What Can Database Query Processing Do for Instance-Spanning Constraints?

TL;DR

This paper introduces a novel approach to monitoring instance-spanning constraints in process mining by leveraging database query processing techniques, enabling efficient compliance checking at runtime.

Contribution

It proposes defining constraints through database queries and applying incremental view maintenance for compliance monitoring, filling a gap in database-oriented process mining methods.

Findings

Effective use of database queries for constraint monitoring

Demonstrated feasibility with DBToaster engine

Potential for real-time compliance checking

Abstract

In the last decade, the term instance-spanning constraint has been introduced in the process mining field to refer to constraints that span multiple process instances of one or several processes. Of particular relevance, in this setting, is checking whether process executions comply with constraints of interest, which at runtime calls for suitable monitoring techniques. Even though event data are often stored in some sort of database, there is a lack of database-oriented approaches to tackle compliance checking and monitoring of (instance-spanning) constraints. In this paper, we fill this gap by showing how well-established technology from database query processing can be effectively used for this purpose. We propose to define an instance-spanning constraint through an ensemble of four database queries that retrieve the satisfying, violating, pending-satisfying, and pending-violating cases of the constraint. In this context, the problem of compliance monitoring then becomes an application of techniques for incremental view maintenance, which is well-developed in database query processing. In this paper, we argue for our approach in detail, and, as a proof of concept, present an experimental validation using the DBToaster incremental database query engine.