发表机构
Institute of Applied Informatics and Formal Description Methods; Karlsruhe Institute of Technology; Institute of Production Sciences; Institute for Anthropomatics and Robotics; Fraunhofer Institute of Optronics, System Technologies and Image Exploitation; Institute of Vehicle System Technology; Institute of Information Security and Dependability; Fraunhofer Institute for Chemical Technology（应用信息学与形式描述方法研究所; 卡尔斯鲁厄理工学院; 生产科学研究所; 人机系统与机器人研究所; 弗劳恩霍夫光学技术、系统技术与图像利用研究所; 车辆系统技术研究所; 信息安全与可靠性研究所; 弗劳恩霍夫化学技术研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出基于知识图谱的虚拟过程卷宗（VPD），用于多阶段制造场景，可捕获工作流溯源、以FAIR方式提供数据集，包含本体、溯源框架和用户界面三项核心贡献。
AI 中文摘要
我们提出虚拟过程卷宗（Virtual Process Dossier，简称VPD），这是一种基于知识图谱的数据目录，同时可捕获工作流溯源。我们开发VPD用于多阶段制造用例，其中下游基于AI的优化任务需要区分各个工作流步骤中生成的数据集。VPD以FAIR方式提供这些数据集，并使前瞻性和回顾性工作流溯源明确。我们的贡献包括：（1）作为目录语义核心的VPD本体；（2）将本体实例化集成到生产环境的VPD溯源框架；（3）为用户提供与VPD知识图谱以人为中心交互的VPD用户界面。该本体和代码可在指定URL获取。
英文摘要
We propose the Virtual Process Dossier (VPD), a Knowledge Graph-based data catalogue that also captures workflow provenance. We developed VPD for multi-stage manufacturing use-cases where downstream AI-based optimization tasks require to distinct between datasets generated during individual workflow steps. VPD provides these datasets in a FAIR manner and makes both prospective and retrospective workflow provenance explicit. Our contributions are: (1) the VPD ontology that serves as the catalogue's semantic core; (2) the VPD provenance framework that integrates ontology instantiation into the production environment; and (3) the VPD user interface that provides human-centered interaction with the VPD Knowledge Graph. The ontology and code are available at https://github.com/kubeluk/VirtualProcessDossier .
