Top 5 Data Management Tips for Graduate Students


By Cameron Cook

Now that it’s the end of January, how are your new year’s data management resolutions going?

If you need some help with them, we have some tips for you as we head into the spring semester. Time to bust some bad data management habits!

As a graduate student, you are building skills you will need as an early career professional when you enter your chosen field. Good data management is one of those skills and a key piece of making your research stronger and more reproducible (as well as just ensuring that you will still have a copy of your data if your hard drive crashes!).

Another important thing to note is that data management goes beyond the sciences. Researchers in all disciplines benefit from proactively organizing, managing, and backing up your data. If you are in the humanities you may think that you are not producing ‘data’, but if you are producing any sort of digital files as outputs of your research or research objects, you’ll benefit from putting some data management practices into place.

1) Take a picture of that notebook

If you do work on pen and paper or keep a lab notebook, take a picture! Notebooks can be lost, forgotten and stored in a professor’s office, or spilled on. Think of taking a picture as backing up your physical notebook, you will have a copy if anything terrible were to happen to it.

2) No USBs

Remember the rule of 3 from our past post? 3-2-1? 3 copies of your data in 2 physically separate locations on more than one type of storage hardware.

Let’s add on to that. 3-2-1-0. 0 USBs used as a form of storage hardware. A USB is easy to lose, misplace, and drop – it happens all the time. A USB is simply not a good form of backup. You can explore options available to you on our resources page.

3) Create a system

In our last post we talked about being aware of open file formats and good file naming. Have you thought about what formats you want to save your files in? Have you thought about the steps of your process and what needs to be saved at each step (i.e. raw, processed, analyzed)? Are you consistently saving your files with meaningful names? Make sure you have a system and stick to it, so that you will not lose your work among an avalanche of files named “final” and “draft”.

4) Make a schedule

Do you have a schedule for backing up your files?  Form a plan and write it down! It may sound silly, but marking a backup date on your calendar or setting up an automatic back up process (just be sure to double check it regularly) ensure that you will have your data when you need it most.

5) Be smart about how you document your data

Plan ahead and your data will be more useful to you in the long run. Thinking about how you will be using and sharing your data can help you make decisions on how best to document it.

Is there a metadata schema or vocabulary common to your discipline? If so, are you using them?

Have you included how your data may be reused, shared, or cited?

If you use spreadsheets in your work, get to know the issues caused by poor data input. Data carpentry has great resources on the common mistakes in spreadsheets.