Event abstraction is a technique to reduce complexity by aggregating or summarizing lower-level events into higher-level, more meaningful concepts. This technique is especially useful in the context of process mining, where event logs can be voluminous and difficult to interpret. By abstracting events, analysts can create more readable and manageable process models. Here are some steps and strategies to effectively utilize event abstraction in complex process modeling:

1. Identify Common Patterns: Analyze the event logs to identify frequent sequences or patterns of low-level events that can be abstracted into a single high-level activity. For instance, a sequence of "login -> select item -> add to cart -> checkout" events could be abstracted to a higher-level "make purchase" event.

2. Define Abstraction Criteria: Establish rules or criteria for when and how to abstract events. These criteria could be based on the frequency of occurrence, the sequence of events, the roles of participants involved, or other relevant factors.

3. Categorize Events: Group events into categories based on their attributes or context. For example, events could be categorized by department, by system component, or by type of activity (e.g., data entry, approval, transaction processing).

4. Use Hierarchical Modeling: Create a hierarchical process model where high-level abstracted events can be drilled down into to reveal the underlying detailed events. This allows for a multi-level view of the process, accommodating both high-level oversight and detailed analysis.

5. Apply Semantic Aggregation: Instead of just clustering events based on sequences, focus on the semantics behind the actions to create meaningful aggregations. For instance, multiple events indicating different forms of approval could be abstracted to a single "approval" event.

6. Simplified Process Maps: Redraw the process maps using abstracted events to represent complex paths. This will help stakeholders to understand the overall process flow without getting lost in the details.

7. Validate Abstractions: Work with process experts and stakeholders to validate that the abstractions accurately represent the underlying events and do not oversimplify to the point of losing critical information.

8. Iterative Refinement: Continuously refine the event abstractions as you gain more insights from the stakeholders or as the process evolves. This will help to maintain the balance between simplicity and accuracy.

9. Automate Abstraction: Use machine learning algorithms or process mining tools that can assist in the identification and abstraction of recurring patterns, making the process of event abstraction more efficient and scalable.

10. Document and Share Knowledge: Ensure that any abstracted models are well documented, and the rationale behind certain abstractions is clear. This documentation should be accessible to all process stakeholders to facilitate understanding and encourage collaborative model refinement.

By applying these strategies, organizations can develop process models that are easier to read and manage, thereby enhancing the ability to analyze, improve, and monitor business processes.