# Towards a Domain-Specific Modeling Language for Extracting Event Logs from ERP Systems
## 5 Results
### Step 3--Mapping DSML Model to XES Format
## 7 Conclusions

In this paper, we have proposed a graphical DSML that provides support to domain experts in obtaining event logs from ERP databases. A new metamodel version with corresponding constraints has been introduced, as well as a graphical representation of the language concepts. Specifically, domain experts will be able to indicate where cases and events are located within a database at a conceptual level. Afterward, these conceptual models will be automatically validated and transformed into SQL code. When the query results are obtained, the extracted data can be mapped to XES elements. We have briefly described each component and demonstrated the applicability of the approach using a case study with real data from a Microsoft Dynamics NAV ERP database. Although the demonstration shows its usefulness, more empirical experiments are still needed. As part of our work-in-progress, we are developing a specialized CASE tool that will include a set of applications to support the implementation of each component. Besides, the proposed language makes the querying of process data easier and domain experts can focus on modeling data of interest conceptually without the need to learn a programming language. As future work, a further formal definition of mechanisms for mapping ERP transactional data to the XES event log will be provided according to the data extraction model and transformation rules. Conceptualization, A.P.S., S.B. and O.P. ; methodology, A.P.S. and S.B. ; software, A.P.S. and S.K. ; validation, S.B. and O.P. ; investigation, A.P.S., S.B. and O.P. ; writing--original draft preparation, A.P.S. and S.K. ; writing--review and editing, S.B. and O.P. ; visualization, A.P.S. and S.K. ; supervision, S.B. and O.P. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The data presented in this study are available on request from the corresponding author. The data are not publicly available because they contain confidential business information. The authors declare no conflict of interest. ## References

* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Mining shift work operation from event logs. _Appl. Sci._**2020**, _10_, 7202. [CrossRef]
* [PERSON] and [PERSON]. (2016) [PERSON]. _Process Mining: Data Science in Action_, 2 nd ed. ; Springer: Berlin/Heidelberg, Germany, 2016. * _[PERSON]_ (2019)_ _[PERSON] [PERSON]. Object-Centric Process Mining: Dealing with Divergence and Convergence in Event Data. In_ Software Engineering and Formal Methods (SEFM 2019). Lecture Notes in Computer Science_; [PERSON], [PERSON], [PERSON]; Springer: Cham, Switzerland, 2019; Volume 11724, pp. 3-25. [CrossRef]
* _[PERSON]_ (2015)_ _[PERSON] [PERSON]. Extracting Event Data from Databases to Unleash Process Mining. In_ BPM--Driving Innovation in a Digital World. Management for Professionals; [PERSON] [PERSON], [PERSON], [PERSON]; Springer: Cham, Switzerland, 2015; pp. 105-128. [CrossRef]
* _[PERSON]_ (2017)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON] OBDA for log extraction in process mining. In_ Reasoning Web. Semantic Interoperability on the Web. Reasoning Web 2017. Lecture Notes in Computer Science_; [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON]; Springer: Cham, Switzerland, 2017; Volume 10370, pp. 292-345. [CrossRef]
* _[PERSON]_ (2020)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Event Log Extraction for the Purpose of Process Mining: A Systematic Literature Review. In_ Innovation in Sustainable Management and Entrepreneurship (SIM 2019). Springer Proceedings in Business and Economics_; [PERSON], [PERSON], [PERSON], [PERSON], [PERSON]; Springer: Cham, Switzerland, 2020; pp. 299-312. [CrossRef]
* _[PERSON]_ (2019)_ _[PERSON]; [PERSON]; [PERSON] Building a valuable event log for process mining: An experimental exploration of a guided process._ Enterp. Inf. Syst._ **2019**, _13_, 601-630.