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Paper presentation: 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 starting point for developing process mining applications in the logistics industry.
EVALUATING THE USE OF THE OPEN TRIP MODEL FOR PROCESS MINING:
AN INFORMAL CONCEPTUAL MAPPING STUDY IN LOGISTICS
J.P.S. PIEST (SPEAKER), J.A. CUTINHA, R.H. BEMTHUIS, F.A. BUKHSH
AREA 1: DATABASES AND INFORMATION SYSTEMS INTEGRATION
23RD INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS
Motivation
Process Mining in Logistics
Interoperability Challenges
Introduction of the Open Trip Model
Informal Conceptual Mapping Study
Step-by-Step Walkthrough
Conclusion
Outlook
Discussion
4/28/2021
This research is financially supported by the Dutch Ministry of Economic Affairs and co-financed via TKI
DINALOG. Funding for this work has been granted by the ICCOS project (grant no. 2018-2-169TKI) 2
OUTLINE
RESEARCH PAPER PRESENTATION
4/28/2021Typical interoperability scenario in Logistics
(adapted from OTM presentation) 3
MOTIVATION
WHAT BROUGHT US HERE?
Systematic Mapping Study (dos Santos Garcia et. al., 2019):
Less than 5% of the studies is in the Logistics domain;
27 studies identified and examined;
Rich spectrum of use cases for process mining.
Generalization is difficult due to complex, dynamic and heterogenous
nature of event data in Logistics (Intayoad and Becker, 2018);
Established approaches and tools focus on working with noisy data.
4/28/2021 4
PROCESS MINING IN LOGISTICS
CURRENT STATE OF THE ART
The Open Trip Model eliminates certain interoperability issues by
linking different Information Systems and devices (Lont, et. al., 2018);
Need for new research for discretizing, aggregating and correlating
event data for tracing the overall business performance (Cabanillas et al.,
2013; Wang et al., 2014);
Current literature pays little attention to unified standards and process
definitions.
4/28/2021 5
INTEROPERABILITY CHALLENGES
NEED FOR UNIFICATION AND STANDARDIZATION OF PROCESS MODELS
Initiated and developed by Simacan;
Managed by SUTC, acting on behalf of:
Transport Logistiek Nederland;
Evofenedex;
Dalti.
Centered around event data;
Entities: representing logistics objects;
Lifecycles: workflow and order over time.
4/28/2021Current version 5 of the OTM 6
OPEN TRIP MODEL
OPEN, FLEXIBLE DATA SHARING MODEL
Goal:
Unified storage, integration,
interoperability, and querying of
logistic event data.
Minimum requirements:
Case ID
Event / activity
Timestamp
Resource
4/28/2021Adapted OTM data model version 4.2 linked to
the minimum process mining requirements 7
INFORMAL CONCEPTUAL MAPPING STUDY
EVALUATING THE USE OF THE OTM FOR PROCESS MINING
1. Describe the scenario;
2. Identify and map entities;
3. Identification of events;
4. Extract the event data;
5. Create the event log;
6. Generate the process model.
4/28/2021https://www.opentripmodel.org/docs/walkthrough 8
STEP-BY-STEP WALKTHROUGH
USING THE DEFAULT OTM SCENARIO AND SAMPLE DATA
Initial support that the OTM can fulfil minimum requirements for
process mining, however, further experimental development required;
Demonstration based on simple scenario with synthetic data;
Foundation for future research about interoperability challenges and
unifying process mining models based on industry standards;
Starting point for developing process mining applications in the
logistics industry based on the step-by-step approach and identified
use cases.
4/28/2021 9
CONCLUSION
INTERMEDIATE RESULTS, CONTRIBUTION AND LIMITATIONS
Systematically mapping the process mining spectrum to the OTM
based on formal methods and techniques in a full implementation of
OTM;
Case study research to test robustness with real-life datasets in
multiple use cases to determine if implementations of OTM and real-
world data are also as straightforward to map for process mining;
Comparison study involving organizations that implement and do not
implement the OTM, solution alternatives (e.g., the GS1 EPICS) and
alternative approached (e.g., data mining, machine learning).
4/28/2021 10
OUTLOOK
DIRECTIONS FOR FUTURE RESEARCH AND DEVELOPMENT
4/28/2021Image licensed under CC BY-NC 11
DISCUSSION
PLEASE SHARE YOUR THOUGHTS AND ASK YOUR QUESTIONS
EVALUATING THE USE OF THE OPEN TRIP MODEL FOR PROCESS MINING:
AN INFORMAL CONCEPTUAL MAPPING STUDY IN LOGISTICS
J.P.S. PIEST (SPEAKER), J.A. CUTINHA, R.H. BEMTHUIS, F.A. BUKHSH
AREA 1: DATABASES AND INFORMATION SYSTEMS INTEGRATION
23RD INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS
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