The IEEE Scientific Visualization (SciVis) Conference solicits novel research ideas and innovative applications in all areas of scientific visualization. The scope of the conference, co-located at VIS with the annual IEEE Visual Analytics and IEEE Information Visualization Conferences, includes both fundamental research contributions within scientific visualization, as well as advances towards understanding or solving real world problems, or that impact a particular application in a significant way.
Please note that topics focused on visual analytics, e.g., computational solutions facilitated by visual interfaces to support analysis, might be a better match for the IEEE VAST Conference at IEEE VIS. Similarly, topics which clearly focus on information visualization, e.g., graphical representation of abstract data to aid cognition, might be a better match for the IEEE InfoVis Conference, also at IEEE VIS. Papers chairs reserve the right to move papers between conferences based on its topic and perceived fit.
Research contributions are welcomed across a range of topics including, but not limited to:
Visualization, rendering, and manipulation of spatial data
Visual computing, systems and methodologies
Interaction techniques and devices
Visual computing applications
Visual computing for emerging applications
A technique paper describes a new or significantly improved algorithm or technique in sufficient detail so that other researchers can reproduce the results. This technique should ideally be of general application rather than being 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, when to use it, and what the computational and other costs are.
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. Here, the focus should be on the design decisions, the implications for software / hardware structure, and comparison with other systems.
An application paper normally starts with 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. Techniques related to a single problem are normally application papers, and evaluation is often limited because many application papers are essentially custom software for a specific problem.
An evaluation paper is usually an empirical assessment of how effective a technique or system is when used by humans. As such, these often involve rigorous experimental protocols and statistical analysis, but this is not the only possible form of evaluation. Good evaluation papers go beyond statistical analysis to explain causes, construct models and predict effectiveness of related systems.
A theory paper describes aspects of the process by which humans construct visualizations to explore data or communicate with other humans. These papers do not usually involve implementation, but contribute by illuminating the role of visualization in data analysis and often by proposing models for improving visualization as a discipline.