Towards a Domain-Specific Modeling Language for Extracting Event Logs from ERP Systems
Source abstract
Abstract
Enterprise resource planning (ERP) systems are often seen as viable sources of data for process mining analysis. To perform most of the existing process mining techniques, it is necessary to obtain a valid event log that is fully compliant with the eXtensible Event Stream (XES) standard. In ERP systems, such event logs are not available as the concept of business activity is missing. Extracting event data from an ERP database is not a trivial task and requires in-depth knowledge of the business processes and underlying data structure. Therefore, domain experts require proper techniques and tools for extracting event data from ERP databases. In this paper, we present the full specification of a domain-specific modeling language for facilitating the extraction of appropriate event data from transactional databases by domain experts. The modeling language has been developed to support complex ambiguous cases when using ERP systems. We demonstrate its applicability using a case study with real data and show that the language includes constructs that enable a domain expert to easily model data of interest in the log extraction step. The language provides sufficient information to extract and transform data from transactional ERP databases to the XES format.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Business Process Modeling and Analysis · Service-Oriented Architecture and Web Services · ERP Systems Implementation and Impact
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Organizational Sciences, University of Belgrade, 11010 Belgrade, Serbia
References (30)
Show source-provided references
1. Utama, N.I., Sutrisnowati, R.A., Kamal, I.M., Bae, H., and Park, Y.J. (2020). Mining shift work operation from event logs. Appl. Sci., 10.10.3390/app10207202 ↗
2. Van der Aalst, W.M.P. (2016). Process Mining: Data Science in Action, Springer. [2nd ed.].10.1007/978-3-662-49851-4 ↗
3. Object-Centric Process Mining: Dealing with Divergence and Convergence in Event Data
4. vom Brocke, J., and Schmiedel, T. (2015). Extracting Event Data from Databases to Unleash Process Mining. BPM—Driving Innovation in a Digital World. Management for Professionals, Springer.10.1007/978-3-319-14430-6 ↗
5. OBDA for log extraction in process mining
6. Prostean, G., Lavios Villahoz, J., Brancu, L., and Bakacsi, G. (2020). Event Log Extraction for the Purpose of Process Mining: A Systematic Literature Review. Innovation in Sustainable Management and Entrepreneurship (SIM 2019). Springer Proceedings in Business and Economics, Springer.10.1007/978-3-030-44711-3 ↗
7. Building a valuable event log for process mining: An experimental exploration of a guided process10.1080/17517575.2019.1587788 ↗
8. Erdogan, T.G., and Tarhan, A. (2018). A goal-driven evaluation method based on process mining for healthcare processes. Appl. Sci., 8.10.3390/app8060894 ↗
9. Sakr, S., and Zomaya, A.Y. (2019). Artifact-Centric Process Mining. Encyclopedia of Big Data Technologies, Springer.10.1007/978-3-319-77525-8 ↗
10. IEEE Standard for eXtensible Event Stream (XES) for Achieving Interoperability in Event Logs and Event Streams (2016). IEEE Std 1849–2016, The Institute of Electrical and Electronics Engineers.
11. Discovering Interacting Artifacts from ERP Systems10.1109/TSC.2015.2474358 ↗
12. Wieczorek, S., Stefanescu, A., and Schieferdecker, I.K. (2008, January 9–11). Test data provision for ERP systems. Proceedings of the 2008 1st International Conference on Software Testing, Verification, and Validation, Lillehammer, Norway.10.1109/ICST.2008.53 ↗
13. Connecting databases with process mining: A meta model and toolset10.1007/s10270-018-0664-7 ↗
14. Teniente, E., and Weidlich, M. (2018). From Relational Database to Event Log: Decisions with Quality Impact. Business Process Management Workshops (BPM 2017). Lecture Notes in Business Information Processing, Springer.10.1007/978-3-319-74030-0 ↗
15. Diba, K., Batoulis, K., Weidlich, M., and Weske, M. (2020). Extraction, correlation, and abstraction of event data for process mining. WIREs Data Min. Knowl. Discov., 10.10.1002/widm.1346 ↗
16. Automatic Discovery of Data-Centric and Artifact-Centric Processes10.1007/978-3-642-36285-9_36 ↗
17. Extracting Object-Centric Event Logs to Support Process Mining on Databases
18. Li, G., de Carvalho, R.M., and van der Aalst, W.M.P. (2019, January 8–12). Object-Centric Behavioral Constraint Models: A Hybrid Model for Behavioral and Data Perspectives. Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing (SAC ’19), Limassol, Cyprus.10.1145/3297280.3297287 ↗
19. Automatic Discovery of Object-Centric Behavioral Constraint Models
20. XES, XESame, and ProM 6
21. A Generic Import Framework For Process Event Logs
22. Preprocessing Support for Large Scale Process Mining of SAP Transactions10.1007/978-3-540-78238-4_5 ↗
23. Piessens, D. (2011). Event Log Extraction from SAP ECC 6.0. [Master’s Thesis, Eindhoven University of Technology].
24. Process Mining on Databases: Unearthing Historical Data from Redo Logs10.1007/978-3-319-23063-4_25 ↗
25. Artifact lifecycle discovery10.1142/S021884301550001X ↗
26. Magal, S.R., and Word, J. (2011). Integrated Business Processes with ERP Systems, Wiley Publishing. [1st ed.].
27. Reinhartz-Berger, I., Sturm, A., Clark, T., Cohen, S., and Bettin, J. (2013). Domain-Specific Modeling Languages: Requirements Analysis and Design Guidelines. Domain Engineering, Springer.10.1007/978-3-642-36654-3 ↗
28. Object Management Group (OMG) (2021, March 12). OMG Unified Modeling Language (UML), Available online: https://www.omg.org/spec/UML/About-UML/.
29. Object Management Group (OMG) (2021, June 05). Meta Object Facility (MOF) Core Specification, Available online: https://www.omg.org/spec/MOF/2.5.1/PDF.
30. Pajić Simović, A., Babarogić, S., and Pantelić, O. (2018, January 8–12). A Domain-Specific Language for Supporting Event Log Extraction from ERP systems. Proceedings of the 2018 7th International Conference on Computers Communications and Control (ICCCC), Oradea, Romania.10.1109/ICCCC.2018.8390430 ↗