  We present P6, a declarative language for building high performance visual
analytics systems through its support for specifying and integrating machine
learning and interactive visualization methods. As data analysis methods based
on machine learning and artificial intelligence continue to advance, a visual
analytics solution can leverage these methods for better exploiting large and
complex data. However, integrating machine learning methods with interactive
visual analysis is challenging. Existing declarative programming libraries and
toolkits for visualization lack support for coupling machine learning methods.
By providing a declarative language for visual analytics, P6 can empower more
developers to create visual analytics applications that combine machine
learning and visualization methods for data analysis and problem solving.
Through a variety of example applications, we demonstrate P6's capabilities and
show the benefits of using declarative specifications to build visual analytics
systems. We also identify and discuss the research opportunities and challenges
for declarative visual analytics.
