The discipline of process mining aims to study processes in a data-driven manner by analyzing historical process executions, often employing Petri nets. Event data, extracted from information systems (e.g. SAP), serve as the starting point for process mining. Recently, novel types of event data have gathered interest among the process mining community, including uncertain event data. Uncertain events, process traces and logs contain attributes that are characterized by quantified imprecisions, e.g., a set of possible attribute values. The PROVED tool helps to explore, navigate and analyze such uncertain event data by abstracting the uncertain information using behavior graphs and nets, which have Petri nets semantics. Based on these constructs, the tool enables discovery and conformance checking.

翻译：过程采矿的学科旨在以数据驱动的方式研究过程,方法是分析往往使用Petrinet的历史性过程处决过程,从信息系统(例如SAP)中提取的事件数据作为过程采矿的起点;最近,新类型的事件数据在过程采矿界中引起了兴趣,包括不确定事件数据;不确定的事件、过程痕迹和日志含有量化不精确的特点,例如一套可能的属性值;PROVED工具利用具有Petrinet 结构的动作图和网抽取不确定的信息,帮助探索、浏览和分析这种不确定的事件数据;根据这些构思,该工具有助于发现和检查符合性。