Guidelines

While other countries have already launched massive campaigns to promote and better connect communities at the interface between natural sciences and machine learning, the German government has also adopted a national strategy to promote the development of artificial intelligence and to support better networking of national research in autumn 2018. In order to achieve the following goals and to make Germany a leading location for the development of advanced and generally useful machine learning, we would like to start an initiative through which on the one hand scientists from different disciplines (biochemistry, chemistry, computer science, mathematics, pharmacy, etc.) can exchange ideas, and on the other hand strong and forward-looking research will be supported to achieve long-term effects. Therefore, all members of the SPP are embolden to publish program codes, data sets, method descriptions, complete analytical data and any experimental details in an easily comprehensible fashion as supporting information or in well-documented depositions on open access platforms such as Github or Zenodo.

The aim is to ensure full transparency and reproducibility by other research groups. We hope to encourage scientists to take up the topic presented and thus bring the academic community and the spirits of young scientists and students into a new digital age. In the best case, the know-how of participating groups should cover both the theoretical and the practical side of the planned project. This should encourage the formation of new and the strengthening of existing collaborations and will help to form ties between the two areas.

Due to academia’s and industry's high demand for scientists with knowledge in the field of data science and artificial intelligence, a change in the education of students must take place. In addition, this program will positively affect bachelor’s/master’s theses and teaching projects in the described area, making the currently underrepresented subject of cheminformatics, data science and AI part of the standard training for future chemists, medicinal chemists, and pharmacologists.