NOVA: A Practical Method for Creating Notebook-Ready Visual Analytics

Understand

How can we develop visual analytics (VA) tools that can be easily adopted? Visualization researchers have developed a large number of web-based VA tools to help data scientists in a wide range of tasks.

• However, adopting these standalone systems can be challenging, as they require data scientists to create new workflows to streamline the VA processes.
• Recent surveys suggest computational notebooks have been dominating data scientists' analytical workflows, as these notebooks seamlessly combine text, code, and visualization, allowing users to rapidly iterate code experiments.
• To help visualization researchers develop VA tools that can be easily integrated into existing data science workflows, we present NOVA, a simple and flexible method to adapt web-based VA systems for notebooks.