Managing Your Data

Data management makes it easier to organize, find, and use your research data. Good data habits also protect your data from loss and help you disprove allegations of fraud and misconduct. A little data management planning at the start of a project can save you a huge headache at the end of the project when you can’t find the information you need.

Good data management occurs through the summation of many small practices. This page describes some easy-to-implement best practices to improve the way you manage your research data. Try implementing one best practice every month and see how your data management improves!

Best Practices in File Organization and Naming

A file naming convention adds standardization to your files, making them easier to organize and find later. Your naming scheme can be personalized, but should follow these rules:

  • Files should be named consistently
  • Files names should be descriptive but short (<25 characters)
  • Use underscores instead of spaces
  • Avoid these characters: “ / \ : * ? ‘ < > [ ] & $
  • Date your files using the convention: YYYY-MM-DD
  • For analyzed data, use version numbers and save files often to a new version
  • Label the final version of a file FINAL

A file organization convention will also help you organize your files and find them later. There are several possible organizational systems to choose from:

  • One project, one folder (for small projects)
  • Separate folders for data or project stages
  • Separate folders for different types of data
  • Date-based folders, which pair well with a laboratory notebook

No matter your convention, be sure to document it with a README.txt file embedded in any and all relevant folders and in your research notes/laboratory notebooks.

Best Practices in Documentation

What would someone unfamiliar with your data need in order to find, evaluate, understand, and reuse them?

The answer to this question will determine how your document your data. Documentation not only helps others understand your data but it also helps you remember the context of your data when you need it in the future. There are two parts of documentation: methods and metadata.

Methods describe how the data were gathered and how the data should be interpreted. This type of documentation includes:

  • Code
  • Survey
  • Codebook
  • Data dictionary
  • Anything that lets someone reproduce your results

All of this information should be preserved alongside the necessary data.

Metadata provides information about a dataset, such as:

  • Creator
  • Contributor
  • Date
  • Title
  • Description
  • Identifier
  • Format
  • Language
  • Related information

Good metadata allows you to completely understand what a dataset is from the metadata alone. This information will help you locate a file without having to actually look at the data itself.

A formal metadata schema will help you document your data completely and consistently. There are many schemas available for many disciplines. To find one that works for your datasets, consult:

  • A disciplinary repository
  • Your peers
  • You subject librarian
  • The Data Services Librarian

If you know you will be depositing your data in a particular repository, identify their preferred metadata schema before you collect your data so you know what information to record.

Best Practices in Backup

The motto for storage and backup is: Lots of Copies Keeps Stuff Safe. At the very least, you should have 2 on-site copies and 1 off-site copy of your information.

The ideal backup system has the following qualities:

  • Automated
  • Reliable
  • As secure as necessary
  • As open as possible to collaborators
  • Well organized

Test your system by recovering from backup 1-2 times per year or whenever you make changes to the system.

Best Practices in Data Security

Keeping your data secure involves many different practices, such as:

  • Secure storage
  • Access permissions
  • De-identification of personal information
  • Security training

The UWM Information Security Office is the campus expert on keeping your private and confidential data safe. Contact them for a consultation.

Data Management Training

Data Services currently offers training in data management. Please contact the Data Services Librarian at for more information or to schedule a session.


Graduate School Information on Data Management
This site covers many aspects of creating a data management plan and addresses best practices for data management.
UWM Researcher Central
This site contains resources for writing grant proposals and conducting research at UWM.
UWM Information Security Office
Contact the Information Security Office for a consultation on securing sensitive or private data.


For more information about data management, please contact:

Kristin Briney
Data Services Librarian
(414) 229-6511