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.

中文翻译：

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P6：在视觉分析中集成机器学习的声明性语言

我们介绍了 P6，这是一种声明式语言，通过它支持指定和集成机器学习和交互式可视化方法来构建高性能可视化分析系统。随着基于机器学习和人工智能的数据分析方法不断进步，可视化分析解决方案可以利用这些方法更好地利用大型复杂数据。然而，将机器学习方法与交互式视觉分析相结合是具有挑战性的。现有的声明式编程库和可视化工具包缺乏对耦合机器学习方法的支持。通过为可视化分析提供声明式语言，P6 可以让更多开发人员创建可视化分析应用程序，将机器学习和可视化方法结合起来进行数据分析和问题解决。通过各种示例应用程序，我们展示了 P6 的功能并展示了使用声明式规范构建可视化分析系统的好处。我们还确定并讨论了声明式可视化分析的研究机会和挑战。