用对话AI查询澳洲自然史博物馆170万份标本数据，让公众轻松访问复杂科学资源。
Conversational AI-Enhanced Exploration System to Query Large-Scale Digitised Collections of Natural History Museums
- 通过对话式AI和地图可视化，支持自然语言查询标本数据
- 集成大模型函数调用能力，实时获取外部API中的结构化数据
- 适合对自然史研究感兴趣的公众及教育工作者使用
自然史博物馆的数字化工作产生了大量藏品数据，但其规模与科学复杂性常阻碍公众访问与理解。传统数据库依赖关键词搜索或需专业模式知识，限制探索。本文设计并开发了一套基于对话AI的探索系统，可查询澳大利亚博物馆生命科学藏品中近170万条数字化标本记录。系统采用以人为中心的设计流程，包含交互式地图用于空间可视化探索，以及自然语言对话代理，能检索详细标本信息并回答馆藏相关问题。该系统利用现代大模型的函数调用能力，动态从外部API获取结构化数据，实现对大规模且频繁更新数据集的快速实时交互。本研究提出一种将大型博物馆藏品与自然语言查询相连接的新方法，为未来自然史博物馆科学AI代理的设计提供参考。
原文摘要 · Abstract (English)
Recent digitisation efforts in natural history museums have produced large volumes of collection data, yet their scale and scientific complexity often hinder public access and understanding. Conventional data management tools, such as databases, restrict exploration through keyword-based search or require specialised schema knowledge. This paper presents a system design that uses conversational AI to query nearly 1.7 million digitised specimen records from the life-science collections of the Australian Museum. Designed and developed through a human-centred design process, the system contains an interactive map for visual-spatial exploration and a natural-language conversational agent that retrieves detailed specimen data and answers collection-specific questions. The system leverages function-calling capabilities of contemporary large language models to dynamically retrieve structured data from external APIs, enabling fast, real-time interaction with extensive yet frequently updated datasets. Our work provides a new approach of connecting large museum collections with natural language-based queries and informs future designs of scientific AI agents for natural history museums.
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