Suggested topics include, but are 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, 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, GPUs, 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.

Please note that papers that focus on visual analytics might be a better match for the IEEE VAST Conference at IEEE VIS. Similarly, papers that focus on information visualization might be a better match for the IEEE InfoVis Conference, also at IEEE VIS. The papers co-chairs reserve the right to move papers between these three conferences based on topic and perceived fit.