anchor.diff:  SciVis,TVCG,The Topology ToolKit,"Julien Tierny, Guillaume Favelier, Joshua Levine, Charles Gueunet, Michaël Michaux",https://hal.archives-ouvertes.fr/hal-01499905/document,"This system paper presents the Topology ToolKit (TTK), a software platform designed for the topological analysis of scalar data in scientific visualization. While topological data analysis has gained in popularity over the last two decades, it has not yet been widely adopted as a standard data analysis tool for end users or developers. TTK aims at addressing this problem by providing a unified, generic, efficient, and robust implementation of key algorithms for the topological analysis of scalar data, including: critical points, integral lines, persistence diagrams, persistence curves, merge trees, contour trees, Morse-Smale complexes, fiber surfaces, continuous scatterplots, Jacobi sets, Reeb spaces, and more. TTK is easily accessible to end users due to a tight integration with ParaView. It is also easily accessible to developers through a variety of bindings (Python, VTK/C++) for fast prototyping or through direct, dependency-free, C++, to ease integration into pre-existing complex systems. While developing TTK, we faced several algorithmic and software engineering challenges, which we document in this paper. In particular, we present an algorithm for the construction of a discrete gradient that complies to the critical points extracted in the piecewise-linear setting. This algorithm guarantees a combinatorial consistency across the topological abstractions supported by TTK, and importantly, a unified implementation of topological data simplification for multi-scale exploration and analysis. We also present a cached triangulation data structure, that supports time efficient and generic traversals, which self-adjusts its memory usage on demand for input simplicial meshes and which implicitly emulates a triangulation for regular grids with no memory overhead. Finally, we describe an original software architecture, which guarantees memory efficient and direct accesses to TTK features, while still allowing for researchers powerful and easy bindings and extensions. TTK is open source (BSD license) and its code, online documentation and video tutorials are available on TTK’s website [108].",https://topology-tool-kit.github.io/,https://github.com/topology-tool-kit/ttk,,youtube Hn8w0V-jHgw,,2018,2017,SciVis,207,Wednesday,Topology-based methods,2:40 PM,3:00 PM
   SciVis,TVCG,TopoAngler: Interactive Topology-based Extraction of Fishes,"Alexander Bock, Harish Doraiswamy, Adam Summers, Claudio Silva",https://alexanderbock.github.io/papers/vis17-bock-topoangler.pdf,"We present TopoAngler, a visualization framework that enables an interactive user-guided segmentation of fishes contained in a micro-CT scan. The inherent noise in the CT scan coupled with the often disconnected (and sometimes broken) skeletal structure of fishes makes an automatic segmentation of the volume impractical. To overcome this, our framework combines techniques from computational topology with an interactive visual interface, enabling the human-in-the-loop to effectively extract fishes from the volume. In the first step, the join tree of the input is used to create a hierarchical segmentation of the volume. Through the use of linked views, the visual interface then allows users to interactively explore this hierarchy, and gather parts of individual fishes into a coherent sub-volume, thus reconstructing entire fishes. Our framework was primarily developed for its application to CT scans of fishes, generated as part of the ScanAllFish project, through close collaboration with their lead scientist. However, we expect it to also be applicable in other biological applications where a single data set contains multiple specimen; a common routine that is now widely followed in laboratories to increase throughput of expensive CT scanners.",,,,youtube gz22DjMRJjk,,2018,2017,SciVis,207,Wednesday,Topology-based methods,2:00 PM,2:20 PM
   SciVis,TVCG,Uncertainty Visualization Using Copula-Based Analysis in Mixed Distribution Models,"Subhashis Hazarika, Ayan Biswas, Han-Wei Shen",,,,,,,,2018,2017,SciVis,207,Tuesday,"Mix: Foundations, uncertainty, particles",2:40 PM,3:00 PM
  -SciVis,TVCG,Visualization Multipipeline for Communicating Biology,"Peter Mindek, David Kouřil, Johannes Sorger, Daniel Toloudis, Blair Lyons, Graham Johnson, M. Eduard Gröller, Ivan Viola",https://www.cg.tuwien.ac.at/research/publications/2017/mindek-2017-marion/mindek-2017-marion-Paper.pdf,"We propose a system to facilitate biology communication by developing a pipeline to support the instructional visualization of heterogeneous biological data on heterogeneous user-devices. Discoveries and concepts in biology are typically summarized with illustrations assembled manually from the interpretation and application of heterogenous data. The creation of such illustrations is time consuming, which makes it incompatible with frequent updates to the measured data as new discoveries are made. Illustrations are typically non-interactive, and when an illustration is updated, it still has to reach the user. Our system is designed to overcome these three obstacles. It supports the integration of heterogeneous datasets, reflecting the knowledge that is gained from different data sources in biology. After pre-processing the datasets, the system transforms them into visual representations as inspired by scientific illustrations. As opposed to traditional scientific illustration these representations are generated in real-time - they are interactive. The code generating the visualizations can be embedded in various software environments. To demonstrate this, we implemented both a desktop application and a remote-rendering server in which the pipeline is embedded. The remote-rendering server supports multi-threaded rendering and it is able to handle multiple users simultaneously. This scalability to different hardware environments, including multi-GPU setups, makes our system useful for efficient public dissemination of biological discoveries.",,,,video https://www.cg.tuwien.ac.at/research/publications/2017/mindek-2017-marion/mindek-2017-marion-Preview.avi,,2018,2017,SciVis,207,Thursday,Visualization in Biology and Medicine,9:30 AM,9:50 AM
  +SciVis,TVCG,Visualization Multi-Pipeline for Communicating Biology,"Peter Mindek, David Kouřil, Johannes Sorger, Daniel Toloudis, Blair Lyons, Graham Johnson, M. Eduard Gröller, Ivan Viola",https://www.cg.tuwien.ac.at/research/publications/2017/mindek-2017-marion/mindek-2017-marion-Paper.pdf,"We propose a system to facilitate biology communication by developing a pipeline to support the instructional visualization of heterogeneous biological data on heterogeneous user-devices. Discoveries and concepts in biology are typically summarized with illustrations assembled manually from the interpretation and application of heterogenous data. The creation of such illustrations is time consuming, which makes it incompatible with frequent updates to the measured data as new discoveries are made. Illustrations are typically non-interactive, and when an illustration is updated, it still has to reach the user. Our system is designed to overcome these three obstacles. It supports the integration of heterogeneous datasets, reflecting the knowledge that is gained from different data sources in biology. After pre-processing the datasets, the system transforms them into visual representations as inspired by scientific illustrations. As opposed to traditional scientific illustration these representations are generated in real-time - they are interactive. The code generating the visualizations can be embedded in various software environments. To demonstrate this, we implemented both a desktop application and a remote-rendering server in which the pipeline is embedded. The remote-rendering server supports multi-threaded rendering and it is able to handle multiple users simultaneously. This scalability to different hardware environments, including multi-GPU setups, makes our system useful for efficient public dissemination of biological discoveries.",,,,video https://www.cg.tuwien.ac.at/research/publications/2017/mindek-2017-marion/mindek-2017-marion-Preview.avi,,2018,2017,SciVis,207,Thursday,Visualization in Biology and Medicine,9:30 AM,9:50 AM
   SciVis,TVCG,Decision Graph Embedding for High-Resolution Manometry Diagnosis,"Julian Kreiser, Alexander Hann, Eugen Zizer, Timo Ropinski",,,,,,,,2018,2017,SciVis,207,Thursday,Visualization in Biology and Medicine,9:10 AM,9:30 AM
positive.code: TVCG,TVCG,Data Flow Analysis and Visualization for Spatiotemporal Statistical Data without Trajectory Information,"Seokyeon Kim, Seongmin Jeong, Insoo Woo, Yun Jang, Ross Maciejewski, David Ebert",http://rmaciejewski.faculty.asu.edu/papers/2017/Yun-Flow.pdf,"Geographic visualization research has focused on a variety of techniques to represent and explore spatiotemporal data. The goal of those techniques is to enable users to explore events and interactions over space and time in order to facilitate the discovery of patterns, anomalies and relationships within the data. However, it is difficult to extract and visualize data flow patterns over time for non-directional statistical data without trajectory information. In this work, we develop a novel flow analysis technique to extract, represent, and analyze flow maps of non-directional spatiotemporal data unaccompanied by trajectory information. We estimate a continuous distribution of these events over space and time, and extract flow fields for spatial and temporal changes utilizing a gravity model. Then, we effectively visualize the spatiotemporal patterns in the data by employing flow visualization techniques. The user is presented with temporal trends of geo-referenced discrete events on a map. As such, overall spatiotemporal data flow patterns help users analyze geo-referenced temporal events, such as disease outbreaks, crime patterns, etc. To validate our model, we discard the trajectory information in an origin-destination dataset and apply our technique to the data and compare the derived trajectories and the original. Finally, we present spatiotemporal trend analysis for statistical datasets including twitter data, maritime search and rescue events, and syndromic surveillance",,,,vimeo 230834322,10.1109/TVCG.2017.2666146,2017,2017,VAST,301-C,Tuesday,"Space, Time, Movement",3:20 PM,3:40 PM
  TVCG,TVCG,Evaluating Interactive Graphical Encodings for Data Visualization,"Bahador Saket, Arjun Srinivasan, Eric D. Ragan, Alex Endert",http://bahadorsaket.com/publication/encodingsPaper.pdf,"User interfaces for data visualization often consist of two main components: control panels for user interaction and visual representation. A recent trend in visualization is directly embedding user interaction into the visual representations. For example, instead of using control panels to adjust visualization parameters, users can directly adjust basic graphical encodings (e.g., changing distances between points in a scatterplot) to perform similar parameterizations. However, enabling embedded interactions for data visualization requires a strong understanding of how user interactions influence the ability to accurately control and perceive graphical encodings. In this paper, we study the effectiveness of these graphical encodings when serving as the method for interaction. Our user study includes 12 interactive graphical encodings. We discuss the results in terms of task performance and interaction effectiveness metrics.",https://medium.com/@GT_Vis/evaluating-interactive-graphical-encodings-for-data-visualization-b9b8b4bf47f8,https://github.com/gtvalab/interactive-graphical-encodings,https://github.com/gtvalab/interactive-graphical-encodings/tree/master/Supplementary%20Materials/Raw%20Data,vimeo 230834446,10.1109/TVCG.2017.2680452,2017,2017,InfoVis,301-D,Wednesday,Perception,9:50 AM,10:10 AM
  TVCG,TVCG,PETMiner - A Visual Analysis Tool for Petrophysical Properties of Core Sample Data,"Dave G. Harrison, Nick D. Efford, Quentin J. Fisher, Roy A. Ruddle",http://eprints.whiterose.ac.uk/113580/1/harrison-ieee-tvcg-2017.pdf,"The aim of the PETMiner software is to reduce the time and monetary cost of analysing petrophysical data that is obtained from reservoir sample cores. Analysis of these data requires tacit knowledge to fill ’gaps’ so that predictions can be made for incomplete data. Through discussions with 30 industry and academic specialists, we identified three analysis use cases that exemplified the limitations of current petrophysics analysis tools. We used those use cases to develop nine core requirements for PETMiner, which is innovative because of its ability to display detailed images of the samples as data points, directly plot multiple sample properties and derived measures for comparison, and substantially reduce interaction cost. An 11-month evaluation demonstrated benefits across all three use cases by allowing a consultant to: (1) generate more accurate reservoir flow models, (2) discover a previously unknown relationship between one easy-to-measure property and another that is costly, and (3) make a 100-fold reduction in the time required to produce plots for a report.",,,,vimeo 230834380,10.1109/TVCG.2017.2682865,2017,2017,SciVis,106-ABC,Friday,Applications and Visual analysis,9:10 AM,9:30 AM
  TVCG,TVCG,Indexed-Points Parallel Coordinates Visualization of Multivariate Correlations,"Liang Zhou, Daniel Weiskopf",http://www.cs.utah.edu/~zhoul/Research/mypapers/pflatsInPCP_authors.pdf,"We address the problem of visualizing multivariate correlations in parallel coordinates. We focus on multivariate correlation in the form of linear relationships between multiple variables. Traditional parallel coordinates are well prepared to show negative correlations between two attributes by distinct visual patterns. However, it is difficult to recognize positive correlations in parallel coordinates. Furthermore, there is no support to highlight multivariate correlations in parallel coordinates. In this paper, we exploit the indexed point representation of p-flats (planes in multidimensional data) to visualize local multivariate correlations in parallel coordinates. Our method yields clear visual signatures for negative and positive correlations alike, and it supports large datasets. All information is shown in a unified parallel coordinates framework, which leads to easy and familiar user interactions for analysts who have experience with traditional parallel coordinates. The usefulness of our method is demonstrated through examples of typical multidimensional datasets.",,,,vimeo 230834568,10.1109/TVCG.2017.2698041,2017,2017,InfoVis,301-D,Wednesday,Multidimensional Data,3:20 PM,3:40 PM
  TVCG,TVCG,Visual Analysis of Inclusion Dynamics in Two-Phase Flow,"Grzegorz Karch, Fabian Beck, Moritz Ertl, Christian Meister, Kathrin Schulte, Bernhard Weigand, Thomas Ertl, Filip Sadlo",,,,,,vimeo 230834468,10.1109/TVCG.2017.2692781,2017,2017,SciVis,207,Wednesday,Flow Visualization,8:50 AM,9:10 AM
  TVCG,TVCG,A Combined Eulerian-Lagrangian Data Representation for Large-scale Applications,"Franz Sauer, Jinrong Xie, Kwan-Liu Ma",,"The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously utilize information from both representations are becoming increasingly popular. However, due to their fundamentally different nature, drawing correlations between these data formats is a computationally difficult task, especially in a large-scale setting. In this work, we present a new data representation which combines both reference frames into a joint Eulerian-Lagrangian format. By reorganizing Lagrangian information according to the Eulerian simulation grid into a “unit cell” based approach, we can provide an efficient out-of-core means of sampling, querying, and operating with both representations simultaneously. We also extend this design to generate multi-resolution subsets of the full data to suit the viewer’s needs and provide a fast flow-aware trajectory construction scheme. We demonstrate the effectiveness of our method using three large-scale real world scientific datasets and provide insight into the types of performance gains that can be achieved.",,,,vimeo 230834211,10.1109/TVCG.2016.2620975,2016,2017,SciVis,207,Wednesday,Flow Visualization,9:10 AM,9:30 AM
  TVCG,TVCG,Keshif: Rapid and Expressive Tabular Data Exploration for Novices,"Mehmet Adil Yalcin, Niklas Elmqvist, Benjamin B Bederson",http://www.umiacs.umd.edu/~elm/projects/keshif/keshif.pdf,"General purpose graphical interfaces for data exploration are typically based on manual visualization and interaction specifications. While designing manual specification can be very expressive, it demands high efforts to make effective decisions, therefore reducing exploratory speed. Instead, principled automated designs can increase exploratory speed, decrease learning efforts, help avoid ineffective decisions, and therefore better support data analytics novices. Towards these goals, we present Keshif, a new systematic design for tabular data exploration. To summarize a given dataset, Keshif aggregates records by value within attribute summaries, and visualizes aggregate characteristics using a consistent design based on data types. To reveal data distribution details, Keshif features three complementary linked selections: highlighting, filtering, and comparison. Keshif further increases expressiveness through aggregate metrics, absolute/part-of scale modes, calculated attributes, and saved selections, all working in synchrony. Its automated design approach also simplifies authoring of dashboards composed of summaries and individual records from raw data using fluid interaction. We show examples selected from 160+ datasets from diverse domains. Our study with novices shows that after exploring raw data for 15 minutes, our participants reached close to 30 data insights on average, comparable to other studies with skilled users using more complex tools.",https://www.keshif.me/,https://github.com/adilyalcin/Keshif,,youtube 3Hmvms-1grU,10.1109/TVCG.2017.2723393,2017,2017,InfoVis,301-D,Wednesday,Multidimensional Data,2:40 PM,3:00 PM
  
negative.code: SciVis,TVCG,BASTet: Shareable and reproducible analysis and visualization of mass spectrometry imaging data via OpenMSI,"Oliver Ruebel, Benjamin P. Bowen",,,https://openmsi.nersc.gov/openmsi/client/bastet.html,https://github.com/biorack/BASTet,,vimeo 230835941,,2018,2017,SciVis,106-ABC,Friday,Applications and Visual analysis,9:50 AM,10:10 AM
  SciVis,TVCG,Clique Community Persistence: A Topological Visual Analysis Approach for Complex Networks,"Bastian Rieck, Ulderico Fugacci, Jonas Lukasczyk, Heike Leitte",https://osf.io/td973/,"Complex networks require effective tools and visualizations for their analysis and comparison. Clique communities have been recognized as a powerful concept for describing cohesive structures in networks. We propose an approach that extends the computation of clique communities by considering persistent homology, a topological paradigm originally introduced to characterize and compare the global structure of shapes. Our persistence-based algorithm is able to detect clique communities and to keep track of their evolution according to different edge weight thresholds. We use this information to define comparison metrics and a new centrality measure, both reflecting the relevance of the clique communities inherent to the network. Moreover, we propose an interactive visualization tool based on nested graphs that is capable of compactly representing the evolving relationships between communities for different thresholds and clique degrees. We demonstrate the effectiveness of our approach on various network types",,https://osf.io/rdktg/,,vimeo 230835775,,2018,2017,SciVis,207,Wednesday,Topology-based methods,2:20 PM,2:40 PM
  SciVis,TVCG,Dynamic Load Balancing Based on Constrained K-D Tree Decomposition for Parallel Particle Tracing,"Jiang Zhang, Hanqi Guo, Fan Hong, Xiaoru Yuan, Tom Peterka",http://www.mcs.anl.gov/papers/P7034-0417.pdf,"Particle tracing is a fundamental technique in flow field data visualization. In this work, we present a novel dynamic load balancing method for parallel particle tracing. Specifically, we employ a constrained k-d tree decomposition approach to dynamically redistribute tasks among processes. Each process is initially assigned a regularly partitioned block along with duplicated ghost layer under the memory limit. During particle tracing, the k-d tree decomposition is dynamically performed by constraining the cutting planes in the overlap range of duplicated data. This ensures that each process is reassigned particles as even as possible, and on the other hand the new assigned particles for a process always locate in its block. Result shows good load balance and high efficiency of our method.",,,,,,2018,2017,SciVis,207,Tuesday,"Mix: Foundations, uncertainty, particles",3:20 PM,3:40 PM
  SciVis,TVCG,Globe Browsing: Contextualized Spatio-Temporal Planetary Surface Visualization,"Karl Bladin, Emil Axelsson, Erik Broberg, Carter Emmart, Patric Ljung, Alexander Bock, Anders Ynnerman",https://alexanderbock.github.io/papers/vis17-bladin-globe_browsing.pdf,"Results of planetary mapping are often shared openly for use in scientific research and mission planning. In its raw format, however, the data is not accessible to non-experts due to the difficulty in grasping the context and the intricate acquisition process. We present work on tailoring and integration of multiple data processing and visualization methods to interactively contextualize geospatial surface data of celestial bodies for use in science communication. As our approach handles dynamic data sources, streamed from online repositories, we are significantly shortening the time between discovery and dissemination of data and results. We describe the image acquisition pipeline, the pre-processing steps to derive a 2.5D terrain, and a chunked level-of-detail, out-of-core rendering approach to enable interactive exploration of global maps and high-resolution digital terrain models. The results are demonstrated for three different celestial bodies. The first case addresses high-resolution map data on the surface of Mars. A second case is showing dynamic processes, such as concurrent weather conditions on Earth that require temporal datasets. As a final example we use data from the New Horizons spacecraft which acquired images during a single flyby of Pluto. We visualize the acquisition process as well as the resulting surface data. Our work has been implemented in the OpenSpace software [8], which enables interactive presentations in a range of environments such as immersive dome theaters, interactive touch tables, and virtual reality headsets.",,https://github.com/OpenSpace/OpenSpace,,vimeo 230835323,,2018,2017,Other,207,Tuesday,VIS Awards & Best Papers,9:45 AM,10:05 AM
  SciVis,TVCG,Instant Construction and Visualization of Crowded Biological Environments,"Tobias Klein, Ludovic K. Autin, Barbora Kozlikova, David Goodsell, Arthur Olson, Eduard Gröller, Ivan Viola",https://www.cg.tuwien.ac.at/research/publications/2017/klein_2017_IM/klein_2017_IM-paper.pdf,"We present the first approach to integrative structural modeling of the biological mesoscale within an interactive visual environment. These complex models can comprise up to millions of molecules with defined atomic structures, locations, and interactions. Their construction has previously been attempted only within a non-visual and non-interactive environment. Our solution unites the modeling and visualization aspect, enabling interactive construction of atomic resolution mesoscale models of large portions of a cell. We present a novel set of GPU algorithms that build the basis for the rapid construction of complex biological structures. These structures consist of multiple membrane-enclosed compartments including both soluble molecules and fibrous structures. The compartments are defined using volume voxelization of triangulated meshes. For membranes, we present an extension of the Wang Tile concept that populates the bilayer with individual lipids. Soluble molecules are populated within compartments using the Halton sequence for their distribution. Fibrous structures, such as RNA or actin filaments, are created by self-avoiding random walks. Resulting overlaps of molecules are resolved by a forced-based system. Our approach opens new possibilities to the world of interactive construction of cellular compartments. We demonstrate its effectiveness by showcasing scenes of different scale and complexity that comprise blood plasma, mycoplasma, and HIV.",,,,vimeo 230835707,,2018,2017,SciVis,207,Thursday,Visualization in Biology and Medicine,8:50 AM,9:10 AM
  SciVis,TVCG,Interactive Design and Visualization of Branched Covering Spaces,"Lawrence Roy, Prashant Kumar, Sanaz Golbabaei, Yue Zhang, Eugene Zhang",http://web.engr.oregonstate.edu/~zhange/images/Paper_BCSVis_main.pdf,"Branched covering spaces are a mathematical concept which originates from complex analysis and topology and has applications in tensor field topology and geometry remeshing. Given a manifold surface and an N-way rotational symmetry field, a branched covering space is a manifold surface that has an N-to-1 map to the original surface except at the ramification points, which correspond to the singularities in the rotational symmetry field. Understanding the notion and mathematical properties of branched covering spaces is important to researchers in tensor field visualization and geometry processing, and their application areas. In this paper, we provide a framework to interactively design and visualize the branched covering space (BCS) of an input mesh surface and a rotational symmetry field defined on it. In our framework, the user can visualize not only the BCSs but also their construction process. In addition, our system allows the user to design the geometric realization of the BCS using mesh deformation techniques as well as connecting tubes. This enables the user to verify important facts about BCSs such as that they are manifold surfaces around singularities, as well as the Riemann-Hurwitz formula which relates the Euler characteristic of the BCS to that of the original mesh. Our system is evaluated by student researchers in scientific visualization and geometry processing as well as faculty members in mathematics at our university who teach topology. We include their evaluations and feedback in the paper.",,,,vimeo 230835443,,2018,2017,SciVis,207,Wednesday,Topology-based methods,3:20 PM,3:40 PM
  SciVis,TVCG,Interactive Dynamic Volume Illumination with Refraction and Caustics,"Jens Magnus, Stefan Bruckner",,,,,,youtube 3tn6sSXw4NQ,,2018,2017,SciVis,207,Tuesday,Volume Rendering,5:15 PM,5:35 PM
  