File organization and naming conventions are often unique to the lab and can be highly personalized; the important thing is to be consistent and to write them down. Spending a little time on file management strategies early in the project planning process can save lots of time (and headaches) later. After determining conventions for file naming and organization, document and share them with collaborators, faculty advisors, or anyone else who may need access to the data. Lab groups should establish a convention for the lab and save it to a shared space so that everyone can follow the same conventions.
For example: DryValleySoil_ICPOES_20101115_JDS.dat
DryValleySoil is the project name, ICPOES is the instrument from which the data originated, 20101115 is the date of the sample run on the instrument, and JDS are the initials of Jane Doe Scientist.
It is important to keep track of versions when working with data. There are many benefits, most importantly the ability to revert data to an earlier version instead of starting from scratch or worse, having to regenerate data. There are three basic ways to keep track of versions.
Some tools, like Electronic Lab Notebooks (ELN) or Box assign version numbers, and that is one option for managing versions of data. Other options include using a naming scheme or version control software. Some best practices for working with versions include:
Do not rely on directory structure to provide critical information about the file contents. Directory top-level folders should include the project title, unique identifier, and date (year), but the files themselves should be well-described independent of the directory structure. Consider creating a brief description of the contents of major folders and providing an overview of the directory structure. This can be a text document or readme file that is stored in a top-level folder or shared space. The level of detail to strive for is enough to help someone else understand the contents and organization of your files in your absence.
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Portions of this guide are adapted from the Cornell University Research Data Management Services Group website under a Creative Commons Attribution 4.0 International License.