Big data analytics is the process of examining large data sets to uncover hidden patterns and previously unknown correlations. Big data analytics has been widely used in businesses to find market trends, customer preferences, and other useful business information. The research community is also beginning to embrace this exciting and powerful technology. Considering the huge amount of data produced in scientific fields such as biology, medicine, physics, and material science, big data analytics can be a powerful means of making new scientific discoveries. Efficient and effective big data analytics requires the development of programming tools and models.

In this special issue, we invite original research articles as well as review articles on the research and development of programing foundations for scientific big data analytics.

Potential topics include but are not limited to the following:

• Programming models and environments for big data
• Visual programming approach to big data analytics
• Programming frameworks for big data in cloud computing environment
• Big data challenges in dynamic program analysis
• Program analysis for secure big data processing
• Big data challenges: A program optimization perspective
• Distributed programming in big data classification
• Developing programming tools and models for scientific big data processing