Visual Analytics Meets Process Mining: Challenges and Opportunities

Abstract : Event data or traces of activities often exhibit unexpected behavior and complex relations. Thus, before and during the application of automated analysis methods, such as process mining algorithms, the analyst needs to investigate and understand the data at hand in order to decide which analysis methods might be appropriate. Visual analytics integrates the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers to form a powerful knowledge discovery environment. The combination of visual data exploration with process mining algorithms makes complex information structures more comprehensible and facilitates new insights. In this position paper I portray various concepts of interactive visual support for process mining, focusing on the challenges, but also the great opportunities for analyzing process data with visual analytics methods.
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Paolo Ceravolo; Stefanie Rinderle-Ma. 5th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA), Dec 2015, Vienna, Austria. Springer International Publishing, Lecture Notes in Business Information Processing, LNBIP-244, pp.142-154, 2017, Data-Driven Process Discovery and Analysis. 〈10.1007/978-3-319-53435-0_7〉
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Theresia Gschwandtner. Visual Analytics Meets Process Mining: Challenges and Opportunities. Paolo Ceravolo; Stefanie Rinderle-Ma. 5th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA), Dec 2015, Vienna, Austria. Springer International Publishing, Lecture Notes in Business Information Processing, LNBIP-244, pp.142-154, 2017, Data-Driven Process Discovery and Analysis. 〈10.1007/978-3-319-53435-0_7〉. 〈hal-01651890〉

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