Everything you always wanted to know about your process, but did not know how to ask

Abstract

The size of execution data available for process mining analysis grows several orders of magnitude every couple of years. Extracting and selecting the relevant data to be analyzed on each case represents an open challenge in the field. This paper presents a systematic literature review on different approaches to query process data and establish their provenance. In addition, a new query language is proposed, which overcomes the limitations identified during the review. The proposal is based on a combination of data and process perspectives. It provides simple constructs to intuitively formulate questions. An implementation of the language is provided, together with examples of queries to be applied on different aspects of the process analysis.