In the past decade, Process Mining has not only seen tremendous growth in the academic arena, but also started to establish itself as one of the predominant approaches to improving processes for larger companies of virtually any industry. Process Mining and related services have become a sizeable business - for software vendors, professional service firms, and commercial end user alike.

Such a trajectory naturally spurs substantial investment and advancement; however, it is also typical that – in an attempt to safeguard intellectual property – many new features, products and services
are being shielded off from usage by other players in the ecosystem. Especially when this affects areas that are of concern to all market participants, such silos impede competition, innovation and the pace of further development. In many industries that are heavily reliant on the exchange of something, standardizing terms and conditions of such exchange led to a great leap forward for the entire ecosystem – think containers for global trade, internet protocol for global communication.

Process Mining itself is heavily reliant on the exchange of data, which typically originates from systems that were not designed around this use case and hence requires substantial transformation. Market participants have created different approaches to reduce the effort required for data transformation, but so far no data exchange format has seen enough adoption to be nominated as a de-facto standard. The relevance and magnitude of this bottleneck as one of the predominant effort drivers in process mining projects has been reconfirmed by the Task Force on Process Mining (TFPM).

With the IEEE eXtensible Event Stream (XES) initiated in 2010, academia has established a data exchange format, which fueled tremendous growth in process mining research. Standardizing how academia captures, transfers, loads and interprets event data continues to pay dividends.

However, process mining adoption by business entities and the academic progress in the past decade changed the requirements towards an up-to-date standard substantially. The IEEE TFPM initiated a community process to co-design the XES successor Object-Centric Event Data (OCED):

• creating more competition and innovation by lowering the market entry barrier
• allowing commercial end users and professional service providers to focus their effort on process improvement and other value creating tasks rather than data transformation
• allowing software vendors to focus on value-adding differentiators, rather than creating the n^th data transformation engine and corresponding development environment
• improving security of investment for commercial end users
• creating a market for source system specific adapter modules translating data into OCED

Since 2021, the OCED Working Group is organizing various activities to gather requirements and feedback from the process mining community. These resulted in the white paper “Towards a Simple and Extensible Standard for OCED” published in 2024. 

As of 2025, the OCED Working Group is defining and pursuing a structured process to develop the official OCED standard together with the community. For details and ongoing activities, see OCED Standardization Activities (create link to new page).

Intermediate Results and Documents

• Towards a Simple and Extensible Standard for OCED (http://arxiv.org/abs/2410.14495)
  • Summarizing result of “Call for Action: Reference Implementations”
  • Proposing OCED Core model as common core of various proposals for OCED
  • Proposing core interpretation of OCED Core model
  • Analysis and discussion of gaps between OCED Core model, various use cases, and other proposed models
  • Description, Links, and lessons learned from 5 reference implementations of OCED models
  • Outline for future research and open tasks for standardization
• “Rethinking the Input for Process Mining: Insights from the XES Survey and Workshop”, (https://link.springer.com/chapter/10.1007/978-3-030-98581-3_1)
  • Result of XES 2.0 Workshop at ICPM 2021
  • Core challenges for data exchange and preparation are: handling complex and undocumented source data structures specifically one-to-many and many-to-many relations, and handling inconsistent and incomplete data
  • Expectations of a new standard are: accelerate preparation and pre-processing of data through easy availability and access, easy visualization, and lower costs of data exchange
  • New standard should be: able to capture complex data structures (many-to-many relations between objects and events), acts as semantic layer by allowing to express domain-specific concepts, and find the right balance between true interoperability, vendor-specific added value, expressive power, and simplicity