Orange Lab：通过嵌入式交互工作流降低数据挖掘门槛
Orange Lab: Lowering Barriers to Data Mining through Embedded Interactive Workflows
AI总结：
提出Orange Lab，一种基于Web的可视化数据分析环境，通过组件展示范式将机器学习工作流嵌入任意网页，实现动态交互与数据驱动叙事，降低数据科学使用门槛。
摘要：
虽然数据分析工作流的可视化编程已成为数据科学民主化的重要工具，但此类系统仍主要局限于独立应用程序，并且对将其可视化分析解决方案过渡到交互式网络环境的支持有限。因此，数据分析管道难以共享、嵌入和适应用户面向的分析工具。我们提出了Orange Lab，一个基于Web的协作式可视化数据分析环境。其核心是，Orange Lab使用户能够从模块化组件中可视化地构建机器学习工作流，其中任何组件中的交互都会无缝地传播到整个工作流，将静态管道转变为支持探索和数据驱动叙事的动态响应系统。我们的关键贡献是组件展示，这是一种范式，允许作者将选定的工作流组件或其界面部分嵌入到任意网络上下文中，创建同步的交互式界面，同时隐藏底层工作流的复杂性。这支持开发定制化的分析视图和叙事驱动的体验，将数据分析直接集成到在线材料中。我们通过在数据素养教育中的部署来展示该方法，其中嵌入式组件引导学生动手探索机器学习概念，而无需了解底层系统，表明Orange Lab有效降低了入门门槛并支持数据科学的民主化。
英文摘要：
While visual programming of data analysis workflows has become an important vehicle for the democratization of data science, such systems remain largely confined to standalone applications and offer limited support for transitioning their visual analytics solutions into interactive web environments. As a result, data analysis pipelines are difficult to share, embed, and adapt into user-facing analytical tools. We present Orange Lab, a web-based collaborative environment for visual data analytics. At its core, Orange Lab enables users to visually construct machine learning workflows from modular components, where interactions in any component propagate seamlessly through the workflow, turning static pipelines into dynamic, reactive systems that support exploration and data-driven storytelling. Our key contribution is component exposition, a paradigm that allows authors to embed selected workflow components, or parts of their interfaces, into arbitrary web contexts, creating synchronized, interactive interfaces while hiding underlying workflow complexity. This enables the development of tailored analytical views and narrative-driven experiences that integrate data analysis directly into online materials. We demonstrate the approach through deployments in data literacy education, where embedded components guide students in hands-on exploration of machine learning concepts without requiring knowledge of the underlying system, showing that Orange Lab effectively lowers barriers to entry and supports the democratization of data science.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
