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

This paper has attempted to address the issue of extracting suitable event logs from data stored in relational databases, supporting domain knowledge. We have particularly focused on the business processes supported by ERP systems, which are generally seen as a collection of interrelated documents. In fact, a single process instance may involve several documents, each with its own life cycle. Hence it is very difficult to describe the evolution of various documents using a single process definition. This has led to artifact-centric approaches which can deal with one-to-many and many-to-many relations, avoiding convergence and divergence problems. These approaches have proven more appropriate for complex business processes supported by an ERP system [9]. To deal with one-to-many and many-to-many relations, the metamodel proposed in this paper provides an artifact-centric view of databases. The DSML metamodel was initially described in our previous work [30]; however, this metamodel was revised and we acknowledged some limitations compared to the new metamodel proposed in this paper. Firstly, the metamodel was incomplete in terms of its semantics and also inconsistent that made it more difficult to understand by the end-user. The artifact type log element was not considered, thus lacking properties which provide valuable information, such as the timestamp from which to begin querying for event data. Also, the attributes of metaclasses and the number of metamodel restrictions were not described. Secondly, the different levels of abstraction were within the model which compromised an appropriate interpretation of the model. For example, the trace and link elements at type level (M1) were included. Afterward, a full specification of the language was provided in this paper. This DSML is composed of the revised metamodel with its attributes and new constraints and a graphical representation of the metamodel concepts. In addition, we have determined how certain metaclasses of language could be transformed into SQL code. This is an automatic process that does not require any further user interaction. The case study demonstrates that it is possible to apply the developed solution to a real example. The results show that the language includes constructs that enable a domain expert to easily model data of interest in a log extraction step. Once a conceptual model has been designed, this provides sufficient information to automate the generation of queries. We have successfully described the preferred artifacts and the relations between them. We argue that our solution works in real settings because it facilitates mapping from

Figure 7: Discovered process model from the generated XES document. the conceptual model and queries variables to the target XES representation. The output consists of an event log in the XES format for each main artifact. This results in avoiding the data convergence and data divergence problems, since multiple event logs are obtained with stored relations among artifacts. For this purpose, we use the list attribute in the XES standard. We have demonstrated that the generated XES document is valid by discovering a business process model. The resulting process model is in line with the business logic presented in the case study. Furthermore, an artifact-centric process model can be discovered from these multiple event logs using existing process discovery techniques. A discussion on that topic extends beyond the scope of this paper. We refer the readers to [11; 25] for more information about process discovery techniques that can be used to discover artifact life cycle models and artifact interactions. Furthermore, the authors are aware that the main limitation of the presented solution is the lack of tool support in particular phases. In view of the positive results of the study, active work is being carried out to develop a more natural and sophisticated tool to provide better guidance to users.