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Research Data Management Self-Assessment

A self-assessment and introductory guide to research data management for researchers

Saving Data

Saving Data

There is more to saving data than ensuring you have appropriate backups. How and where you save your data and other materials depends their size, format, and content as well as your intentions about making them available at the conclusion of your research project.

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.

Location

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.

Time

Saving data takes time, but losing data wastes 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.

Format

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. For example, if your data contains participant names or other personally identifying information, it will need to either be de-identified or stored in a secure system like Secure Box or RedCap.

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. For help identifying what solutions are right for your data, contact the LRDS team at LRDS@chapman.edu.