top of page
chemzymes
chemistry with enzymes
Open Science
Science should be accessible to everyone.
Sadly, the current scientific landscape falls way short of that ideal. On many levels.
I do not have the answers to all the problems we are facing as a community but I am actively trying to make the way we communicate science more inclusive. Specifically, I am engaged in two areas:
Responsible use of color in scientific communication
Color is a powerful design feature. Color allows you to highlight elements of a figure or guide the reader's eye. Color is often also easier to recognize than shapes and makes it a lot easier to recognize recurring concepts. However, improper uses of color can introduce visual artefacts into data or make the information content of a given figure inaccessible to people with color vision deficiences. That concerns more people than one might intuitively think, as around 4% of the human population have some sort of color vision deficiency (protanomaly and deuteranomaly among males are the most common type of color vision deficiency, both of which make it harder or impossible to differentiate hues of green and red).
Thus, one needs to use color mindfully. Unfortunately, many authors of scientific publications or text books do not. In fact, around 70% of the literature published today contains figures that are at least partially inaccessible to people with color vision deficiences. Ironically, this problem is an easy one to fix. Most of the issue comes down to communication and education. To provide a concise reference material, Fabio Crameri and I wrote about design principles for inclusive figure design recently. I also try to lead by example as every paper we have published over the past few years uses scientific color maps which preserve the information in their figures for all readers (e.g. this, this and this paper use plasma, while this and this one use viridis and/or batlow). In addition, I bring up the issue at every (scientific) talk I give. Please do reach out, if you are interested in me talking about inclusive figure design at your institution.
Data sharing
Research generates hypotheses; Hypotheses require experimental interrogation; Experiments yield data; Data demand analysis and interpretation; That in turn leads to conclusions.
That is also (more or less) the way we report research findings in scientific papers. We describe hypotheses, experiments/methods, results and discuss conclusions. However, that approach ignores the data.
To address that shortcoming, data sharing should be the default when publishing scientific findings. For that reason, I am committed to open and transparent science. Each of my research papers (from 2019 on) is accompanied by a zenodo entry which contains all relevant raw data for that publication (see e.g. this, this or this entry). I try to be as upfront and transparent as possible and share all data (even anecdotal observations, see e.g. the really detailed SI for our paper on the PUB module or the archael ether synthases). We need to normalize sharing of raw data and I hope that my efforts make a small impact toward that.
bottom of page