In academic data management I have identified what I suspect is a common progression over the course of a career. Obliviousness to the problem. Rage at the inad

In academic data management I have identified what I suspect is a common progression over the course of a career. Obliviousness to the problem. Rage at the inadequacy. Search for alternatives. Realization that you do not have the resources to build and maintain something else, much less train all the labs to use it. Further realization that it is harder to explain how to set the right file encoding and the fact that a csv file is not a colon separated file to hundreds of labs than to just accept xlsx. Acceptance that Excel is a more reasonable user interface for data deposition than anything you could come up with. It is sad, but at the end of the day, however bad Excel is for life sciences data (to the point where standards bodies renamed genes due to autoformat issues!?), it ends up being better when usability and bad data edge cases are considered. Defaults matter for non-technical users, and even asking them to change the format they save in to csv is likely to cause issues because it is one more manual step that can go wrong, or there is some locale nonsense that will cause something to break etc.