Visual Analytics Meets Process Mining: Challenges and Opportunities

被引:0
|
作者
Miksch, Silvia [1 ]
Di Ciccio, Claudio [2 ]
Soffer, Pnina [3 ]
Weber, Barbara [4 ]
Rhyne, Theresa-Marie
机构
[1] Vienna Univ Technol, A-1040 Vienna, Austria
[2] Univ Utrecht, NL-3584 CC Utrecht, Netherlands
[3] Univ Haifa, IL-31905 Haifa, Israel
[4] Univ St Gallen, CH-9000 St Gallen, Switzerland
关键词
Process mining; Computers; Data analysis; Visual analytics; Knowledge discovery; Human in the loop; Cognition; Monitoring;
D O I
10.1109/MCG.2024.3456916
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Visual analytics (VA) 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. In other words, VA is the science of analytical reasoning facilitated by interactive interfaces, capturing the information discovery process while keeping humans in the loop. Process mining (PM) is a data-driven and process centric approach that aims to extract information and knowledge from event logs to discover, monitor, and improve processes in various application domains. The combination of interactive visual data analysis and exploration with PM algorithms can make complex information structures more comprehensible and facilitate new insights. Yet, this combination remains largely unexplored. In this article, we illustrate the concepts of VA and PM, how their combination can support the extraction of more insights from complex event data, and elaborate on the challenges and opportunities for analyzing process data with VA methods and enhancing VA methods using PM techniques.
引用
收藏
页码:132 / 141
页数:10
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