Motivation
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Academia lags far behind industry in many practical ways
Science, while pursuing cutting edge knowledge, lags far behind industry in standard operational, organisational, and technological practices, tools, and methods. For example, there are nearly no research software or data engineers within research groups or institutions, even though software and data are foundational components to conducting research in the modern era.
Traditional management of larger scale research projects often involves setting up steering committees who check on progress through status updates and discuss solutions to issues that arise. However, there are many modern tools and methods used within industry that research environments and projects could benefit from, such as data engineering, software development, and operations management.
Likewise, basic modern communication and project management tools are rarely, if ever, used within research environments, even though they are standard practice in many corporate settings. If these things are used by some groups, they are not shared nor advertised through traditional scientific publications, so if they exist, others can’t reuse and learn from each other to improve how we do research.
Science needs more team-based, collaborative approaches
Science is also increasingly moving into more team-based, multi-centered enterprises, as well as having a greater requirement for openness and reproducibility. These require using modern practices designed for these conditions, rarely seen in academia but common within many industry settings.
Ultimately, academia needs to recognize and incorporate these practices in order to stay relevant and competitive in the modern research landscape. But we need more funds, support, awareness, and training to make this happen.
This is what Work Package 1 aims to help address.