We discuss protoforms that are designed to capture process specific information. Linguistic summaries can capture information on the tasks or sequences of tasks that are frequently executed as well as properties of these tasks or sequences, such as their throughput and service time. Such information is of specific interest in the context of process analysis and diagnosis. Through a case study with a data from practice, we show that the knowledge derived from these linguistic summaries is useful for identifying problems in processes and establishing best practices.

**Bio**

Anna Wilbik received her Ph.D degree in computer science from the Systems Research Institute, Polish Academy of Science, Warsaw, Poland in 2010. She is currently an Assistant Professor at School of Industrial Engineering, Eindhoven University of Technology, The Netherlands. In 2011 she was a Post-doctoral Fellow at Electrical and Computer Engineering Department, University of Missouri, Columbia, MO, USA. In 2012 she participated in TOP 500 Innovators: Science - Management – Commercialization Program of the Polish Ministry of Science and Higher Education. Her research interests include linguistic summaries, data analysis, machine learning, and computational intelligence with a focus on applications in healthcare.

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