Problem-Solving Methods for Understanding Process Executions

Abstract

Provenance information can be seen as a pyramid with four main levels: data, organization, process, and knowledge. The first three levels focus on how data is transformed across a process's execution, the roles of the actors involved, and which tasks it comprises. However, the increasing complexity of the distributed, data-intensive applications that produce ever-larger amounts of provenance information require more advanced analytical capabilities with a higher level of abstraction. In this regard, the authors approach knowledge provenance as being focused on providing users with meaningful interpretations of process executions, explaining provenance in a way closer to how domain experts reason on a given problem, and facilitating their comprehension. Their approach is based on problem-solving methods (PSM), which are used in application development as generic and reusable strategies to model, establish, and control the sequence of actions required to accomplish tasks in different application domains. In this article, the authors describe how they use PSMs for a different purpose: to exploit their analytical power as high-level, domain-independent, knowledge templates and support user-focused interpretation of the execution of past processes.