| Abstract | This paper presents a discussion of the potential of Process Mining for the analysis of general processes involving the time variation of magnitudes given by real-valued variables. These scenarios are common in a broad variety of domains, like natural and life sciences, engineering, and many others beyond business processes, where, in general, complex systems are observed and monitored using sensor data, producing time-series information. Two approaches are presented to construct event logs for such types of problems and one of them is applied to a real-world case (monitoring the F10.7 cm electromagnetic flux produced by the Sun). The results obtained with the Fuzzy Miner and the Multi-Objective Evolutionary Tree Miner algorithms successfully exposed the differences in the internal structure of the F10.7 cm series between Solar cycles. For this application, Process Mining proved to be a valuable tool for analyzing the rhythm of solar activity and how it is changing. The approach introduces here is general and could be used in the analysis of data from a broad variety of time-dependent information from many domains. |
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