PAIS Lab Seminar: Towards a Process Scientist: Dealing with Big Data and Processes in a Comprehensive Manner // prof. W. van der Aalst
At the PAIS Lab seminar session the ademic supervisor of the PAIS Lab, professor of the Eindhoven University of Technology (TU/e) Wil van der Aalst presented the talk on the emerging field of study: process science.June 9th, 2014 - 18:30 - Kirpichnaya 33, aud. 902
Towards a Process Scientist:
Dealing with Big Data and Processes in a Comprehensive Manner
The term "Big Data" has reached the board rooms of larger organizations and there is a huge demand for "Data Scientists". Although the term "Big Data" is at the top of the hype cycle, it is clear that data science is an emerging and important discipline. Just like computer science emerged from mathematics, data science is emerging from statistics, databases, machine learning, and social sciences.
However, processes should not be neglected: we need to educate "Process Scientists" that can convert data analytics into process improvements and innovations. Process mining will play an important role in this. In his talk prof. Wil van der Aalst will discuss the importance of data science and the role of process mining in it.
Moreover, he will focus on the input side of process mining: event data. What are typical problems when extracting event data? Not just data quality problems, but also conceptual data conversion problems. The aim is to start a discussion on "Guidelines for Logging" (GoL) as a complement to the Guidelines of Modeling (GoM) framework and the Seven Process Modeling Guidelines (7PMG).
Slides: WvdAalst-HSE-Guidelines-for-Logging-June2014.pdf
.JPG "Prof. I.A.Lomazova introducing prof. Wil van der Aalst")
.JPG "Lecture of prof. Wil van der Aalst")
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However, processes should not be neglected: we need to educate "Process Scientists" that can convert data analytics into process improvements and innovations. Process mining will play an important role in this. In his talk prof. Wil van der Aalst will discuss the importance of data science and the role of process mining in it.
Moreover, he will focus on the input side of process mining: event data. What are typical problems when extracting event data? Not just data quality problems, but also conceptual data conversion problems. The aim is to start a discussion on "Guidelines for Logging" (GoL) as a complement to the Guidelines of Modeling (GoM) framework and the Seven Process Modeling Guidelines (7PMG).
Slides: WvdAalst-HSE-Guidelines-for-Logging-June2014.pdf
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