Engineers need to do better

This is a notable issue in research, but one for which there is progress, albeit gradually. The role of a Research Software Engineer (RSE) is becoming more common to support technical development in science and there is a growing body of practice aiming to improve the state of software. This practice includes both traditional development "best practice", as well as training of scientists and pushing for the software lifecycle to be included in grants and proposals. [1]

Software is an area where university based researchers often struggle more than their industry counterparts, largely due to the short term nature of university funding and contracts, and a focus on publication output for promotion, etc. Over the past few years a number of UK universities have established a central pool of RSEs, often employed on a permanent basis, to mitigate this.

However, while there is a lot of focus around reproducibility, especially in the context of FAIR [2], it does seem that a lot of the effort is going towards freezing all the dependencies and effectively reproducing the original environment, whether through conda environments, containers, or VMs. I guess it is the difference between single paper analytics, and creating a reusable analytics tool.

Software is more essential to science than ever before, so this is definitely an area to keep on improving.

[1]: J. Cohen, D. S. Katz, M. Barker, N. Chue Hong, R. Haines and C. Jay, "The Four Pillars of Research Software Engineering," in IEEE Software, vol. 38, no. 1, pp. 97-105, Jan.-Feb. 2021, https://doi.org/10.1109/MS.2020.2973362
[2]: Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18