A framework for Multi-level Trace Abstraction and Semantic Process Mining

Many commercial information systems and enterprise resource planning tools routinely adopted by organizations and companies worldwide, like those provided by, e.g., Oracle and SAP, record information about the executed business process instances in the form of an event log. The event log stores the sequences (traces henceforth) of actions that have been executed at the organization, typically together with key execution parameters, such as times, costs and resources. Event logs constitute a very rich source of information for several business process management tasks. Indeed, the experiential knowledge embedded in traces is directly resorted to, e.g., in operational support and in agile workflow tools, which can take advantage of trace comparison and retrieval. Operational support assists users while process instances are being executed, by making predictions about the instance completion, or recommending suitable actions, resources or routing decisions, on the basis of the comparison to already completed instances retrieved from the log. The agile workflow technology deals with adaptation and overriding needs in response to expected situations (e.g., new laws, reengineering efforts) as well as to unanticipated exceptions and problems in the operating environment (e.g., emergencies), even if the default process schema is already in use by some running instances: in order to provide an effective and quick adaptation support, many agile workflow systems share the idea of recalling and reusing concrete examples of changes adopted in the past, recorded as traces in the event log. The CBR methodology, and in particular the retrieval step, can therefore be adopted in this context. In my PhD thesis, I am developing a framework to compare and retrieve process traces, represented at different levels of abstraction. The framework will then be interfaced to operational support or agile workflow tools, as well as to other analysis mechanisms. In this paper, I describe the methodological approach behind trace abstraction; the applications mentioned above will be considered in my future work.