Business processes and their outcomes rely on data whose values are changed during process execution. When unexpected changes occur, e.g., due to last minute changes of circumstances, human errors, or corrections of detected errors in data values, this may have consequences for various parts of the process. This challenges the process participants to understand the full impact of the changes and decide on responses or corrective actions. To tackle this challenge, the paper suggests a semi-automated approach for data impact analysis. The approach entails a trans-formation of business process models to a relational database representation, to which querying is applied, in order to retrieve process elements that are related to a given data change. Specifically, the proposed method receives a data item (an attribute or an object) and information about the current state of process execution (in the form of a trace upon which an unexpected change has occurred). It analyzes the impact of the change in terms of activities, other data items, and gateways that are affected. When evaluating the usefulness of the approach through a case study, it was found that it has the potential to assist experienced process participants, especially when the consequences of the change are extensive, and its locus is in the middle of the process. The approach contributes both to practice with tool-supported guidance on how to handle unexpected data changes, and to research with a set of impact analysis primitives and queries.

中文翻译：

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业务流程中的数据影响分析

业务流程及其结果依赖于在流程执行期间其值发生变化的数据。当发生意外变化时，例如，由于环境的最后一分钟变化、人为错误或数据值中检测到的错误的更正，这可能对过程的各个部分产生影响。这要求流程参与者了解更改的全部影响并决定响应或纠正措施。为了应对这一挑战，本文提出了一种用于数据影响分析的半自动化方法。该方法需要将业务流程模型转换为应用查询的关系数据库表示，以便检索与给定数据更改相关的流程元素。具体来说，建议的方法接收一个数据项（一个属性或一个对象）和有关进程执行当前状态的信息（以发生意外变化的跟踪的形式）。它分析了变化对活动、其他数据项和受影响的网关的影响。在通过案例研究评估该方法的有效性时，发现它有可能帮助有经验的流程参与者，尤其是当更改的后果是广泛的，并且其位置在流程的中间时。该方法有助于通过工具支持的指导来练习如何处理意外数据更改，并有助于研究一组影响分析原语和查询。