Process-aware Event Log Datacubes for Workflow Process and Knowledge Mining, Predicting and Analyzing Frameworks

Abstract

The issue of workflow process mining and analytics is beginning to make its appearance in the workflow-supported enterprise intelligence and systems literature. In order to improve the quality of workflow process intelligence, it is essential for an efficient and effective data center storing workflow enactment event logs to be provisioned in carrying out the workflow process mining and analytics. In this paper, we propose a three-dimensional datacube, which is named as a process-aware dat-acube, for organizing workflow-supported enterprise data centers to efficiently as well as effectively store the workflow process enactment event logs in the IEEE XES format, and also we carry out an experimental process mining and analytics to show how much perfectly the process-aware datacubes are suitable for discovering workflow process patterns and its analytical knowledge, like enacted proportions and enacted work transferences, from the workflow process enactment event histories. From the process-aware datacubes, the workflow process mining must be able to properly discover all the workflow process patterns based upon the four types of control-flow primitives such as linear (sequential) routing, disjunctive (selective) routing, conjunctive (parallel) routing, and iterative (loop) routing patterns, whereas the workflow process analytics is to discover the enacted pro-protions of each of the process pattherns and the enacted work transferences of each of the workflow performers.