Finding Non-compliances with Declarative Process Constraints Through Semantic Technologies

Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 350)


Business process compliance checking enables organisations to assess whether their processes fulfil a given set of constraints, such as regulations, laws, or guidelines. Whilst many process analysts still rely on ad-hoc, often handcrafted per-case checks, a variety of constraint languages and approaches have been developed in recent years to provide automated compliance checking. A salient example is Declare, a well-established declarative process specification language based on temporal logics. Declare specifies the behaviour of processes through temporal rules that constrain the execution of tasks. So far, however, automated compliance checking approaches typically report compliance only at the aggregate level, using binary evaluations of constraints on execution traces. Consequently, their results lack granular information on violations and their context, which hampers auditability of process data for analytic and forensic purposes. To address this challenge, we propose a novel approach that leverages semantic technologies for compliance checking. Our approach proceeds in two stages. First, we translate Declare templates into statements in SHACL, a graph-based constraint language. Then, we evaluate the resulting constraints on the graph-based, semantic representation of process execution logs. We demonstrate the feasibility of our approach by testing its implementation on real-world event logs. Finally, we discuss its implications and future research directions.


Process mining Compliance checking SHACL RDF SPARQL 



This work was partially funded by the Austrian FFG grant 861213 (CitySPIN), the Austrian FWF/netidee SCIENCE grant P30437-N31 (SEPSES), the EU H2020 programme under MSCA-RISE agreement 645751 (RISE_BPM), the Christian Doppler Research Association, the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.TU WienViennaAustria
  2. 2.WU ViennaViennaAustria

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