Process modeling and discovery techniques aim to construct sound and valid process models for different types of processes, i.e., process orchestrations and collaboration processes. Orchestrations represent behavior of cases within one process. Collaboration processes represent behavior of collaborating cases within multiple process orchestrations that interact via collaboration concepts such as organizations, agents, objects, and services. The heterogeneity of collaboration concepts and types such as message exchange and resource sharing has led to different representations and discovery techniques for collaboration process models, but a standard model class is lacking. We propose collaboration Petri nets (cPN) to achieve comparability between techniques, to enable approach and property transfer, and to build a standardized collaboration mining pipeline similar to process mining. For cPN, we require desirable modeling power, decision power, modeling convenience, and relations to existing model classes. We show the representation of collaboration types, structural characterization as workflow nets, automatic verification of soundness, bisimulation equivalence to existing model classes, and application in a general discovery framework. As empirical evidence to discover cPN, we conduct a comparative evaluation between three discovery techniques on a set of existing collaboration event logs.

中文翻译：

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协作 Petri 网：验证、等价和发现（扩展版）

流程建模和发现技术旨在为不同类型的流程（即流程编排和协作流程）构建合理且有效的流程模型。编排代表一个流程中案例的行为。协作流程表示多个流程编排中协作案例的行为，这些流程编排通过协作概念（例如组织、代理、对象和服务）进行交互。协作概念和类型（例如消息交换和资源共享）的异构性导致了协作过程模型的不同表示和发现技术，但缺乏标准的模型类。我们提出协作 Petri 网（cPN）来实现技术之间的可比性，实现方法和属性转移，并构建类似于流程挖掘的标准化协作挖掘管道。对于 cPN，我们需要理想的建模能力、决策能力、建模便利性以及与现有模型类的关系。我们展示了协作类型的表示、工作流网络的结构表征、健全性的自动验证、与现有模型类的互模拟等价性以及在通用发现框架中的应用。作为发现 cPN 的经验证据，我们对一组现有协作事件日志的三种发现技术进行了比较评估。