让数据融合更智能：用代码或聊天对话自动对齐不同系统的数据结构
BDI-Kit Demo: A Toolkit for Programmable and Conversational Data Harmonization
- 提供代码接口和对话界面，支持开发者与领域专家协同处理数据异构问题
- 通过自动匹配+AI建议+人工修正的迭代流程，实现高精度的数据字段对齐
- 适合需要跨系统整合数据的研究者或数据工程师快速搭建匹配管道
数据融合仍受制于模式、取值表示及领域惯例的异质性。BDI-Kit 提供可扩展的工具包，用于模式与取值匹配。它包含两个互补接口：面向开发者的 Python API，支持程序化构建融合流水线；以及面向领域专家的 AI 辅助聊天界面，可通过自然语言对话完成数据对齐。演示展示用户如何结合自动化匹配、AI 推理与人工干预，迭代地探索、验证并优化模式与取值匹配结果。两种使用场景包括：(i) 使用 Python API 组合基本操作，检查中间输出并复用转换逻辑；(ii) 通过自然语言与 AI 助手交互，获取功能支持，并根据建议逐步优化输出。
原文摘要 · Abstract (English)
Data harmonization remains a major bottleneck for integrative analysis due to heterogeneity in schemas, value representations, and domain-specific conventions. BDI-Kit provides an extensible toolkit for schema and value matching. It exposes two complementary interfaces tailored to different user needs: a Python API enabling developers to construct harmonization pipelines programmatically, and an AI-assisted chat interface allowing domain experts to harmonize data through natural language dialogue. This demonstration showcases how users interact with BDI-Kit to iteratively explore, validate, and refine schema and value matches through a combination of automated matching, AI-assisted reasoning, and user-driven refinement. We present two scenarios: (i) using the Python API to programmatically compose primitives, examine intermediate outputs, and reuse transformations; and (ii) conversing with the AI assistant in natural language to access BDI-Kit's capabilities and iteratively refine outputs based on the assistant's suggestions.
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