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.
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Project title:
Guidance-Enriched Visual Analytics for Temporal Data: ICT19-47 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds) SANE: Visual Analytics für Ereignisdiffusion in Netzwerken: I 6635-N (FWF - Österr. Wissenschaftsfonds) Visuelle Analytik und Computer Vision treffen auf kulturelles Erbe: DFH 37-N (FWF - Österr. Wissenschaftsfonds)
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Research Areas:
Visual Computing and Human-Centered Technology: 100%