Swevels, A., Fahland, D., & Montali, M. (2024). Implementing Object-Centric Event Data Models in Event Knowledge Graphs. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 431-443). (Lecture Notes in Business Information Processing; Vol. 503 LNBIP). https://doi.org/10.1007/978-3-031-56107-8_33
Abstract
Recent advances in object-centric process mining necessitated the standardization of object-centric event data (OCED). An IEEE taskforce has developed a “meta-model” for OCED, but there is no existing reference implementation or automated techniques to transform legacy data into OCED. This task requires domain-specific knowledge about the semantics of the legacy data in order to make explicit how events act on various inter-related data objects and their attributes. We propose a semantic header that defines how extracted legacy data maps to OCED concepts and the domain-specific reference ontology using PG-schema. We automatically translate the header into database queries to construct an event knowledge graph that is compliant with OCED and the domain ontology using a declarative extract-load-transform approach. The approach has been implemented and demonstrated on 7 real-life datasets, making it one of the first attempts to make OCED operational.