Consider that someone reviewing your data may not be able to piece together the generation/manipulation process without a step-by-step description. Just as published findings have a Methods section, so should a data deposit have a "methods file," especially if the data are attached to findings. These details are often collected in a plain text file named README.

IT-environmental details are also important for replicating in the setting in which you performed your work. It could well be that running the same code on a (much) newer version of the same software produces a different result (let's hope not one that invalidates your findings).

Here are examples of information elements to consider including:

• Study protocol(s), especially for wet lab work: what was your experimental design, and what were the individual steps and quantities?
• Instruments used, if any, including brand and model names
• Names and version numbers of software/packages used for processing and analysis (e.g., "pandas 2.0.3 in Python 3.11.4")

💡 Research tip: the software/packages you use for processing and analysis, such as the pandas example given above, should also be cited in your posters and manuscripts!