Object-centric process mining

Practical problem

Classical process mining assumes that every event belongs to exactly one case. Processes run on ERP systems, manufacturing lines and hospital information systems break this assumption: an order has many items, deliveries and invoices, a technician’s day spans many service schedules, and a single event often concerns several of these objects at once. Forcing such data into one case notion creates convergence and divergence errors and hides exactly the interactions where delays, overstock and compliance problems arise. Object-centric event data removes this blind spot, but it needs its own standard, extraction methods, analysis techniques and tools. Since 2020, I have built this chain from the raw tables of SAP ERP to object-centric event logs, analysis techniques and open-source software.

Research questions

The line has three pillars.

Standards and extraction. Object-centric event data has to be stored, exchanged and obtained before it can be analysed.

  • How should event data in which one event touches several objects of different types be represented and exchanged without losing the object relationships, and how can it be stored and queried at the scale of millions of events?
  • How can object-centric event logs be extracted from the thousands of tables of an ERP system such as SAP, or from a clinical data model such as OMOP, with as little domain knowledge as possible, and how does an analyst find out which processes a database supports at all?

Analysis techniques. The notions that process mining relies on change when cases overlap.

  • Which definitions of performance, variant, conformance and constraint violation make sense for interacting objects, and how are they computed by replaying an object-centric Petri net or an object-centric directly-follows graph?
  • How can object-centric event data feed machine learning while keeping the graph structure of a process execution, instead of flattening it into a table or a sequence?

Practice. Object-centric analysis has to pay off in real projects.

  • How does a process mining project methodology such as PM² change for object-centric projects, and what do real purchase-to-pay, after-sales and healthcare processes reveal when analysed this way?

Contributions

The contributions so far fall into five groups, each linked to the publication in which it appears.

The OCEL standard and its storage.

  • The OCEL standard for object-centric event logs: a meta-model in which each event references a set of objects of different types and object attributes are stored once, with JSON and XML serializations, validation schemas and Python and Java tool support (ADBIS Workshops 2021).
  • A MongoDB schema and indexing scheme for OCEL with database-level aggregations for object lifecycles, statistics and object-centric directly-follows graphs, assessed on synthetic logs of 1 to 100 million events (ICPM Demo 2021).

Extraction from SAP ERP and clinical databases.

  • A technology-independent approach for extracting object-centric event data from databases: a graph of relationships derived from the data dictionary, blueprints that map table entries to events, a formal conversion to OCEL and the open-source Interactive SAP Explorer with two published order-to-cash and purchase-to-pay logs (Journal of Intelligent Information Systems, 2023); first presented as an extraction approach (ICPM Workshops 2021) and as an interactive process identification demo (ICPM Demo 2022).
  • OMOP CDM4PM, a formally defined subset of the OMOP common data model, and a transformation into OCEL whose event and object types are derived from the OMOP concept table and the SNOMED CT hierarchy, implemented in omop2ocel and evaluated on three MIMIC-IV sub-datasets (Journal of Biomedical Informatics, 2024).

Performance, constraints and conformance on object-centric data.

  • OPerA: replay of a discovered object-centric Petri net to compute flow, sojourn, waiting and service time per event occurrence, plus the object-centric synchronization, pooling and lagging time (ER 2022).
  • Object-centric constraint graphs and behavioral metrics for monitoring control-flow, object involvement and performance constraints, with the ProPPa web application (ICPM Workshops 2022, Best Paper Award), and constraint checking for object-centric process executions (ICPM Workshops 2023).
  • A taxonomy of object-centric operational problems, Operational Problem Graphs with formal occurrence semantics and a monitoring function, and the ProAct monitoring engine (Computers in Industry, 2025).
  • Conformance checking and performance analysis on object-centric directly-follows graphs, which project per object type, align the projected log and map log and model moves back onto the graph, in the Explori tool (BPM Forum 2024).
  • Super variants, which summarize object-centric variants with choice, optionality and object multiplicity through a hitting-set selection and a matching-based merging hierarchy (BPM 2024).
  • GOProQ, a graphical query language with formal syntax and semantics over object-centric process executions and a query-reordering evaluation strategy, evaluated on six public OCELs (ICSOC 2025).

Object-centric data for machine learning.

  • A framework that translates control-flow, data, resource and performance features to object-centric event logs, adds an object perspective, and defines tabular, sequential and graph encodings of process executions (ICSOC 2022).
  • An approach that keeps process executions as event graphs throughout the machine-learning pipeline, as graph neural network input or as graph embeddings, with an evaluation protocol that isolates the value of structure alone (Engineering Applications of Artificial Intelligence, 2023), and object-centric process mining to improve predictive process monitoring (ECIS 2024).

Tools and case studies.

  • ocpa, the open-source Python library for object-centric process analysis: OCEL import and export, process executions and variants, object-centric Petri net discovery, precision and fitness, constraint monitoring, performance analysis and feature extraction (Software Impacts, 2022).
  • An extension of the PM² project methodology to five stages for object-centric projects, applied to the after-sales service process of Borusan Cat (ICPM Workshops 2023) and to a real-life purchase-to-pay process (International Journal of Data Science and Analytics, 2025).
  • Overstock in the purchase-to-pay process of Europe’s largest pet retailer: a conceptual model with five object types, extraction from Celonis into OCEL, two discovered object-centric Petri nets and two improvement measures agreed with logistics management (CAiSE Workshops 2024).