Evaluating the Use of the Open Trip Model for Process Mining: An Informal Conceptual Mapping Study in Logistics

J. Piest, Jennifer Alice Cutinha, R. Bemthuis, F. Bukhsh
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引用次数: 4

Abstract

When aggregating logistic event data from different supply chain actors and information systems for process mining, interoperability, data loss, and data quality are common challenges. This position paper proposes and evaluates the use of the Open Trip Model (OTM) for process mining. Inspired by the current industrial use of the OTM for reporting and business intelligence, we believe that the data model of OTM can be utilized for unified storage, integration, interoperability, and querying of logistic event data. Therefore, the OTM data model is mapped to a generic event log structure to satisfy the minimum requirements for process mining. A demonstrative scenario is used to show how event data can be extracted from the OTM’s default scenario dataset to create an event log as the starting point for process mining. Thus, this approach provides a foundation for future research about interoperability challenges and unifying process mining models based on industry standards, and a starting point for developing process mining applications in the logistics industry.
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评价开放行程模型在过程挖掘中的应用:物流中的非正式概念映射研究
在聚合来自不同供应链参与者和信息系统的物流事件数据以进行流程挖掘时,互操作性、数据丢失和数据质量是常见的挑战。本立场文件提出并评估了开放式行程模型(OTM)在过程挖掘中的使用。受到OTM用于报告和商业智能的当前工业用途的启发,我们相信OTM的数据模型可以用于统一存储、集成、互操作性和查询物流事件数据。因此,将OTM数据模型映射到通用的事件日志结构,以满足流程挖掘的最低要求。演示场景用于展示如何从OTM的默认场景数据集中提取事件数据,以创建事件日志作为流程挖掘的起点。因此,该方法为未来研究互操作性挑战和基于行业标准的统一流程挖掘模型提供了基础,并为开发物流行业的流程挖掘应用提供了起点。
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