Ontology-driven extraction of event logs from relational databases

Diego Calvanese, Marco Montali, Alifah Syamsiyah, Wil M P van der Aalst

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

60 Citations (Scopus)
2 Downloads (Pure)


Process mining is an emerging discipline whose aim is to discover, monitor and improve real processes by extracting knowledge from event logs representing actual process executions in a given organizational setting. In this light, it can be applied only if faithful event logs, adhering to accepted standards (such as XES), are available. In many real-world settings, though, such event logs are not explicitly given, but are instead implicitly represented inside legacy information systems of organizations, which are typically managed through relational technology. In this work, we devise a novel framework that supports domain experts in the extraction of XES event log information from legacy relational databases, and consequently enables the application of standard process mining tools on such data. Differently from previous work, the extraction is driven by a conceptual representation of the domain of interest in terms of an ontology. On the one hand, this ontology is linked to the underlying legacy data leveraging the well-established ontology-based data access (OBDA) paradigm. On the other hand, our framework allows one to enrich the ontology through user-oriented log extraction annotations, which can be flexibly used to provide different log-oriented views over the data. Different data access modes are then devised so as to view the legacy data through the lens of XES.

Original languageEnglish
Title of host publicationBusiness Process Management Workshops : BPM 2015, 13th International Workshops, Innsbruck, Austria, August 31 - September 3, 2015 : Revised Papers
EditorsM. Reichert, H.A. Reijers
Number of pages14
ISBN (Electronic)978-3-319-42887-1
ISBN (Print)9783319428864
Publication statusPublished - 2015
Event11th International Workshop on Business Process Intelligence (BPI 2015) - Innsbruck, Austria
Duration: 31 Aug 201531 Aug 2015
Conference number: 11

Publication series

NameLecture Notes in Business Information Processing
ISSN (Print)18651348


Workshop11th International Workshop on Business Process Intelligence (BPI 2015)
Abbreviated titleBPI 2015
Internet address


  • Event data
  • Log extraction
  • Multi-perspective process mining
  • Ontology-based data access


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