Recording Information Acquired by Interpreting Observational Data of Environmental Research Infrastructures (Example)

Interpreting observational data is a fundamental task in environmental and earth sciences. Nowadays, observational data are increasingly acquired, curated, and published systematically by environmental research infrastructures. Typically subject to substantial processing, observational data are used by scientists who interpret data for their meaning in the context of research investigations. The result of interpretation is information about the observed environment. For a use case in aerosol science, namely the study of atmospheric new particle formation events using polydisperse aerosol particle concentration data, we present a Jupyter Notebook implementation of a workflow that supports scientists in interpreting particle concentration data, and in recording and processing information about events.