Versioning is the practice of naming and saving the various versions of your files, so that earlier versions of your work are accessible later on. Save each version as a separate file with a unique name and somehow indicate the version number (e.g., v2 at the end of the file name). And be sure to document any changes made - some data collection tools will do this for you automatically.
It is best to use non-cryptic, intuitive names whenever possible - so DataValidation rather than DatVal or DV. Remember that what may seem like a clear shorthand at the time of an experiment, may seem less so when you look back at files at some future date.
File names should also be extensible. If you plan ahead as to how many files there will be, you can choose the number of digits in any filename element for which you are cycling through numbers, so that they will sort properly.
Finally, if you use consistent, documentable names, it will be easy to parse what is in each file, and easier for others to decipher. In this example, the file name contains the experiment type, experiment number, sample number, stain, coordinates of image, and stage of data processing.
AtherRat = experiment name
012 = experiment number
056 = sample number
mb = stain used, methylene blue
0423 = 2-digit coordinates of image (4 across, 23 down)
It is crucial throughout your research process that you track and document where your data will be stored at different stages. Plan this out ahead of time so you always know what data is located where. NOTE: Be sure to check cloud storage ownership policies; you want to avoid storing data on a cloud server that can claim ownership of your data.
Some data storage best practices include:
Electronic lab notebooks (ELNs) are another tool to consider using for proper data documentation. For help choosing an ELN that works best for your project, check out this article published in Nature (August 2018) as well as some of the resources below.