Abstract
Object-centric process mining (OCPM) addresses the limitations of case-centric process mining by allowing events to relate to multiple objects of different types and by capturing object-to-object relationships. However, the practical adoption of OCPM is still hindered by three challenges: (1) conceptualizing object-centric event data (OCED) in a standardized way that is semantically precise and interoperable across tools, (2) investigating how OCED can be extracted from legacy information systems according to this model, including the assumptions and trade-offs involved, and (3) identifying the requirements and principles for querying OCED in a way that respects its unflattened structure. This PhD research tackles these challenges by developing an ontology-based conceptual model for object-centric event data grounded in unified foundational ontologies, investigating how ontology-based data access can support the extraction of OCED from existing information systems, and defining the semantic requirements and design principles for querying OCED. Preliminary results include an initial UFO-based metamodel that addresses limitations of current object-centric event data representations, including the current OCED Core Model, capturing object relationships, event-to-event relations, and the temporal evolution of object attributes and relations.