Enhancing workflow-nets with data for trace completion

TL;DR

This paper proposes a novel approach to automatically repair incomplete process traces by considering both activities and data, using planning techniques to improve process analysis in real-world scenarios.

Contribution

It introduces a method that encodes trace repair as a reachability problem, enabling the use of planning algorithms to handle incomplete logs with data considerations.

Findings

Effective repair of incomplete traces demonstrated

Supports complex process analysis with data considerations

Utilizes existing planning tools for trace completion

Abstract

The growing adoption of IT-systems for modeling and executing (business) processes or services has thrust the scientific investigation towards techniques and tools which support more complex forms of process analysis. Many of them, such as conformance checking, process alignment, mining and enhancement, rely on complete observation of past (tracked and logged) executions. In many real cases, however, the lack of human or IT-support on all the steps of process execution, as well as information hiding and abstraction of model and data, result in incomplete log information of both data and activities. This paper tackles the issue of automatically repairing traces with missing information by notably considering not only activities but also data manipulated by them. Our technique recasts such a problem in a reachability problem and provides an encoding in an action language which allows to virtually use any state-of-the-art planning to return solutions.