Best Practices with Research Data
To avoid potential ‘disasters’ with data, it’s very important to know how to manage it. One of the most important aspects of data management is data storage. Once the data is collected, it can be in physical or digital form.
A good idea is always to have a plan on how the data should be stored and protected, at least until the research project requires the data to be present. The following are six important data tips for avoiding data disasters:
1. Store your data securely
Store the data in a secure location or device to ensure parts – or all – of the data are not lost, accessed, or stolen by unauthorized users. Make secure data storage an official step in the research project. When I say ‘secure’, it relates to
2. Make your data less sensitive
The best way to make sure sensitive data is protected is to avoid having sensitive data in the first place. Make it more secure by replacing names with random IDs or initials.
3. Always back up your data
Always have a secure backup of your data. Backup data can be stored on a USB drive, the cloud, a CD (less used today but still used), scans, or physical printouts of the data. Backing up your data is the main protection against data loss; and losing data without some form of backup is one of the most frequent and avoidable mistakes researchers must deal with.
4. Keep track of where your data is stored
Keep track of where you store the data, whether it is stored physically or online. Data can be stored in many places, like USBs, personal computers, online on databases and repositories, the cloud, and more. Making sure to keep track of where that data is stored is essential, as many different types of data might be included in some projects; and it’s easy to forget the data locations.
5. Store your login details in a safe place
Make sure to store in a safe place any usernames, passwords, and other login information that protects your data . Databases, or even personal computers, often have login procedures, so forgetting the login details might cause the data to be inaccessible.
6. Keep all versions of your data
One of the most important mistakes to avoid: If newer or cleaner versions of your data are created, avoid overwriting the old files. Why? Older versions are very important references. Keeping them makes sure that we can always go back to previous versions and keep track of the additions/changes that were made. Also, your original “raw” data, the first version, contributes to the overall data integrity.
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