The approaches used in software development in an industry setting and a scientific environment are exhibit a number of fundamental differences. In the former industry setting modern team development tools and methods are used (version control, continuous integration, Scrum, ...) to develop software in teams with a focus on the final software product. In contrast, in the latter scientific environment a large fraction of scientific code is produced by individual scientists lacking thorough training in software development with a specific research goal in mind. Indeed, it is only in the last decades that scientific software development started to become a fully recognized part of scientific work. Still, formal training in software development is largely missing in the scientific curricula of many universities. Additionally, due to the exploratory nature of the scientific method at the frontier of knowledge, most projects require the implementation of custom code. The combination of these circumstances promotes the development of scientific code not suited for sharing and long term maintenance, limiting the reusability and reproducibility of scientific data and findings. The systematic development and adoption of open source packages by the scientific community can emend this situation. Here we present examplary open source packages from the field of neuroscience and discuss the special requirements for open source software development and services in this research area.
Acknowledgements: This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 785907 (Human Brain Project SGA2). Supported by the NFDI Neuroscience Initiative.
Speakers: Julia Sprenger