anchor.diff:  VAST,TVCG,Cost-benefit Analysis of Visualization in Virtual Environments ,J),"Min Chen, Kelly Gaither, Nigel John, Brian McCann",,,,,,,vimeo 289787910,,2018,2018,VAST,"Convention Hall 1, Section C",Tuesday,Opening & Evaluation and Theory,23-Oct,3:40 PM,4:00 PM,
   InfoVis,TVCG,Shape-preserving Star Coordinates ,J),"Vladimir Molchanov, Lars Linsen",,,,,,,vimeo 289785145,,2018,2018,InfoVis,"Convention Hall 1, Section D",Tuesday,Opening & Multiple Dimensions,23-Oct,2:20 PM,2:40 PM,
   TVCG,TVCG,Using Dashboard Networks to Visualize Multiple Patient Histories: A Design Study on Post-operative Prostate Cancer ,T),"Jürgen Bernard, David Sessler, Jörn Kohlhammer, Roy A. Ruddle",http://eprints.whiterose.ac.uk/128739/1/bernard-ieee-tvcg-dashboard-networks.pdf,"In this design study, we present a visualization technique that segments patients' histories instead of treating them as raw event sequences, aggregates the segments using criteria such as the whole history or treatment combinations, and then visualizes the aggregated segments as static dashboards that are arranged in a dashboard network to show longitudinal changes. The static dashboards were developed in nine iterations, to show 15 important attributes from the patients' histories. The final design was evaluated with five non-experts, five visualization experts and four medical experts, who successfully used it to gain an overview of a 2,000 patient dataset, and to make observations about longitudinal changes and differences between two cohorts. The research represents a step-change in the detail of large-scale data that may be successfully visualized using dashboards, and provides guidance about how the approach may be generalized.",,,,,vimeo 289789053,,,2018,InfoVis,"Convention Hall 1, Section D",Tuesday,Opening & Multiple Dimensions,23-Oct,2:40 PM,3:00 PM,
  -InfoVis,TVCG,Towards Better Spatial Integration in Ranking Visualization ,J),"Di Weng, Ran Chen, Zikun Deng, Feiran Wu, Jingmin Chen, Yingcai Wu",http://zjuvis.org/files/srvis.pdf,"Interactive ranking techniques have substantially promoted analysts ability in making judicious and informed decisions effectively based on multiple criteria. However, the existing techniques cannot satisfactorily support the analysis tasks involved in ranking large-scale spatial alternatives, such as selecting optimal locations for chain stores, where the complex spatial contexts involved are essential to the decision-making process. Limitations observed in the prior attempts of integrating rankings with spatial contexts motivate us to develop a context-integrated visual ranking technique. Based on a set of generic design requirements we summarized by collaborating with domain experts, we propose SRVis, a novel spatial ranking visualization technique that supports efficient spatial multi-criteria decision-making processes by addressing three major challenges in the aforementioned context integration, namely, a) the presentation of spatial rankings and contexts, b) the scalability of rankings visual representations, and c) the analysis of context-integrated spatial rankings. Specifically, we encode massive rankings and their cause with scalable matrix-based visualizations and stacked bar charts based on a novel two-phase optimization framework that minimizes the information loss, and the flexible spatial filtering and intuitive comparative analysis are adopted to enable the in-depth evaluation of the rankings and assist users in selecting the best spatial alternative. The effectiveness of the proposed technique has been evaluated and demonstrated with an empirical study of optimization methods, two case studies, and expert interviews.",https://srvis.zjuvis.org/,,,,vimeo 289784783,,2018,2018,InfoVis,"Convention Hall 1, Section D",Tuesday,Opening & Multiple Dimensions,23-Oct,3:00 PM,3:20 PM,
  -InfoVis,TVCG,A Declarative Rendering Model for Multiclass Density Maps ,J),"Jaemin Jo, Frédéric Vernier, Pierre Dragicevic, Jean-Daniel Fekete",https://hal.inria.fr/hal-01848427/document,"Multiclass maps are scatterplots, multidimensional projections, or thematic geographic maps where data points have a categorical attribute in addition to two quantitative attributes. This categorical attribute is often rendered using shape or color, which does not scale when overplotting occurs. When the number of data points increases, multiclass maps must resort to data aggregation to remain readable. We present multiclass density maps: multiple 2D histograms computed for each of the category values. Multiclass density maps are meant as a building block to improve the expressiveness and scalability of multiclass map visualization. In this article, we first present a short survey of aggregated multiclass maps, mainly from cartography. We then introduce a declarative modela simple yet expressive JSON grammar associated with visual semanticsthat specifies a wide design space of visualizations for multiclass density maps. Our declarative model is expressive and can be efficiently implemented in visualization front-ends such as modern web browsers. Furthermore, it can be reconfigured dynamically to support data exploration tasks without recomputing the raw data. Finally, we demonstrate how our model can be used to reproduce examples from the past and support exploring data at scale.",https://jaeminjo.github.io/Multiclass-Density-Maps/,https://github.com/e-/Multiclass-Density-Maps,,,vimeo 289785026,,2018,2018,InfoVis,"Convention Hall 1, Section D",Tuesday,Opening & Multiple Dimensions,23-Oct,3:20 PM,3:40 PM,
  +InfoVis,TVCG,Towards Better Spatial Integration in Ranking Visualization ,J),"Di Weng, Ran Chen, Zikun Deng, Feiran Wu, Jingmin Chen, Yingcai Wu",http://zjuvis.org/files/srvis.pdf,"Interactive ranking techniques have substantially promoted analysts' ability in making judicious and informed decisions effectively based on multiple criteria. However, the existing techniques cannot satisfactorily support the analysis tasks involved in ranking large-scale spatial alternatives, such as selecting optimal locations for chain stores, where the complex spatial contexts involved are essential to the decision-making process. Limitations observed in the prior attempts of integrating rankings with spatial contexts motivate us to develop a context-integrated visual ranking technique. Based on a set of generic design requirements we summarized by collaborating with domain experts, we propose SRVis, a novel spatial ranking visualization technique that supports efficient spatial multi-criteria decision-making processes by addressing three major challenges in the aforementioned context integration, namely, a) the presentation of spatial rankings and contexts, b) the scalability of rankings' visual representations, and c) the analysis of context-integrated spatial rankings. Specifically, we encode massive rankings and their cause with scalable matrix-based visualizations and stacked bar charts based on a novel two-phase optimization framework that minimizes the information loss, and the flexible spatial filtering and intuitive comparative analysis are adopted to enable the in-depth evaluation of the rankings and assist users in selecting the best spatial alternative. The effectiveness of the proposed technique has been evaluated and demonstrated with an empirical study of optimization methods, two case studies, and expert interviews.",https://srvis.zjuvis.org/,,,,vimeo 289784783,,2018,2018,InfoVis,"Convention Hall 1, Section D",Tuesday,Opening & Multiple Dimensions,23-Oct,3:00 PM,3:20 PM,
  +InfoVis,TVCG,A Declarative Rendering Model for Multiclass Density Maps ,J),"Jaemin Jo, Frédéric Vernier, Pierre Dragicevic, Jean-Daniel Fekete",https://hal.inria.fr/hal-01848427/document,"Multiclass maps are scatterplots, multidimensional projections, or thematic geographic maps where data points have a categorical attribute in addition to two quantitative attributes. This categorical attribute is often rendered using shape or color, which does not scale when overplotting occurs. When the number of data points increases, multiclass maps must resort to data aggregation to remain readable. We present multiclass density maps: multiple 2D histograms computed for each of the category values. Multiclass density maps are meant as a building block to improve the expressiveness and scalability of multiclass map visualization. In this article, we first present a short survey of aggregated multiclass maps, mainly from cartography. We then introduce a declarative model�a simple yet expressive JSON grammar associated with visual semantics�that specifies a wide design space of visualizations for multiclass density maps. Our declarative model is expressive and can be efficiently implemented in visualization front-ends such as modern web browsers. Furthermore, it can be reconfigured dynamically to support data exploration tasks without recomputing the raw data. Finally, we demonstrate how our model can be used to reproduce examples from the past and support exploring data at scale.",https://jaeminjo.github.io/Multiclass-Density-Maps/,https://github.com/e-/Multiclass-Density-Maps,,,vimeo 289785026,,2018,2018,InfoVis,"Convention Hall 1, Section D",Tuesday,Opening & Multiple Dimensions,23-Oct,3:20 PM,3:40 PM,
   InfoVis,TVCG,DimReader: Axis lines that explain non-linear projections ,J),"Rebecca Faust, David Glickenstein, Carlos Scheidegger",https://arxiv.org/pdf/1710.00992.pdf,"Non-linear dimensionality reduction (NDR) methods such as LLE and t-SNE are popular with visualization researchers and experienced data analysts, but present serious problems of interpretation. In this paper, we present DimReader, a technique that recovers readable axes from such techniques. DimReader is based on analyzing infinitesimal perturbations of the dataset with respect to variables of interest. The perturbations define exactly how we want to change each point in the original dataset and we measure the effect that these changes have on the projection. The recovered axes are in direct analogy with the axis lines (grid lines) of traditional scatterplots. We also present methods for discovering perturbations on the input data that change the projection the most. The calculation of the perturbations is efficient and easily integrated into programs written in modern programming languages. We present results of DimReader on a variety of NDR methods and datasets both synthetic and real-life, and show how it can be used to compare different NDR methods. Finally, we discuss limitations of our proposal and situations where further research is needed.",,,,,vimeo 289784574,,2018,2018,InfoVis,"Convention Hall 1, Section D",Tuesday,Opening & Multiple Dimensions,23-Oct,3:40 PM,4:00 PM,
   SciVis,TVCG,Recirculation Surfaces for Flow Visualization ,J),"Thomas Wilde, Christian Rössl, Holger Theisel",,,,,,,vimeo 290325803,,2018,2018,SciVis,Estrel Hall A+B,Tuesday,Opening & Flow Features,23-Oct,2:20 PM,2:40 PM,
   SciVis,TVCG,Objective Vortex Corelines of Finite-sized Objects in Fluid Flows ,J),"Tobias Günther, Holger Theisel",,,,,,,vimeo 290327685,,2018,2018,SciVis,Estrel Hall A+B,Tuesday,Opening & Flow Features,23-Oct,2:40 PM,3:00 PM,
  
positive.code: VAST,TVCG,GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation ,J),"Minsuk Kahng, Nikhil Thorat, Duen Horng Chau, Fernanda Viegas, Martin Wattenberg",,,,,,,vimeo 289787794,,2018,2018,VAST,"Convention Hall 1, Section C",Thursday,Deep Learning,25-Oct,12:20 PM,12:40 PM,
  InfoVis,TVCG,A Framework for Creative Visualization-Opportunities Workshops ,J),"Ethan Kerzner, Sarah Goodwin, Jason Dykes, Sara V Jones, Miriah Meyer",http://sci.utah.edu/~vdl/papers/2018_infovis_creative-workshops.pdf,"Applied visualization researchers often work closely with domain collaborators to explore new and useful applications of visualization. The early stages of collaborations are typically time consuming for all stakeholders as researchers piece together an understanding of domain challenges from disparate discussions and meetings. A number of recent projects, however, report on the use of creative visualization-opportunities (CVO) workshops to accelerate the early stages of applied work, eliciting a wealth of requirements in a few days of focused work. Yet, there is no established guidance for how to use such workshops effectively. In this paper, we present the results of a 2-year collaboration in which we analyzed the use of 17 workshops in 10 visualization contexts. Its primary contribution is a framework for CVO workshops that: 1) identifies a process model for using workshops; 2) describes a structure of what happens within effective workshops; 3) recommends 25 actionable guidelines for future workshops; and 4) presents an example workshop and workshop methods. The creation of this framework exemplifies the use of critical reflection to learn about visualization in practice from diverse studies and experience.",,,,,vimeo 289784415,,2018,2018,InfoVis,"Convention Hall 1, Section D",Thursday,Design & Storytelling,25-Oct,11:00 AM,11:20 AM,
  TVCG,TVCG,ATOM: A Grammar for Unit Visualizations ,T),"Deokgun Park, Steven M. Drucker, Roland Fernandez, Niklas Elmqvist",,,,,,,vimeo 289789243,,,2018,InfoVis,"Convention Hall 1, Section D",Thursday,Design & Storytelling,25-Oct,11:20 AM,11:40 AM,
  InfoVis,TVCG,Design Exposition with Literate Visualization ,J),"Jo Wood, Alexander Kachkaev, Jason Dykes",http://openaccess.city.ac.uk/20081/1/wood_literate_2018.pdf,"We propose a new approach to the visualization design and communication process, literate visualization, based upon and extending, Donald Knuths idea of literate programming. It integrates the process of writing data visualization code with description of the design choices that led to the implementation (design exposition). We develop a model of design exposition characterised by four visualization designer architypes: the evaluator, the autonomist, the didacticist and the rationalist. The model is used to justify the key characteristics of literate visualization: notebook documents that integrate live coding input, rendered output and textual narrative; low cost of authoring textual narrative; guidelines to encourage structured visualization design and its documentation. We propose narrative schemas for structuring and validating a wide range of visualization design approaches and models, and branching narratives for capturing alternative designs and design views. We describe a new open source literate visualization environment, litvis, based on a declarative interface to Vega and Vega-Lite through the functional programming language Elm combined with markdown for formatted narrative. We informally assess the approach, its implementation and potential by considering three examples spanning a range of design abstractions: new visualization idioms; validation though visualization algebra; and feminist data visualization. We argue that the rich documentation of the design process provided by literate visualization offers the potential to improve the validity of visualization design and so benefit both academic visualization and visualization practice.",,https://github.com/gicentre/litvis,,,vimeo 289785349,,2018,2018,InfoVis,"Convention Hall 1, Section D",Thursday,Design & Storytelling,25-Oct,11:40 AM,12:00 PM,
  InfoVis,TVCG,iStoryline: Effective Convergence to Hand-drawn Storylines ,J),"Tan Tang, Sadia Rubab, Jiewen Lai, Weiwei Cui, Lingyun Yu, Yingcai Wu",http://zjuvis.org/files/istoryline.pdf,"Storyline visualization techniques have progressed significantly to generate illustrations of complex stories automatically. However, the visual layouts of storylines are not enhanced accordingly despite the improvement in the performance and extension of its application area. Existing methods attempt to achieve several shared optimization goals, such as reducing empty space and minimizing line crossings and wiggles. However, these goals do not always produce optimal results when compared to hand-drawn storylines. We conducted a preliminary study to learn how users translate a narrative into a hand-drawn storyline and check whether the visual elements in hand-drawn illustrations can be mapped back to appropriate narrative contexts. We also compared the hand-drawn storylines with storylines generated by the state-of-the-art methods and found they have significant differences. Our findings led to a design space that summarizes 1) how artists utilize narrative elements and 2) the sequence of actions artists follow to portray expressive and attractive storylines. We developed iStoryline, an authoring tool for integrating high-level user interactions into optimization algorithms and achieving a balance between hand-drawn storylines and automatic layouts. iStoryline allows users to create novel storyline visualizations easily according to their preferences by modifying the automatically generated layouts. The effectiveness and usability of iStoryline are studied with qualitative evaluations",https://istoryline.github.io/,,https://istoryline.github.io/interview/interview.html,,video https://istoryline.github.io/img/iStoryline.mp4,,2018,2018,InfoVis,"Convention Hall 1, Section D",Thursday,Design & Storytelling,25-Oct,12:00 PM,12:20 PM,
  InfoVis,TVCG,Narvis: Authoring Narrative Slideshows for Introducing Data Visualization Designs ,J),"Qianwen Wang, Zhen Li, Siwei Fu, Weiwei Cui, Huamin Qu",https://wangqianwen0418.github.io/assets/pdf/Narvis.pdf,"Visual designs can be complex in modern data visualization systems, which poses special challenges for explaining them to the non-experts. However, few if any presentation tools are tailored for this purpose. In this study, we present Narvis, a slideshow authoring tool designed for introducing data visualizations to non-experts. Narvis targets two types of end users: teachers, experts in data visualization who produce tutorials for explaining a data visualization, and students, non-experts who try to understand visualization designs through tutorials. We present an analysis of requirements through close discussions with the two types of end users. The resulting considerations guide the design and implementation of Narvis. Additionally, to help teachers better organize their introduction slideshows, we specify a data visualization as a hierarchical combination of components, which are automatically detected and extracted by Narvis. The teachers craft an introduction slideshow through first organizing these components, and then explaining them sequentially. A series of templates are provided for adding annotations and animations to improve efficiency during the authoring process. We evaluate Narvis through a qualitative analysis of the authoring experience, and a preliminary evaluation of the generated slideshows.",,,,,vimeo 289784711,,2018,2018,InfoVis,"Convention Hall 1, Section D",Thursday,Design & Storytelling,25-Oct,12:20 PM,12:40 PM,
  SciVis,TVCG,Culling for Extreme-Scale Segmentation Volumes: A Hybrid Deterministic and Probabilistic Approach ,J),"Johanna Beyer, Haneen Mohammed, Marco Agus, Ali K. Al-Awami, Hanspeter Pfister, Markus Hadwiger",,,,,,,vimeo 290327965,,2018,2018,SciVis,Estrel Hall A+B,Thursday,Scalable Techniques,25-Oct,11:00 AM,11:20 AM,
  
negative.code: VAST,VAST,SMARTexplore: Simplifying High-Dimensional Data Analysis through a Table-Based Visual Analytics Approach ,C),"Michael Blumenschein, Michael Behrisch, Stefanie Schmid, Simon Butscher, Deborah R. Wahl, Karoline Villinger, Britta Renner, Harald Reiterer, Daniel Keim",,,,,,,vimeo 289787735,,2018,2018,VAST,"Convention Hall 1, Section C",Wednesday,High Dimensional Data,24-Oct,3:00 PM,3:20 PM,
  TVCG,TVCG,ColorMapND: A Data-Driven Approach and Tool for Mapping Multivariate Data to Color ,T),"Shenghui Cheng, Wei Xu, Klaus Mueller",,,,,,,vimeo 289788955,,,2018,VAST,"Convention Hall 1, Section C",Wednesday,High Dimensional Data,24-Oct,3:20 PM,3:40 PM,
  VAST,VAST,EmbeddingVis: A Visual Analytics Approach to Comparative Network Embedding Inspection ,C),"Quan Li, Kristanto Sean Njotoprawiro, Hammad Haleem, Qiaoan Chen, Chris YI, Xiaojuan Ma",,,,,,,vimeo 289788000,,2018,2018,VAST,"Convention Hall 1, Section C",Wednesday,High Dimensional Data,24-Oct,3:40 PM,4:00 PM,
  InfoVis,TVCG,Evaluating 'Graphical Perception' with CNNs,,"Daniel Haehn, James Tompkin, Hanspeter Pfister",https://github.com/Rhoana/perception/tree/master/PAPER,"Convolutional neural networks can successfully perform many computer vision tasks on images. For visualization, how do CNNs perform when applied to graphical perception tasks? We investigate this question by reproducing Cleveland and McGill's seminal 1984 experiments, which measured human perception efficiency of different visual encodings and defined elementary perceptual tasks for visualization. We measure the graphical perceptual capabilities of four network architectures on five different visualization tasks and compare to existing and new human performance baselines. While under limited circumstances CNNs are able to meet or outperform human task performance, we find that CNNs are not currently a good model for human graphical perception. We present the results of these experiments to foster the understanding of how CNNs succeed and fail when applied to data visualizations.",,https://github.com/rhoana/perception,,,vimeo 280506639,,2018,2018,InfoVis,"Convention Hall 1, Section D",Wednesday,Text & Communication,24-Oct,2:20 PM,2:40 PM,
  InfoVis,TVCG,NLIZE: A Perturbation-Driven Visual Interrogation Tool for Analyzing and Interpreting Natural Language Inference Models ,J),"Shusen Liu, Zhimin Li, Tao Li, Vivek Srikumar, Valerio Pascucci, Peer-Timo Bremer",http://www.sci.utah.edu/~shusenl/publications/paper_entailVis.pdf,"With the recent advances in deep learning, neural network models have obtained state-of-the-art performances for many linguistic tasks in natural language processing. However, this rapid progress also brings enormous challenges. The opaque nature of a neural network model leads to hard-to-debug-systems and difficult-to-interpret mechanisms. Here, we introduce a visualization system that, through a tight yet flexible integration between visualization elements and the underlying model, allows a user to interrogate the model by perturbing the input, internal state, and prediction while observing changes in other parts of the pipeline. We use the natural language inference problem as an example to illustrate how a perturbation-driven paradigm can help domain experts assess the potential limitation of a model, probe its inner states, and interpret and form hypotheses about fundamental model mechanisms such as attention.",,,,,vimeo 289784737,,2018,2018,InfoVis,"Convention Hall 1, Section D",Wednesday,Text & Communication,24-Oct,2:40 PM,3:00 PM,
  InfoVis,TVCG,Elastic Documents: Coupling Text and Tables through Contextual Visualizations for Enhanced Document Reading ,J),"Sriram Karthik Badam, Zhicheng Liu, Niklas Elmqvist",http://users.umiacs.umd.edu/~elm/projects/elastic-documents/elastic-documents.pdf,"Today's data-rich documents are often complex datasets in themselves, consisting of information in different formats such as text, gures, and data tables. These additional media augment the textual narrative in the document. However, the static layout of a traditional for-print document often impedes deep understanding of its content because of the need to navigate to access content scattered throughout the text. In this paper, we seek to facilitate enhanced comprehension of such documents through a contextual visualization technique that couples text content with data tables contained in the document. We parse the text content and data tables, cross-link the components using a keyword-based matching algorithm, and generate on-demand visualizations based on the reader's current focus within a document. We evaluate this technique in a user study comparing our approach to a traditional reading experience. Results from our study show that (1) participants comprehend the content better with tighter coupling of text and data, (2) the contextual visualizations enable participants to develop better summaries that capture the main data-rich insights within the document, and (3) overall, our method enables participants to develop a more detailed understanding of the document content.",,,,,vimeo 289784966,,2018,2018,InfoVis,"Convention Hall 1, Section D",Wednesday,Text & Communication,24-Oct,3:00 PM,3:20 PM,
  InfoVis,TVCG,Augmenting Visualizations with Interactive Data Facts to Facilitate Interpretation and Communication ,J),"Arjun Srinivasan, Steven Drucker, Alex Endert, John Stasko",https://arjun010.github.io/static/papers/voder-infovis18.pdf,"Recently, an increasing number of visualization systems have begun to incorporate natural language generation (NLG) capabilities into their interfaces. NLG-based visualization systems typically leverage a suite of statistical functions to automatically extract key facts about the underlying data and surface them as natural language sentences alongside visualizations. With current systems, users are typically required to read the system-generated sentences and mentally map them back to the accompanying visualization. However, depending on the features of the visualization (e.g., visualization type, data density) and the complexity of the data fact, mentally mapping facts to visualizations can be a challenging task. Furthermore, more than one visualization could be used to illustrate a single data fact. Unfortunately, current tools provide little or no support for users to explore such alternatives. In this paper, we explore how system-generated data facts can be treated as interactive widgets to help users interpret visualizations and communicate their findings. We present Voder, a system that lets users interact with automatically-generated data facts to explore both alternative visualizations to convey a data fact as well as a set of embellishments to highlight a fact within a visualization. Leveraging data facts as interactive widgets, Voder also facilitates data fact-based visualization search. To assess Voder's design and features, we conducted a preliminary user study with 12 participants having varying levels of experience with visualization tools. Participant feedback suggested that interactive data facts aided them in interpreting visualizations. Participants also stated that the suggestions surfaced through the facts helped them explore alternative visualizations and embellishments to communicate individual data facts.",,,,,vimeo 289784943,,2018,2018,InfoVis,"Convention Hall 1, Section D",Wednesday,Text & Communication,24-Oct,3:20 PM,3:40 PM,
  InfoVis,TVCG,What Do We Talk About When We Talk About Dashboards? ,J),"Alper Sarikaya, Michael Correll, Lyn Bartram, Melanie Tory, Danyel A Fisher",https://alper.datav.is/assets/publications/dashboards/dashboards-preprint.pdf,"Dashboards are one of the most common use cases for data visualization, and their design and contexts of use are considerably different from exploratory visualization tools. In this paper, we look at the broad scope of how dashboards are used in practice through an analysis of dashboard examples and documentation about their use. We systematically review the literature surrounding dashboard use, construct a design space for dashboards, and identify major dashboard types. We characterize dashboards by their design goals, levels of interaction, and the practices around them. Our framework and literature review suggest a number of fruitful research directions to better support dashboard design, implementation, and use.",,,,,vimeo 289785315,,2018,2018,InfoVis,"Convention Hall 1, Section D",Wednesday,Text & Communication,24-Oct,3:40 PM,4:00 PM,
  SciVis,TVCG,Visualization of Bubble Formation in Porous Media ,J),"Hui Zhang, Steffen Frey, Holger Steeb, David Uribe, Thomas Ertl, Wenping Wang",,,,,,,vimeo 290325359,,2018,2018,SciVis,Estrel Hall A+B,Wednesday,Space and Physics,24-Oct,2:20 PM,2:40 PM,
  SciVis,TVCG,Gaia Sky: Navigating the Gaia Catalog ,J),"Toni Sagristà Sellés, Stefan Jordan, Thomas Mueller, Filip Sadlo",,,,,,,vimeo 290325474,,2018,2018,SciVis,Estrel Hall A+B,Wednesday,Space and Physics,24-Oct,2:40 PM,3:00 PM,
  