Seminar on 'Event Log Visualisation with Conditional Partial Order Graphs: From Control Flow to Data'
Andrey Mokhov, lecturer in computer engineering at Newcastle University delivered a report on 'Event Log Visualisation with Conditional Partial Order Graphs' during a PAIS seminar.
Several notations and formalisms for event log representation have been proposed in the recent years to enable efficient algorithms for process mining problems. In this talk we show how Conditional Partial Order Graphs (CPOGs), a recently introduced formalism for compact representation of families of partial orders, can be used in the process mining field, in particular for addressing the problem of compact and easy-to-comprehend visualisation of event logs with data.
We present algorithms for extracting both the control flow as well as the relevant data parameters from a given event log and show how CPOGs can be used for efficient and effective visualisation of the obtained results. We demonstrate that the resulting representation can be used to reveal the hidden interplay between the control and data flows of a process, thereby opening way for new process mining techniques capable of exploiting this interplay.
About the speaker:
Andrey Mokhov's background is design of concurrent systems, in particular, asynchronous processors for energy-efficient and high-performance computing. He received his PhD degree from Newcastle University in 2009 for his work on a new formalism for succinct representation of concurrency and choice called Conditional Partial Order Graphs that has recently found a new application in process mining, which is the topic of his talk.