2 Overview
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2.1 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.
2.2 Challenges and barriers in academia
Aside from the standard project management tasks, implementing modern research operations and collaborative practices that support conducting open and reproducible science across multiple institutions (such as all the Steno Centers in Denmark) will be a major challenge. From both the technical and cultural sides, these work tasks often lack support at the institutional level and lack of awareness and training at the personnel level. So usually work is done from the ground-up, which often results in unexpected issues.
Given that there are few personnel in research environments with the necessary technical knowledge and skills, and they often move from academia into industry positions, a substantial amount of time and effort must be spent in training and upskilling existing personnel. The reason we’ve structured the groups to include at least one “tech lead” who is also part of the technical working group is to help minimise this challenge. We aim to provide training to these tech leads by embedding them in some of the work we are doing at Steno Aarhus, where we have been implementing many of these practices.
Another major challenge will be coordinating tasks and work between IT systems that often don’t work well together or are suboptimally designed for cross-institution collaboration. This is one reason we’ve decided to establish the technical working group, so that we can minimise the impact these issues have on completing the project deliverables.
2.3 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.