Development and dissemination of Python packages for FAIR Data Acquisition

The generation of FAIR (Findable, Accessible, Interoperable & Reusable) data in experimental research is best supported by ensuring that the process of data acquisition is systematic and transparent, and the control and calibration of experiments is systematic and reproducible. This project aims to contribute to improving, expanding and disseminating (including training and threshold-lowering measures) a modular Python-based open-source software for data acquisition and experiment control which has emerged from a community of optics researchers, but can easily find a much wider user base eventually.