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SciVis Papers

IEEE VIS 2016 is the premier forum for advances in visualization for academia, government, and industry. This event brings together researchers and practitioners with a shared interest in visualization techniques, tools, and technology. The IEEE Scientific Visualization (SciVis) Conference solicits novel research ideas and innovative applications in all areas of scientific visualization.

Papers accepted to IEEE SciVis will appear in a special issue of the IEEE Transactions on Visualization and Computer Graphics (TVCG). This special issue will be published online the first day of the conference. The acceptance rate is anticipated to be similar to that of 2014 and 2015 subject to the decisions resulting from the review process. After initial notification of review results, conditionally accepted papers (including supplemental material) will undergo a revision and review cycle in order to ensure that they are acceptable for publication and presentation in the journal. The paper and supplemental material will also be submitted to the IEEE Digital Library.

Of the paper types, IEEE SciVis has always had a strong emphasis on technique papers. While SciVis 2016 seeks submissions in all areas of scientific visualization, it particularly welcomes papers that give emphasis to systems for (system paper type) and applications of (application paper type) scientific visualization. In particular, papers that make advances towards understanding or solving real world problems, or that impact a particular application in a significant way are welcome.


Abstract submission (MANDATORY) Monday, March 21, 2016
Paper submission Thursday, March 31, 2016
Notification of results of first review cycle Monday, June 6, 2016
Paper submission for second review cycle Monday, June 27, 2016
Final notification Monday, July 11, 2016
Camera ready copy Monday, August 1, 2016

All deadlines are at 5:00pm Pacific Time (PDT).


All three conferences appearing at IEEE VIS 2016 (VAST, InfoVis, and SciVis) use the Precision Conference System (PCS) to handle their submission and reviewing process. PCS is available at When submitting your manuscript please make sure that you submit it to your intended conference by clicking the appropriate conference header in the conference system landing page. If you are unsure which venue you should submit to, you can use the call for papers on this website, as well as last year’s published proceedings as a guideline.


When preparing your submission, please make sure that you carefully read and adhere to the submission guidelines.


The IEEE Scientific Visualization conference is soliciting papers on all topics in visualization and visual computing research. Besides the traditional scientific visualization research areas, we encourage submissions from related areas such as visual computing, machine learning, data analytics, data sciences etc. that will broaden the foundation of scientific visualization. We also welcome papers that showcase novel use of scientific visualization across the full range of application domains.

Suggested topics for papers include, but are not limited to:

  • Visualization, rendering, and manipulation of spatial data. Scalar, vector and tensor fields, flow fields, regular and unstructured grids, point-based data, temporal data, volumetric data, topology-based and geometry-based techniques, PDEs, time-varying data, multidimensional multi-field, multi-modal, and multivariate data, streaming data, multi-resolution, compression.
  • Interaction techniques and devices. User interfaces, interaction design, coordinated and multiple views, data editing for validation, manipulation and deformation, multimodal input devices, haptics for visualization, mobile and ubiquitous visualization, visual interaction for data science, interaction with visualizations in different display environments.
  • Data science. Large-scale computing, storage and data analytics, distributed, cluster, and grid computing, scalable data management on and off the cloud, high-performance computing on multi-core, GPUs, FPGA, and embedded devices, information extraction and knowledge discovery from big data, petascale visualization, application of computer vision techniques, statistical modeling, data mining, machine learning, clustering techniques, reduced-order modeling, visual steering for data retrieval.
  • Display technologies. Large and high-res displays, giga-pixel displays, wrist-displays, stereo displays, immersive and virtual environments, mixed and augmented visualization, projector-camera systems, perception and cognition coupled displays.
  • Foundations. 
Collaborative and distributed visualization, visual design and design studies, mathematical theories for visualization, scalability issues, uncertainty visualization, visualization verification, view-dependent visualization, information theoretic approaches, perception theory, color, texture, scene and motion perception, knowledge-assisted visualization.
  • Evaluation. 
Usability studies and task analysis, design and user studies, validation and verification visualization, statistical techniques, crowd-sourcing, human computation.
  • Visual computing systems and methodologies. System and toolkit design, glyph-based techniques, illustrative visualization, integrating spatial and non-spatial data visualization, applications of visual analytics approaches, computational steering.
  • Visual computing applications. 
Mathematics, physical sciences and engineering, earth, space, and environmental sciences, flow fields, terrain visualization, geographic/geospatial visualization, molecular, biomedical and medical visualization, bioinformatics visualization, software visualization, business and finance visualization, social and information sciences, education, humanities, for the masses, multimedia (image/video/music).
  • Visual computing for emerging applications. 
Nano-assembly, live cell imaging, imaging genetics, micro-biology, robotics, sensor networks, cybersecurity, urban science, computational architecture and others.


James Ahrens, Los Alamos National Laboratory
Mike Kirby, University of Utah
Jos Roerdink, University of Groningen

Email: scivis_papers(at)