Andrew Y. Ng

The AnIML Ontology: Enabling Semantic Interoperability for Large-Scale Experimental Data in Interconnected Scientific Labs

AnIML本体：实现互联科学实验室大规模实验数据的语义互操作性

Wilf Morlidge, Elliott Watkiss-Leek, George Hannah, Harry Rostron, Andrew Ng, Ewan Johnson, Andrew Mitchell, Terry R. Payne, Valentina Tamma, Jacopo de Berardinis

机构 * School of Computer Science & Informatics, University of Liverpool（利物浦大学计算机科学与信息学院） ； Unilever Plc. Materials Innovation Factory, University of Liverpool（联合利华公司材料创新工厂，利物浦大学） 纠错

AI总结 本文提出AnIML本体，通过专家在环方法结合LLM需求提取与协同本体工程，实现AnIML与Allotrope数据格式的语义对齐，解决异构实验数据系统的互操作性问题。

Comments Accepted at the 38th International Conference on Advanced Information Systems Engineering (CAiSE 2026)

IDEA2: Expert-in-the-loop competency question elicitation for collaborative ontology engineering

IDEA2: 专家在环的协作本体工程能力问题 elicitation

Elliott Watkiss-Leek, Reham Alharbi, Harry Rostron, Andrew Ng, Ewan Johnson, Andrew Mitchell, Terry R. Payne, Valentina Tamma, Jacopo de Berardinis

机构 * School of Computer Science and Informatics, University of Liverpool（利物浦大学计算机科学与信息学院） ； College of Computer Science and Engineering, Taibah University（塔伊巴大学计算机科学与工程学院） ； Unilever Plc., Materials Innovation Factory, University of Liverpool（联合利华公司，利物浦大学材料创新工厂） 纠错

AI总结 IDEA2通过整合大语言模型和专家反馈，解决本体工程中能力问题提取的瓶颈，提升问题相关性和可接受性。