Research Data Management

Jump to other pages in this section

• NEW: Research Data Management Guide
• Documenting Your Work
• Managing Your Files
• Storage and Security
• Preserving Your Data
• Sharing and Reusing Your Data
• Research Data Management Policies

Data Management Planning

Planning how you will organize your data is a crucial step in the study procedure. The methods, protocols, and strategies you will use to manage, describe, store, analyse, preserve, and communicate the data obtained or generated throughout the course of your research project are described in a data management plan (DMP).

A sound and well-documented data management strategy improves project efficiencies and mitigates risks, including loss, corruption, or unintentional disclosure of data. Creating a data management plan helps you comply with current and future funding agency policies as well as with other legal, ethical, and legislative requirements while facilitating decision making around long-term preservation and access to your data when the project ends.

DMP Assistant is a national, bilingual, online data management planning tool developed by the Digital Research Alliance of Canada (the Alliance) in collaboration with University of Alberta and the Arbutus team at the University of Victoria to assist researchers in preparing data management plans (DMPs).

This checklist outlines the questions to consider for your data management plan:

Collecting Data 

• What types of data will be collected or produced?
• What consistent method will you use to collect and process data?
• If you are using mobile devices to collect data or are working remotely, how will you securely transfer the data?
• Have you documented your project methodology?

Documenting Your Work with Metadata 

• What tools or methods will you use to document your work?
• What recognized standards or taxonomies will be employed in describing your data?
• Have you documented your project methodology?
• Will project and data identifiers be assigned?

Managing Your Files 

• Have you established a consistent method to name your files?
• What directory structure will you create to organize your files?
• What formats will be used to save your data?
• How many people will have access to data during the project? Are they all aware of the chosen management procedures?

Storage

• Where will you store your data during the project? Will there be more than one location?
• How much storage space will you need?
• Where will you keep separate copies of your master files?
• How regularly will your working data files be backed up? Where will the backup version reside?
• Do you have personal or sensitive data which requires storage in a secure location?

Preservation 

• Where will you store your data once your project has ended? In an institutional or discipline-specific repository? What factors affect your decision?
• Are there legal or funding obligations concerning data preservation which must be adhered to?
• Will your files be saved in a non-proprietary format to ensure future access?
• How long will the data be retained?

Discovery, Sharing, and Reuse 

• Will informed consent to share data beyond the original research project be obtained from study participants?
• Will your data be accessible and discoverable to others?
• How and under what conditions will you share your data with others?
• Will your data require anonymization before sharing? If so, what methods will you use?
• Are there legal, ethical, or funding requirements prohibiting or limiting sharing your data with others? If so, what are they?