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IEEE SciVis 2017 - Topics and Paper Types

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.

Topics

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
  • Volumetric data
  • Streaming data
  • Multi-resolution
  • Compression.

Visual computing, systems and methodologies

  • System and toolkit design
  • Topology-based and geometry-based techniques
  • Feature extraction and pattern analysis
  • Uncertainty visualization
  • View-dependent visualization
  • PDEs
  • Glyph-based techniques
  • Texture based techniques
  • Illustrative visualization
  • Integrating spatial and non-spatial data visualization
  • Applications of visual analytics approaches
  • Computational steering.

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 techniques

  • Large and high-res displays
  • Giga-pixel displays
  • Wrist displays/wearable displays
  • Stereo displays
  • Immersive and virtual environments
  • Mixed and augmented visualization
  • Projector-camera systems
  • Perception and cognition coupled displays
  • Small displays
  • Mobile Devices

Foundations

  • Collaborative and distributed visualization
  • Visual design and design studies
  • Mathematical theories for visualization
  • Scalability issues
  • Visualization verification
  • 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
  • Crowdsourcing
  • Human computation

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

Paper Types

Paper Type: Technique

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.

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. Here, the focus should be on the design decisions, the implications for software / hardware structure, and comparison with other systems.

Paper Type: Application

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.

Paper Type: Evaluation

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.

Paper Type: Theory

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.

Papers Co-Chairs

  • Ingrid Hotz, Link√∂ping University, Sweden
  • Mike Kirby, University of Utah, USA
  • Xiaoru Yuan, Peking University, China

Email: scivis_papers@ieeevis.org.