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

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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 startin g point for developing process mining applications in the logistics industry.
Original languageEnglish
Title of host publicationProceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS)
PublisherSCITEPRESS
Pages290-296
Number of pages7
Volume1
ISBN (Electronic)978-989-758-509-8
ISBN (Print)978-989-758-509-8
DOIs
Publication statusPublished - 28 Apr 2021
Event23rd International Conference on Enterprise Information Systems, ICEIS 2021 - Online Conference
Duration: 26 Apr 202128 Apr 2021
Conference number: 23
http://www.iceis.org/Home.aspx

Conference

Conference23rd International Conference on Enterprise Information Systems, ICEIS 2021
Abbreviated titleICEIS 2021
CityOnline Conference
Period26/04/2128/04/21
Internet address

Keywords

  • Open Trip Model
  • Process Mining
  • Logistics
  • Event Data

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