Exciting visit from experts: How data analytics can improve public transport

On 26.05.2023, at the invitation of Prof. Markus Lange-Hegermann, the inIT welcomed Mr Achim Oberwöhrmeier, Managing Director of Kommunale Verkehrsgesellschaft Lippe (KVG) mbH, and Dr Valentin Tenorth from Vindelici Advisors AG. The two experts presented current approaches to data analysis in the field of mobility.

Dr. Valentin Tenorth (l.) and Achim Oberwöhrmeier (r.) visiting the inIT on 26.05.2023

[Translate to Englisch:]

Dr Valentin Tenorth presents current approaches to data analysis in the field of mobility.

The day started with a captivating presentation on the importance of data in public transport. Participants gained valuable insights into the many possible applications of data analysis to make transport more sustainable and reduce CO2 emissions. In particular, the focus was on the presentation of typical data evaluations and the use of dashboards.

The topics of data preparation and the added value of data analysis for decision makers were also highly relevant. The students then had the unique opportunity to work with real data themselves and develop concrete suggestions for improvement of public transport in Lippe. The students' creativity and commitment were impressive and resulted in outstanding proposals.

The ensuing discussion allowed participants to share their ideas and benefit from Mr Oberwöhrmeier's experience and perspectives. The exchange was lively and inspiring, and exciting conversations arose about the current plans for public transport in Lippe. Prof. Markus Lange-Hegermann is enthusiastic about the event: "We are proud of our students, who participated in this course with great interest and enthusiasm. Their good suggestions and active contribution helped make this day an enriching experience for all involved."

We would like to express our sincere thanks to Mr Oberwöhrmeier and Dr Tenorth for their valuable contributions. Their expertise and commitment made this event a success and showed our students new perspectives for the concrete application of data analysis.