Data analysis


Modern devices and systems generate increasingly complex data. In order to gain knowledge from this data, analyses have to be well-designed. As not all data can be automatically interpreted completely, complex data often needs to be pre-processed and prepared for the user. This helps the right conclusions to be drawn. Our team from the Department of Laboratory Automation and Biomanufacturing Engineering develops the appropriate data analysis solution for this - from data capture, through pre-processing and graphical representation, up to analysis and filing in the customer’s database system.

As a rule, several disciplines are involved if aspects of the task include planning, set-up, start-up and operation of an automated system in a research or production facility. A technician sees the system and the data generated by it from a different perspective than the laboratory worker operating the system, or the laboratory manager planning and assessing experiments. Therefore, one of the goals of our research work is to represent complex data and information as required by the user group concerned. This should enable users from different disciplines to collaborate with one another without first having to acquire in-depth knowledge of the other disciplines involved. What may sound trivial is in fact anything but easy because even the meaning of individual terms is often not standardized.


  • Data visualization
  • Automated data pre-processing
  • Automated data analysis
  • Development of algorithms
  • Data fusion