Supporting Domain Experts Understanding of Process Executions by means of Problem Solving Methods
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Provenance information can be seen as a pyramid with four main levels: Data, Organization, Process, and, on top of the pyramid, Knowledge. The first three levels are focused on how data is transformed ...
Provenance information can be seen as a pyramid with four main levels: Data, Organization, Process, and, on top of the pyramid, Knowledge. The first three levels are focused on how data is transformed across the execution of a process, what the roles of the actors involved are, and which tasks were comprised in it. However, the increasing complexity of distributed data-intensive applications that produce larger amounts of provenance information require more advanced analytical capabilities with a higher level of abstraction. In this regard, we approach knowledge provenance as the provenance perspective 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. Our approach towards knowledge provenance is based on Problem Solving Methods (PSM). PSMs have been traditionally 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 work, we use PSMs for a different purpose: we exploit their analytical power as high-level, domain-independent, knowledge templates to support user-focused interpretation of the execution of past processes. Our approach has been implemented as the Knowledge-Oriented Provenance Environment (KOPE) and evaluated through its participation in the Provenance Challenge.
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