Topics include:

• Distributed, parallel, and multi-threaded computation
• Streaming methods
• Innovative software solutions
• Advanced hardware and GPU-based approaches
• Hierarchical data storage, retrieval, processing, and rendering
• Sampling, approximate query processing, and progressive computation
• Collection, management, and curation of massive datasets
• Scalable visualization and exploration methods
• Ensemble data visualization and analysis
• In-situ data analysis
• Best practices for large data visualization
• End-to-end system solutions in a large data context
• Industry solutions for big data analysis and visualization
• Collaboration or/and co-design of large data analysis with domain experts
• Topics in cognitive issues specific to manipulating and understanding large data
• Application case studies
• New challenges in visualizing experimental, observational, or simulation data