# Towards a Domain-Specific Modeling Language for Extracting Event Logs from ERP Systems
## 2 Related Work  
Various techniques and tools in the literature have tried to deal with the extraction of event logs from enterprise systems. Tools such as XESame [20] and ProMimport [21] can be used to extract XES event logs from various data sources that hold explicit information about process instances and events. The XES log format has been accepted by the IEEE Task Force on Process Mining as a de facto standard for process mining algorithms. This format represents a structure of an event log, containing traces and events with the corresponding attributes. It comes with standardized extensions for capturing semantics to particular attributes per component. Briefly, a trace describes an order in which events occur during one execution of a process. Note that traces in the XES log describe the evolution of the main case object, i.e., one type of process instance. Moreover, each event refers to some activity. We refer to the official IEEE XES standard [10] for more information about XES metamodel and the OpenXES reference implementation. Since ERP systems provide several identifiers for a process instance, the XES log format cannot be extracted directly. So far, most studies in this regard have dealt with extracting data from specific environments like SAP systems and have not provided a general approach for building event logs from databases. [PERSON] and [PERSON] [22] developed a tool to specifically construct process chains from SAP transactions while allowing users to define events. [PERSON] [23], in turn, initialized a repository with predefined event types for specific processes supported by SAP. A more generic solution is the on-prom project presented by [PERSON] et al. [5], who introduced two ontologies, namely, a domain ontology and an event ontology, to support the extraction of event logs from legacy data. Specifically, the approach provides an annotation mechanism to help users in the conceptual identification of event data. This approach addresses the data from a semantic perspective but does not deal with one-to-many and many-to-many relations, as encountered in this work. Another effort to obtain event logs considered the redo log files of relational databases as a source of event data [4; 24]. Redo logs are used to record information about any modification performed on the data of the database; however, more files need to be explicitly configured to store redo logs. In many real cases, redo logs might not be available. The OpenSlex metamodel [13] has been proposed to store object-centric event logs, covering different types of entities such as objects, object versions, relations, and events. Multiple XES event logs can then be created from this intermediary storage based on the chosen case notion. Unlike OpenSlex, our solution provides the basis for a data extraction model and does not require the manual specification of database queries. It abstracts users from the definition of complex transformations required to obtain an XES event log. Once a conceptual model has been designed by domain experts, it provides sufficient information to automate the generation of queries and translate the obtained query results to the final XES event log. A more recent work [19] has proposed a new process mining technique to discover an object-centric behavioral constraint (OCBC) model from an eXtensible object-centric (XOC) log. This technique is based on a novel log format and a new type of model which is used to describe processes involving complex data dependencies. The XOC format does not assume a unique case notion to group events, thus, it can be extracted from object-centric data [17]. The new log format combines different types of entities, such as objects, events, and attributes, as presented in [13].