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Research Data Management at Ambrose

What is data management planning?

Data management planning starts at the conception of a research project and is an ongoing process. It involves creating a data management plan (DMP) which describes the data that will be acquired or generated, and outlines how this data will be handled, stored, and preserved throughout the course of a research project and beyond. Creating a DMP compels researchers to articulate their plans for managing data, ensuring proper handling throughout the research data lifecyle. Engaging with this process does not necessarily compel researchers to manage data differently, and a DMP can be modified as needed to reflect any changes in a research project.

DMPs enable researchers to anticipate and identify opportunities and challenges in managing their data, before those opportunities and challenges emerge. DMPs, therefore, enable researchers to better adapt their projects to unanticipated obstacles, and to integrate necessary adaptations and improvements. DMPs can also be an excellent way to engage partners and collaborators in ongoing conversation about how to best manage research data. Thus, DMPs improve the design and efficiency of the research project, and are an important tool to ensure research excellence. A DMP also impacts a research project's efficiency, quality, and reusability, and can help satisfy institutional and funding agency criteria.

DMPs do not set standards for what constitutes acceptable research data management practice (e.g., metadata standards, disciplinary expectations about data sharing, etc.). However, by documenting how researchers plan to manage research data, DMPs do allow for a level of internal and external review, and could compel adherence to a certain institutional or disciplinary standard.

Information taken from Tri-Agency Data Management Policy FAQ and Portage Network

What does a data management plan look like?

Data management plans may differ according to discipline and nature of the research, however they typically include the following sections:

  • Data collection: identify file formats, naming conventions, and data organization
  • Documentation and metadata: ensure data can be read and interpreted by using metadata (information that describes the data according to community best practices)
  • Storage and backup: address data security, integrity and appropriate access
  • Preservation: strategy for long-term access to data
  • Sharing and reuse: contributes to the visibility and impact of research while balancing privacy concerns for sensitive data
  • Responsibilities and resources: focus on who and what is in place for responsible data stewardship
  • Ethical and legal compliance: strategies for dealing with sensitive data and ethical/legal concerns

Information taken from the Portage Network

How do I create a data management plan?

There are many tools and templates available to help draft a data management plan (DMP). Researchers at Ambrose are encouraged to use the Portage Network’s DMP Assistant, which is supported by the Digital Research Alliance of Canada.

DMP Assistant is a free web-based tool for creating DMPs. It offers generic and discipline-specific templates which include embedded questions and instructions to guide the process. Training modules are available as well as exemplars. Completed DMPs can be exported for use in grant applications.

Sign up for a free account to access the full range of Portage Network's DMP Assistant tools.