The IEEE Scientific Visualization (SciVis) conference solicits original research papers on a diverse set of topics related to scientific visualization. Papers may contribute new or improved visual encoding or interaction techniques; evaluations of techniques and tools; models or theories related to scientific visualization; systems that support visual data analysis; and the application of scientific visualization to a broad range of real-world contexts and domains.
Research contributions are welcomed across a range of topics including, but not limited to:
- Visualization, rendering, and manipulation of spatial data: scalar, vector, and tensor fields; multidimensional, multi-field, multi-modal, and multivariate data; time-varying data; regular and unstructured grids; point-based data; and volumetric data.
- Foundations: visualization taxonomies and models; mathematical theories for visualization; perception (theory, color, texture, scene, motion); cognition; aesthetics; information theoretic approaches; knowledge-assisted visualization; presentation; production; dissemination; and visual design.
- Systems and methodologies: system and toolkit design; topology-based and geometry-based techniques; feature extraction and pattern analysis; glyph-based, texture-based, and pixel-oriented techniques; uncertainty, view-dependent, and illustrative visualization; visual storytelling; computational steering; sonification; collaborative and distributed visualization; and integrating spatial and non-spatial data visualization.
- Large data visualization: parallel, distributed, cluster, and grid computing; high-performance computing on multi-core, GPU, FPGA, and embedded devices; petascale and exascale visualization; scalability; visualization over networks; compression; multi-resolution techniques; and streaming data.
- Data science: scalable data management on and off the cloud; storage and data analytics; information extraction and knowledge discovery from big data; statistical modeling; data mining; machine learning, including deep learning; clustering techniques; application of computer vision techniques; and visual steering for data retrieval.
- Interaction: human-computer interaction for visualization; interaction design; coordinated multiple views; brushing & linking; focus & context; zooming and navigation; data editing, manipulation, and deformation; guided visualization; multimodal input devices; haptics for visualization; mobile and ubiquitous visualization; and interaction with visualizations in different display environments.
- Display techniques: large and high-resolution displays; gigapixel displays; small displays; mobile devices; wrist and wearable displays; stereo displays; immersive and virtual environments; mixed and augmented visualization; and projector-camera systems.
- Evaluation and user studies: task and requirements analysis; metrics and benchmarks; qualitative evaluation; quantitative evaluation; laboratory studies; eye tracking studies and studies with other physiological sensors; field studies; usability studies; design studies; validation and verification; crowdsourcing; and human computation.
- Application areas of visualization: mathematics; physical sciences and engineering; earth, space, and environmental sciences; urban science; business and finance; social and information sciences; education; humanities; multimedia (image/video/music); robotics; sensor networks; cybersecurity; visualization for visualization research; visualization for the masses; terrain visualization; geographic/geospatial visualization; software visualization; bioinformatics; and molecular, biomedical, and medical visualization.
VIS papers often fall into one or more of five main categories: technique & algorithm; system; application & design study; empirical study; or theory & model. Although your main paper type has to be specified during the paper submission process, papers can include elements of more than one of these categories.
Paper Type: Technique & Algorithm
A technique or algorithm paper introduces a novel technique or algorithm that has not previously appeared in the literature, or that significantly extends known techniques or algorithms. The technique or algorithm description provided in the paper should be complete enough that a competent graduate student in visualization could implement the work, and the authors should create a prototype implementation of the methods. This technique should ideally be of general application rather than be restricted to a single task or single source of data, and the exposition should be focused on what the technique does, how it does it, the tasks and datasets for which this new method is appropriate, and what the computational and other costs are. Evaluation is likely to strengthen technique papers.
- Günther, T., Schulze, M., and Theisel, H. (2016). Rotation Invariant Vortices for Flow Visualization. IEEE Transactions on Visualization and Computer Graphics, 22(1).
- Jönsson, D. and Ynnerman, A. (2017). Correlated Photon Mapping for Interactive Global Illumination of Time-Varying Volumetric Data. IEEE Transactions on Visualization and Computer Graphics, 23(1).
- Tierny, J. and Carr, H. (2017). Jacobi Fiber Surfaces for Bivariate Reeb Space Computation. IEEE Transactions on Visualization and Computer Graphics, 23(1).
Paper Type: System
A system paper describes a solution to a problem where the major task is building a large complex software artifact, applying largely known visualization techniques. The system that is described is both novel and important, and has been implemented. Here, the focus should be on the design decisions, the implications for software / hardware structure, and comparison with other systems. The comparison includes specific discussion of how the described system differs from and is, in some significant respects, superior to those systems.
- Moreland, K., Sewell, C., Usher, W., Lo, L.-T., Meredith, J., Pugmire, D., Kress, J., Schroots, H., Ma, K.-L., Childs, H., Larsen, M., Che, C.-M., Maynard, R., and Geveci, B. (2016). VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures. IEEE Computer Graphics & Applications, 36(3).
- Tierny, J., Favelier, G., Levine, J., Guenet, C., and Michaux, M. (2018). The Topology Toolkit. IEEE Transactions on Visualization and Computer Graphics, 24(1).
- Wald, I., Johnson, G. P., Amstutz, J., Brownlee, C., Knoll, A., Jeffers, J., Günther, J., and Navratil, P. (2017). OSPRay – A CPU Ray Tracing Framework for Scientific Visualization. IEEE Transactions on Visualization and Computer Graphics, 23(1).
Paper Type: Application & Design Study
An application or design study paper explores the choices made when applying visualization techniques in an application area, for example relating the visual encodings and interaction techniques to the requirements of the target task. These papers typically include an encapsulated description of a problem domain and the questions to be resolved by visualization, then describes the application of visualization to the task, any novel techniques developed, and how the visualization solution answered the questions posed. The results of the study, including insights generated in the application domain and visualization knowledge generated through the research process, should be clearly conveyed. The work will be judged by the design lessons learned or insights gleaned for visualization research - which may or may not include novel visualization techniques, algorithms, or systems - on which future contributors can build. We invite submissions on any application area.
- Dutta, S., Chen, C.-M., Heinlein, G., Shen, H.-W., and Chen, J.-P. (2017). In Situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations. IEEE Transactions on Visualization and Computer Graphics, 23(1).
- Miao, H., De Llano, E., Sorger, J., Ahmadi, Y., Kekic, T., Isenberg, T., Gröller, E., Barišić, I., and Viola, I. (2018). Multiscale Visualization and Scale-Adaptive Modification of DNA Nanostructures. IEEE Transactions on Visualization and Computer Graphics, 24(1).
Paper Type: Empirical Study
An empirical study paper explores the usage of visualization by people or provides a detailed analysis of the characteristics of a visualization approach, for example, its technical performance. This kind of paper presents a study, either qualitative or quantitative, of visualization techniques or systems. The research contribution will be judged on the validity and importance of the results, including, where appropriate, the definition of hypotheses, tasks, data sets, the rigorous collection and examination/analysis/coding of data, the selection of subjects and cases, as well as validation, discussion, and conclusions.
- Correa, C. D., Hero, R., and Ma, K.-L. (2011). A Comparison of Gradient Estimation Methods for Volume Rendering on Unstructured Meshes. IEEE Transactions on Visualization and Computer Graphics, 17(3).
- Lind, A. J. and Bruckner, S. (2017). Comparing Cross-Sections and 3D Renderings for Surface Matching Tasks Using Physical Ground Truths. IEEE Transactions on Visualization and Computer Graphics, 23(1).
- Lindemann, F. and Ropinski, T. (2011). About the Influence of Illumination Models on Image Comprehension in Direct Volume Rendering. IEEE Transactions on Visualization and Computer Graphics, 17(12).
- Stevens, A. H., Butkiewicz, T., and Ware, C. (2017). Hairy Slices: Evaluating the Perceptual Effectiveness of Cutting Plane Glyphs for 3D Vector Fields. IEEE Transactions on Visualization and Computer Graphics, 23(1).
Paper Type: Theory & Model
A theory or model paper presents new interpretations of the foundational theory of visualization, including models, typologies or taxonomies of the design, development, evaluation, or use of visualization in particular contexts. These papers do not require implementation, but contribute by illuminating how visualization techniques complement and exploit properties of human vision and cognition, as well as how researchers conduct effective and rigorous visualization studies.
- Bruckner, S., Isenberg, T., Ropinski, T., and Wiebel, A. (2019). A Model of Spatial Directness in Interactive Visualization. IEEE Transactions on Visualization and Computer Graphics, 25(8).
- Bujack, R., Turton. T. L., Samsel, F., Ware, C., Rogers, D. H., and Ahrens, J. (2018). The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps. IEEE Transactions on Visualization and Computer Graphics, 23(1).
- Kindlmann, G. and Scheidegger, C. (2014). An Algebraic Process for Visualization Design. IEEE Transactions on Visualization and Computer Graphics, 20(12).
- Marai, G. A. (2018). Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization. IEEE Transactions on Visualization and Computer Graphics, 24(1).
- Peter Lindstrom, Lawrence Livermore National Laboratory
- Luis Gustavo Nonato, Universidade de Sao Paulo
- Han-Wei Shen, The Ohio State University
- Rüdiger Westermann, Technical University of Munich