Extraction of object-centric event logs through virtual knowledge graphsShow others and affiliations
2022 (English)In: Proceedings of the 35th International Workshop on Description Logics (DL 2022) / [ed] Ofer Arieli; Martin Homola; Jean Christoph Jung; Marie-Laure Mugnier, 2022, article id 15Conference paper, Published paper (Refereed)
Abstract [en]
Process mining is a family of techniques that supports the analysis of operational processes based on event logs. Among the existing event log formats, the IEEE standard eXtensible Event Stream (XES) is the most widely adopted. In XES, each event must be related to a single case object, which may lead to convergence and divergence problems. To solve such issues, object-centric approaches become promising, where objects are the central notion, and one event may refer to multiple objects. In particular, the Object-Centric Event Logs (OCEL) standard has been proposed recently. However, the crucial problem of extracting OCEL logs from external sources is still largely unexplored. In this paper, we try to fill this gap by leveraging the Virtual Knowledge Graph (VKG) approach to access data in relational databases. We have implemented this approach in the OnProm system, extending it from XES to OCEL support. The full version of this article has been submitted to an international conference.
Place, publisher, year, edition, pages
2022. article id 15
Series
CEUR Workshop proceedings, ISSN 1613-0073
Keywords [en]
object-centric event logs, ontology-based data access, Process mining, virtual knowledge graph
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-201425Scopus ID: 2-s2.0-85142457915OAI: oai:DiVA.org:umu-201425DiVA, id: diva2:1715079
Conference
35th International Workshop on Description Logics, DL 2022, Haifa, Israel, August 7-10, 2022
2022-12-012022-12-012022-12-01Bibliographically approved