Topics include:

• Visual representations and interaction techniques including the principles for depicting information, new visual paradigms, statistical graphics, geospatial visualizations, the science of interaction, and approaches for generating visual analytic visualization and interactions.
• Data management and knowledge representation including scalable data representations for high volume and stream data, statistical and semantic signatures, and synthesis of information from diverse data sources.
• Mathematical foundations and algorithms for data transformations to allow interactive visual analysis.
• Analytical reasoning including the human analytic discourse, knowledge discovery methods, perception and cognition, and collaborative visual analytics
• Presentation, production, and dissemination methods including methods and tools for capturing the analytics process, methods for elicitation of stakeholder constraints, priorities & processes for incorporation in analysis, and storytelling for specific and varying audiences.
• Applications of visual analysis techniques, including but not limited to applications in science, engineering, humanities, business, public safety, commerce, and logistics as far as they contribute to visual analytics are of particular interest.
• Evaluation methods, visual ethical analysis such as privacy, security, & regulatory compliance, interoperability, and technology practice & experience.
• Discourse visualization and visual representations of the reasoning process.
• Algorithms and technologies which are fundamental for visual analytics, including user and device adaptivity, web interfaces and mobile or other novel devices.