# Discovering Object-Centric Petri Nets

arXiv: https://arxiv.org/abs/2010.02047 · HTML: https://mlsanity.com/paper/2010.02047/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Oct 2020.

## Built on by (most cited first, 28 of 28)

- [Precision and Fitness in Object-Centric Process Mining](https://mlsanity.com/paper/2110.05375/) (2021)
- [Defining Cases and Variants for Object-Centric Event Data](https://mlsanity.com/paper/2208.03235/) (2022)
- [Object-centric Process Predictive Analytics](https://mlsanity.com/paper/2203.02801/) (2022)
- [Process Comparison Using Object-Centric Process Cubes](https://mlsanity.com/paper/2103.07184/) (2021)
- [TraceCompiler: Skill-Guided Mining and Compilation of LLM Agent Traces into Mostly Deterministic Workflows](https://mlsanity.com/paper/2608.02680/) (2026)
- [OPerA: Object-Centric Performance Analysis](https://mlsanity.com/paper/2204.10662/) (2022)
- [AI-Enhanced Business Process Automation: A Case Study in the Insurance Domain Using Object-Centric Process Mining](https://mlsanity.com/paper/2504.17295/) (2025)
- [Object Type Clustering using Markov Directly-Follow Multigraph in Object-Centric Process Mining](https://mlsanity.com/paper/2206.11017/) (2022)
- [Predictive Object-Centric Process Monitoring](https://mlsanity.com/paper/2207.10017/) (2022)
- [A Framework for Extracting and Encoding Features from Object-Centric Event Data](https://mlsanity.com/paper/2209.01219/) (2022)
- [Monitoring Constraints in Business Processes Using Object-Centric Constraint Graphs](https://mlsanity.com/paper/2210.12080/) (2022)
- [HOEG: A New Approach for Object-Centric Predictive Process Monitoring](https://mlsanity.com/paper/2404.05316/) (2024)
- [Inferring Unobserved Events in Systems With Shared Resources and Queues](https://mlsanity.com/paper/2103.00167/) (2021)
- [Removing Operational Friction Using Process Mining: Challenges Provided by the Internet of Production (IoP)](https://mlsanity.com/paper/2107.13066/) (2021)
- [Soundness in Object-centric Workflow Petri Nets](https://mlsanity.com/paper/2112.14994/) (2021)
- [Preventing Object-centric Discovery of Unsound Process Models for Object Interactions with Loops in Collaborative Systems: Extended Version](https://mlsanity.com/paper/2303.16680/) (2023)
- [Analyzing An After-Sales Service Process Using Object-Centric Process Mining: A Case Study](https://mlsanity.com/paper/2310.10174/) (2023)
- [Extracting Process-Aware Decision Models from Object-Centric Process Data](https://mlsanity.com/paper/2401.14847/) (2024)
- [Predictive Process Monitoring Using Object-centric Graph Embeddings](https://mlsanity.com/paper/2507.15411/) (2025)
- [Analyzing Process-Aware Information System Updates Using Digital Twins of Organizations](https://mlsanity.com/paper/2203.12969/) (2022)
- [Object-Centric Conformance Alignments with Synchronization (Extended Version)](https://mlsanity.com/paper/2312.08537/) (2023)
- [INEXA: Interactive and Explainable Process Model Abstraction Through Object-Centric Process Mining](https://mlsanity.com/paper/2403.18659/) (2024)
- [No AI Without PI! Object-Centric Process Mining as the Enabler for Generative, Predictive, and Prescriptive Artificial Intelligence](https://mlsanity.com/paper/2508.00116/) (2025)
- [Discovery of Decision Synchronization Patterns from Event Logs](https://mlsanity.com/paper/2603.19879/) (2026)
- [On the Hybrid Nature of ABPMS Process Frames and its Implications on Automated Process Discovery](https://mlsanity.com/paper/2604.22455/) (2026)
- [TGCM: Topic-Guided Consistency Modeling for One-Step Disentanglement of Interleaved APT Technique Sequences](https://mlsanity.com/paper/2606.18651/) (2026)
- [From Event Logs to Governed Action: A BlueSky Agenda for Agentic Process Mining](https://mlsanity.com/paper/2609.07984/) (2026)
- [Resolution limits for process comparison from event data](https://mlsanity.com/paper/2609.20489/) (2026)

## Abstract (arXiv)

Techniques to discover Petri nets from event data assume precisely one case identifier per event. These case identifiers are used to correlate events, and the resulting discovered Petri net aims to describe the life-cycle of individual cases. In reality, there is not one possible case notion, but multiple intertwined case notions. For example, events may refer to mixtures of orders, items, packages, customers, and products. A package may refer to multiple items, multiple products, one order, and one customer. Therefore, we need to assume that each event refers to a collection of objects, each having a type (instead of a single case identifier). Such object-centric event logs are closer to data in real-life information systems. From an object-centric event log, we want to discover an object-centric Petri net with places that correspond to object types and transitions that may consume and produce collections of objects of different types. Object-centric Petri nets visualize the complex relationships among objects from different types. This paper discusses a novel process discovery approach implemented in PM4Py. As will be demonstrated, it is indeed feasible to discover holistic process models that can be used to drill-down into specific viewpoints if needed.