Methods and tools for data-driven science in applied plasma physics

With the rapid emergence of data in applied plasma physics, such as plasma medicine and plasma agriculture, there is a need for the development of robust, reliable and reproducible analysis methods. Then, it is advisable that the analysis interacts with existing data stored in databases from different disciplines, with parameters set by the experimenter and with additional data containing information about mathematical models that can then be used for predictive methods in the future. Although plasma medicine has adapted methods from numerous fields, processing the data remains a challenge due to different, non-standardised data formats and differing needs throughout the various hypotheses. In the topical field of plasma agriculture, the need for elaborated data workflows has just been recognised and work is underway to standardise data collection and documentation and to integrate external databases into the research processes. We present an approach to data analysis based on uniformly annotated research data using electronic laboratory notebooks. It includes the KNIME Analytics Platform as well as the R programming language for automated data processing. This approach can also be applied in other application areas and similarly realised with alternative tools.