Research Data Management

What is a DMP?

A Data Management Plan (DMP) is a formal, living document that details the strategies and tools you will implement to effectively manage your data during the active phase of research, and also the mechanisms which will be used for preserving and appropriately sharing data at the end of the project. [from Portage Network. (2020, August 25). Brief Guide - Data Management Plan. Zenodo.] 

If you’re applying for Research Ethics approval, the questions you will answer in your DMP will be one in the same. 

Even if you're not applying for a grant or research ethics approval, it is best practice to think through the questions in a DMP before starting a project. 

Reasons for making a DMP:

• Efficiency - identify both strategies and potential challenges in advance; develop sound data practices for you and your research team; prepare data for effective use during your project.  
• Research Quality - ensure reliability and accuracy of data through careful documentation of your data collection, handling and stewardship practices.  
• Reusability and Impact - Improve discoverability, accessibility, and reusability of your data by planning for sharing in a repository; which increases the potential impact of your research!  
• Compliance - Satisfy DMP requirements that may be set forth by specific granting agencies or even your own institution.  

Brief Guide - Create an Effective Data Management Plan

This brief guide presents a general framework for creating an effective data management plan (DMP) to help you plan and organize your research and to meet research funder requirements.

To prepare your DMP, visit the Portage DMP Assistant tool

Data Management Plan Template: Arts-Based Research

"This template will assist you in creating a data management plan for arts-based research (ABR). It is intended for researchers and artists who use artistic processes as research methods (i.e., arts-based methods). ABR is used across disciplines and encompasses diverse understandings of the arts, research, and how they intersect. In this template, ABR is an umbrella term for all the ways the arts are adapted to answer research questions, including those described as arts research, artistic research, and research-creation. You can use this template on its own, or in combination with others on the DMP Assistant when using arts-based methods with other methodological approaches." -- abstract

Lévesque, Michel, & Doiron, James. (2021). Data Management Plan Template: Arts-Based Research. Zenodo. https://doi.org/10.5281/zenodo.4571671

Data Management Plan Template: History and the Humanities

"This model was developed for researchers in history and in the larger field of humanities. It was designed to take into account the fact that research projects in these disciplines still primarily use analog research data during the active, phases of a project." -- abstract

Lisée, Cynthia, & Kelly, Benoît. (2021). Data Management Plan Template: History and the Humanities. Zenodo. https://doi.org/10.5281/zenodo.4684738

The basics of a DMP include the following (this is from the Portage Network Brief Guide to Creating an Effective Data Management Plan) 
For an ECU specific template, contact Hillary Webb.

Data collection:  

• Include descriptions of how you will collect data, including from where and in what format(s). 
• Provide an estimate of the amount of data you will collect (e.g., MBs/GBs/TBs). 
• Describe any software and/or platforms that will be used for data collection. 
• Clearly explain how you will both store and transfer data. 
• Explain how you will organize your data, including details relating both to file naming and versioning. 

Documentation:  

• Describe what information will be needed for others to understand or reuse your data. 
• Describe how you will consistently capture documentation throughout the project. 
• Choose a metadata standard suited to your discipline and/or chosen data repository or provide rationale for creating your own. 
  • Metadata: “A love note to the future” 

Storage and backup throughout the project 

• Provide an estimate of storage space needed during the active phases of your research - remember to take into account file versioning, backups, and data growth. 
• If needed, follow the 3-2-1 backup rule: 3 copies of your data, on 2 different storage media, with 1 located offsite. 
• State a data backup schedule, automatic being most ideal. 
• Describe how collaborators or research team will be able to access, modify, contribute, and work with your data. 

Data preservation strategy for long-term access 

• Not all data that you create necessarily needs to be preserved - consider such things as the value of your data, funding requirements, etc., and decide which, if any, should be preserved. Consult with experts in your Library as needed. 
• Consider optimal file formats (preferably non-proprietary) for supporting long-term preservation. 

Provisions for sharing and reuse 

• Consider the appropriate sharing of your data, including any funding, ethical and/or confidentiality requirements. 
• Explain what uses can be made of your data through licenses like Creative Commons. 
• Consult with colleagues or librarians to choose an appropriate data repository or search re3data.org to find one. 
• Choose a repository that assigns permanent identifiers to datasets (e.g., DOI) to enhance discoverability, accessibility, and citability.   
• If applicable, describe how you will ensure file integrity, anonymization and de-identification. 

Responsibilities and resources  

• Identify data stewardship roles and responsibilities of project members and other organizations during and after the project. 
• Estimate and describe any required resources and costs for data management and long-term access to your data. 
• Consider how to ensure that the data gets back to the community it came from 

Ethics and legal compliance 

• Describe if there are any legal, ethical, and intellectual property issues when managing and sharing your data. 
• Explain how you will comply with any applicable privacy legislation and laws, including funding and institutional requirements. 
• Describe how you will ensure your data are securely managed after the project is completed including the secure management of sensitive data and in accordance with any ethical obligations.