SchemaLink：用于LinkML模式管理的智能Web编辑器

中文摘要 AI 辅助

研究背景与问题：LinkML是一种适用于表示各类生物医学数据的结构与内容约束的语言，尽管是较新的提案，已在多个生物医学场景中应用，但开发和维护LinkML模式存在诸多挑战，尤其是对新手管理员而言，非专业的生物管理员可能难以掌握LinkML语法和最佳实践，需花费大量时间精力才能开发出结构良好的模式。提出的方法：本文提出SchemaLink，这是一个基于Web的环境，用于图形化构建和增强LinkML模式，满足以下要求：(i)引入用于指定LinkML模式的图形语言；(ii)统一相似场景下模式的指定方式；(iii)利用基于RAG的方法简化设计和管理流程，协助管理员从零创建新模式并编辑已开发的模式。实验设置与结果：多项实验分析通过基于AI的编辑工具验证了所生成LinkML模式的质量。结论与意义：SchemaLink可在线获取，代码和测试数据作为开源资源在GitHub上提供，包括schemalink-webapp和schemalink-api。

英文摘要

Motivation: LinkML is a suitable language for the representation of the structural and content constraints of different kinds of biomedical data. Even if it is a quite recent proposal, it has been applied in several biomedical contexts. Developing and maintaining LinkML schemas presents several challenges, particularly for novice curators. Non-expert bio-curators may struggle with LinkML syntax and best practices, requiring significant time and effort to develop well-structured schemas. Results: In this paper we propose SchemaLink, a web-based environment for the graphical construction and enhancement of LinkML schemas that address the following requirements: $(i)$ introduce a graphical language for the specification of LinkML schemas, $(ii)$ make uniform the specification of schemas in similar contexts, $(iii)$ simplify the design and curation processes by exploiting a RAG-based approach to assist curators in creating new schemas from scratch and editing already developed ones. Several experimental analyses show the quality of the produced LinkML schemas through the AI-based editing facilities. Availability and Implementation: SchemaLink is available online at: https://SchemaLink.biodata.di.unimi.it. SchemaLink code and testing data are available as open-source on GitHub at: https://github.com/AnacletoLAB/{schemalink-webapp,schemalink-api}.

发表机构

• University of Milano（米兰大学）
• Lawrence Berkeley National Lab（劳伦斯伯克利国家实验室）

机构由 AI 辅助整理，请以论文原文为准。