Lab members are typically in charge of their own data and notes. But institutional memory is better served if the team works together, say Stephen McInturff and Victor Adenis.

During the 2020 COVID-19 shutdown, one of us (S.M.), a graduate student at the time, was asked to write a short manuscript using a previous laboratory member’s unpublished data. Thinking it would be a quick and easy pandemic project that would lead to a publication and a chapter in his dissertation, he happily took on the project. But the happiness didn’t last.

After weeks of trudging through poorly documented programming codes and data files, S.M. realized that much of the raw data he needed were missing. V.A., a postdoc in the lab, was recruited to help with the project. Together, we were ultimately able to locate some of the lost data, but they were spread across two other hard drives, saved using file names that were inconsistent with the original data set. We spent the following year repeating experiments, but some data could not be re-collected, because the animal models used in the original project were long gone. Two years later, the paper remains unpublished and has no clear narrative because of inconsistencies and gaps in the data. Sadly, such stories of data loss seem common in academia.

As longer-term lab members who have borne and continue to bear the brunt of continuing older projects, we think these problems arise from a misplaced assignment of responsibility. Academia heaps most of the burden of documentation and data storage onto individuals, instead of the lab as a whole. At the same time, little, if any, instruction is provided to teach individuals how to properly document and store their data. But labs can mitigate data loss by implementing three simple suggestions.