标题： LEMMA-RCA：用于根本原因分析的大规模多模态多领域数据集 显示英文标题

标题： LEMMA-RCA: A Large Multi-modal Multi-domain Dataset for Root Cause Analysis

摘要： 根本原因分析（RCA）对于提高复杂系统的可靠性和性能至关重要。然而，该领域的进展受到了缺乏大规模、开源的针对RCA的数据集的阻碍。为了弥补这一差距，我们引入了LEMMA-RCA，这是一个为跨多个领域和模态的多样化RCA任务设计的大数据集。LEMMA-RCA包含来自IT和OT操作系统的各种现实世界故障场景，涵盖微服务、供水和水处理系统，涉及数百个系统实体。我们通过在不同设置下测试八种基线方法在该数据集上的性能来评估LEMMA-RCA的质量，包括离线和在线模式以及单模态和多模态。我们的实验结果证明了LEMMA-RCA的高质量。该数据集可在https://lemma-rca.github.io/公开获取。 显示英文摘要

摘要： Root cause analysis (RCA) is crucial for enhancing the reliability and performance of complex systems. However, progress in this field has been hindered by the lack of large-scale, open-source datasets tailored for RCA. To bridge this gap, we introduce LEMMA-RCA, a large dataset designed for diverse RCA tasks across multiple domains and modalities. LEMMA-RCA features various real-world fault scenarios from IT and OT operation systems, encompassing microservices, water distribution, and water treatment systems, with hundreds of system entities involved. We evaluate the quality of LEMMA-RCA by testing the performance of eight baseline methods on this dataset under various settings, including offline and online modes as well as single and multiple modalities. Our experimental results demonstrate the high quality of LEMMA-RCA. The dataset is publicly available at https://lemma-rca.github.io/.