The application of process mining techniques to real-life information systems is often challenging. Considering a Purchase to Pay (P2P) process, several case notions such as order and item are involved, interacting with each other. Therefore, creating an event log where events need to relate to a single case (i.e., process instance) leads to convergence (i.e., the duplication of an event related to different cases) and divergence (i.e., the inability to separate events within the same case) problems. To avoid such problems, object-centric event logs have been proposed, where each event can be related to different objects. These can be exploited by a new set of process mining techniques. This paper describes OCEL (Object-Centric Event Log), a generic and scalable format for the storage of object-centric event logs. The implementation of the format can use either JSON or XML, and tool support is provided.
Companies that want to analyze processes such as purchase-to-pay or order-to-cash from their ERP systems find that each event involves several interacting business objects, such as orders, items, packages and customers, rather than one case. Forcing such data into the standard single-case event log format (XES) duplicates events across cases (convergence) or blurs the order of events inside a case (divergence), distorting discovered models and performance figures. Earlier object-centric formats such as XOC replicate object attributes in every event and scale poorly with the number of events and objects, while tabular files lose typing. Analysts and tool builders need a common, compact, strongly typed exchange format for event data with multiple object types.
ProM OCELStandard package) for import, export, schema validation and flattening to traditional event logs.