# Towards a Domain-Specific Modeling Language for Extracting Event Logs from ERP Systems
## 1 Introduction
This shows that the need to support domain experts during the log building process is a real issue, but there is an absence of techniques and tools to facilitate this [9; 15]. To support domain experts, to automate log building process as much as possible, and to mitigate the problems caused by many-to-many relations, a graphical domain-specific modeling language (DSML) for extracting event data from transactional databases has been developed. It has been specifically designed to describe behaviors for complex data in ERP systems in terms of multiple interacting artifacts. To this end, we have followed artifact-centric approaches [11; 16] which consider artifacts, i.e., the documents of ERP systems, as case identifiers. These approaches can deal with one-to-many and many-to-many relations between data. A few researchers have also attempted to address the problems caused by many-to-many relations and have proposed novel metamodels for storing data for process mining [13; 17] and novel modeling notations and process mining techniques for discovering and analyzing artifact-centric processes [18; 19] to achieve this; however, our proposed metamodel is aimed at providing the basis for a data extraction model to create event logs in the XES format from transaction logs. Once event logs are obtained, i.e., XES files, it is possible to perform existing process mining techniques which users are already familiar with. The language supports domain experts to determine the process scope, select correct database tables, and include relevant events for conversion definition in an intuitive way. The metamodel proposed in this paper, along with its corresponding constraints, is the result of several iterations of development and revision. We also introduce a graphical notation for the language concepts. Once the DSML model was designed, the next step of our approach was to transform the model into Structured Query Language (SQL) code. Then, automatic translation from the query results to the final XES event log could be performed. The main contribution of our research is the full specification of the aforementioned language. The benefit of designing a specific language is that it allows domain experts, even without any programming background, to focus on modeling the data of interest in the log extraction step. Another important contribution is a conceptual representation of ERP database content in terms of business artifacts. The new metamodel aligns behavioral and data perspectives in order to provide sufficient information about a process, data objects, and the relations between them. Based on this model information and the specified transformation rules, it will be possible to extract and transform data from transactional ERP databases to the XES target representation, as demonstrated in this paper. The remainder of the paper is organized as follows. The next section discusses related works. Section 3 describes complex ambiguous cases from ERP systems. The specification of the language, its metamodel, and the corresponding constraints are discussed in Section 4. Besides, a graphical notation is presented. Then, our solution is evaluated using a case study with real data in Section 5. A discussion is presented in Sections 6 and 7 provides final conclusions and ideas for future work.