Saving and Backing Up Data

A plan detailing how you’ll manage your data, code, and other research materials (including documentation, code, and physical samples) over the course of a project will help your research proceed efficiently. Creating a comprehensive, specific, and instructive plan for your data is an important step in developing a new research project, but the best plans also evolve as a project proceeds.


I decide what data is important while I am working on it and typically save it in a single location.


I know what data needs to be saved and I back it up after I’m done working on it to reduce the risk of loss.


I have a system for regularly saving important data while I am working on it. I have multiple backups.


I save my data in a manner and location designed to maximize opportunities for re-use by myself and others.


What does it mean to save data?

Saving data means storing research materials so that they can be accessed and used – by yourself or by others – at a later date. Here are three factors to consider when saving your data.


When possible, save multiple copies of your data across a variety of storage mediums. Hard drives, cloud storage, and other options have different levels of reliability, but all will eventually fail or become obsolete.


Saving data takes time, but losing data wastes more time. Backing up data should be a regular part of your research practice and you should also have a plan for how data will be saved after your research is concluded.


Data should be saved in a format that enables later use. This may involve saving data in open or easily accessible file formats, or simply storing your data alongside the documentation and other research materials needed to make use of it.

Requirements and how to meet them

There are specific requirements about how and where data containing sensitive or personally identifying information can be saved. How you deal with sensitive data will depend on a number of factors including the size and contents of your data as well as the resources available to you.

Things to think about

  • The characteristics of your data determine how much flexibility you will have about how and where it can be saved. If you have large quantities of data or data containing sensitive information, it can be challenging to move it from one medium to another.
  • Saving data should also involve saving research materials (e.g. documentation, code, etc.) needed to make sense of or use that data.
  • There may be a difference between where and how you save your data as you work on it and where and how you save your data over the longer term. Consider the difference between regularly backing up your data and archiving it at the end of a project.