Skip Ribbon Commands
Skip to main content
Sign In
Data Challenge HS Osnabrueck
4/4/2024 |News

In search of the needle in the (data) haystack


In a nutshell:

  • ROSEN accompanies Big Data lecture in the Business Informatics degree programm at Osnabrück University of Applied Sciences
  • Data Challenge puts students' analytical skills to the test
  • 39 students accepted the challenge
  • Highlight for the students: Facility tour at our location in Lingen (Ems)
  • Successful presentation of the students results at the end of March


​In order to assess the condition of a pipeline or industrial plant, our inspection equipment collects a large amount of data during a run. This data, which can be characterized by its size, complexity and fast pace, is also known as big data. For this reason, big data methods are an important part of many development projects for evaluation and data management optimization at ROSEN.


Insights into working with big data


Together with Prof. Dr. Stefan Guericke, Chair of Business Informatics (Data Science and Business Intelligence) at Osnabrück University of Applied Sciences, our colleagues Enno Broering and Peter Bergmann have therefore developed a lecture cooperation to provide students with an understanding of how to deal with big data in practice. After all, in the context of a dual study program, the focus is particularly on the transfer of theory to practice. In order to give the students a particularly practical insight into the evaluation of big data, we therefore accompanied their lecture with a data challenge, which is also their central module final examination.


Challenge Accepted


After the kick-off in January, the students worked in small groups for around two months to process a data set of around two thousand individual files. In terms of content, these are based on statistics generated after MFL inspections. These are decisive for the assessment of the validity of inspection runs. Additional correlations and artefacts that are often difficult to recognize in practice have also been built into this artificial data. For example, individual data types or naming are not consistent, or some of the data is very noisy. These are all issues that we regularly encounter in our everyday work with big data.

The students' task was to recognize relevant correlations in the data provided and reconstruct them in the form of mathematical functions. In the end, the teams that mastered the data challenge were those who identified the correlation we created between magnetization and wall thickness of individual measuring devices and were able to quantify the influence of speed on the measurement results.

​In addition to two meetings to present interim results, we also used the contact with the students to introduce them to our work at ROSEN during a facility tour. For the students, this is a welcome change from the proverbial search for a needle in a (data) haystack. The tour in particular allowed the students to develop a vivid idea of our technologies, inspection devices and integrity services.


A fusion of theory and practice that inspires


For the final presentation of the results on March 26 at Campus Lingen, the students prepared project reports and presentations in which they presented their results in several stages. During the students' presentations, we were particularly impressed by the breadth and soundness of the original analytical approaches. At the end, not only Prof. Dr Guericke but also the students praised the integration of theory and practice realized through the Data Challenge. "Data literacy is a key skill for the future labor market. Thanks to the fantastic support from ROSEN during the project period, the students were able to learn the skills in a much more multifaceted way than would be possible in an exclusively theoretical context. The consistently positive feedback from the students shows that the project was very well received and I would be delighted to repeat it." Prof. Dr Guericke concluded.


Congratulations to all students who successfully participated in the Data Challenge! We are already looking forward to a repeat of the cooperation.


Return to Overview
ROSEN accompanies big data lecture at Osnabrück University of Applied Sciences with data challenge