An essential element of scientific research is reproducibility of results. Modern science renders an increased complexity of measurement and analytical methods, which not necessarily, but often, lead to limited transparency, and selective reporting. Such situation promotes growing numbers of irreproducible data. On the contrary, distributed analyses environments, developed by researchers and set up in a bottom-up approach can forge a shared vision of data handling, reproducibility, and trust. The statistical programming environment R has already paved a way, facilitating developments of data-driven and open-source tools. Luminescence dating techniques are amongst the most important and flexible geochronological tools in Quaternary Science, constituting a cornerstone of the Earth and Archaeological Sciences. By using examples from the field of luminescence (dating), the presentation will shed light on the question “Why researchers develop software?”, and how R and the emerging field of Data Science may lead to better reproducibility of scientific results.
Invited by Christoph Schmidt, Geomorphology, as International Junior Research Fellow of the University of Bayreuth
|Th. 2018-06-21 now|
The tangled evolutionary history of plants and fungi
Öffentliche Vorträge im Rahmen der Besetzung der Professur "Sportökologie"
From the field to the lab to integrated risk assessment of vector-borne pathogens
Harmlos bis tödlich: Krankheiten der Bäume
GFBio Roadshow – Research Data Management for scientists, step by step (German Federation for Biological Data)