Slightly smaller-scale than most suggestions here, but for the average nonscientific HNer, the best way to help scientists is to improve their programming tools

Slightly smaller-scale than most suggestions here, but for the average nonscientific HNer, the best way to help scientists is to improve their programming tools. In the Python ecosystem, for instance; numpy/scipy, scikit-learn, and matplotlib are widely used across dozens of disciplines, and are open-source projects relatively welcoming of new contributors. Julia is a whole new language for scientific computing, where all the fundamental tools are still being built and refined. Raspberry pis, 3D printers and other “hobbyist maker” tools are appearing in research labs to help develop novel instrumentation, so hardware-oriented people can help by contributing to open-source efforts of that kind.