tools. In this paper, we present a component model design for data visualization to promote modular designs of visualization tools that enhance their analytical scope. Rather than fragmenting tasks across tools, the component model supports unification, where components�the building blocks of this model�can be assembled to support a wide range of tasks. Furthermore, the model also provides additional key properties, such as support for collaboration, sharing across multiple devices, and adaptive usage depending on expertise, from creating visualizations using dropdown menus, through instantiating components, to actually modifying components or creating entirely new ones from scratch using JavaScript or Python source code. To realize our model, we introduce VISTRATES, a literate computing platform for developing, assembling, and sharing visualization components. From a visualization perspective, Vistrates features cross-cutting components for visual representations, interaction, collaboration, and device responsiveness maintained in a component repository. From a development perspective, Vistrates offers a collaborative programming environment where novices and experts alike can compose component pipelines for specific analytical activities. Finally, we present several Vistrates use cases that span the full range of the classic �anytime� and �anywhere� motto for ubiquitous analysis: from mobile and on-the-go usage, through office settings, to collaborative smart environments covering a variety of tasks and devices.",,https://github.com/karthikbadam/Vistrates,,,vimeo 289784994,10.1109/tvcg.2018.2865144,2018,2018,InfoVis,Estrel Hall C,Wednesday,Devices,24-Oct,11:00 AM,11:20 AM
  InfoVis,TVCG,SmartCues: A Multitouch Query Approach for Details-on-Demand through Dynamically Computed Overlays,J),"Hariharan Subramonyam, Eytan Adar",,,,,,,vimeo 289784720,10.1109/tvcg.2018.2865231,2018,2018,InfoVis,Estrel Hall C,Wednesday,Devices,24-Oct,11:20 AM,11:40 AM
  InfoVis,TVCG,"Multiple Coordinated Views at Large Displays for Multiple Users: Empirical Findings on User Behavior, Movements, and Distances ",J),"Ricardo Langner, Ulrike Kister, Raimund Dachselt",,,,,,,vimeo 289784543,10.1109/tvcg.2018.2865235,2018,2018,InfoVis,Estrel Hall C,Wednesday,Devices,24-Oct,11:40 AM,12:00 PM
  