Data Management & Sharing

A Data Management and Sharing Plan (DMS Plan) is a critical document that outlines how research data will be managed, shared, and preserved during and after a research project. It specifies strategies for data collection, organization, storage, sharing, and long-term preservation to ensure compliance with funding requirements and support research transparency and accessibility. Most funding agencies now require a DMS Plan as part of the grant application process, making it essential for research compliance. Without a strong DMS Plan, researchers risk losing funding opportunities or failing to meet the expectations of funders such as the National Science Foundation (NSF), National Institutes of Health (NIH), National Endowment for the Humanities (NEH), the Institute of Museum and Library Services (IMLS), and the Department of Energy (DOE).

At Sacramento State, researchers can leverage the DMPTool, a free, online platform offering templates and guidance tailored to meet funder requirements. The Sacramento State Library also provides a review service to ensure that DMS Plans are thorough, compliant, and aligned with best practices for ethical and sustainable research data practices.

When developing a DMS Plan, consider strategies to promote inclusivity and avoid bias during data collection and management. Researchers should adopt culturally sensitive, representative data collection methods and design workflows that minimize systematic errors. This includes employing inclusive sampling techniques, ensuring transparent documentation, and adhering to ethical data-sharing practices.

By using the DMPTool and the library's expert review services, researchers can create DMS Plans that not only meet grant requirements but also enhance the integrity, accessibility, and long-term usability of their research data. This approach fosters collaboration, maximizes the impact of research, and ensures compliance with evolving expectations for data stewardship and sharing.

Data Types and Collection Methods
Description of the types of data collected or generated (e.g., qualitative, quantitative, experimental, observational)
Methods for data collection or generation

Documentation and Metadata
How data will be described and documented
Metadata standards used to make data understandable and searchable

Data Storage and Security
Plans for data storage during the project (e.g., institutional storage, cloud storage)
Security measures to protect sensitive or confidential data

Data Sharing and Access
When and how data will be shared
Licensing or restrictions on data sharing (e.g., ethical, legal, or commercial constraints)
Data repositories where data will be deposited

Data Preservation
Long-term preservation plans, including the formats and repositories for data storage
Duration for which data will be preserved

Responsibilities and Resources
Designation of roles and responsibilities for data management within the research team
Resources and support (e.g., funding for data management, software, tools)

Typical Length of a DMP:
1 to 2 pages
Short and concise, focusing on key aspects of data management relevant to the project and funder requirements.