支持本体的AI模型与数据集管理
Ontology-supported AI Model and Dataset Management
- FZI Research Center for Information Technology（FZI信息技术研究中心）
- University of Tübingen（蒂宾根大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出一款融入本体的AI模型交换平台，用于工业场景下AI模型与数据集的交换管理，通过实时关键系统用例验证其实用性。
AI中文摘要：
近年来，大量研究聚焦于改进AI方法及其应用，核心在于追踪进展、实现透明比较并深化对AI的理解。在此过程中，不同机构生成并使用大量需追踪、溯源和管理的资产，且发现与当前任务相关的资产至关重要。本文旨在探究工业场景下，有效交换和管理AI模型及相关资产、消除语义鸿沟所需的条件。我们推出一款AI模型交换平台，该平台便于AI模型与数据集的使用、交换及分析，其融入的本体可深化对相关任务需求的共同理解，助力解决上述问题。最后，我们通过实时关键系统场景中的用例示例阐明该平台的实用性。
英文摘要：
Recently, there has been a great deal of research into improving AI methods and their application. The main focus is on tracking progress, enabling transparent comparisons, and fostering a more profound understanding of AI. In that process, different organizations generate and use plenty of assets that need to be tracked, traced and managed. Moreover, it is important to discover assets relevant for the task at hand. This paper presents research aiming to contribute to answering the question of what is required to exchange and manage AI models and related assets effectively without semantic gaps in an industrial context. We introduce a platform for AI model exchange, which facilitates the usage, exchange, and analysis of AI models and datasets. The platform incorporates an ontology that can foster a more profound common understanding of what is required in these tasks and help tackle the issues mentioned above. Finally, we elucidate the utility of the platform through the illustration of a use case in the context of real-time critical systems.
