Why is Data Management Important?

Practicing good data management principles can mean the difference between being using your information in the future and losing files or experiencing data corruption. Data management is an ongoing process that should be carried out through the entire research data lifecycle: planning, collecting, analyzing, archiving, sharing, reuse, and storage. 

A few ways to manage data though the entire lifecycle includes constructing a data management plan, clearly documenting metadata with READMEs and codebooks, as well as openly sharing your results with your publications. Executing these data management principles can help:

• Keep you organized
• Save time in the future
• Safeguard against catastrophic data loss
• Keep collaborators on the same page
• Provide evidence for research alongside your published results
• Find or interpret older research data
• Promote new discoveries and research by sharing
• Increase research impact with additional citations

Alongside the personal benefits for managing data, many funding agencies and the federal government (through the OPEN Government Data Act) have data management requirements. For example, National Institutes of Health awards post-2023 are required to align with the Data Management and Sharing Policy (DMSP). This means a researcher needs to create and implement a data management and sharing plan with every grant application, regardless of award amount.

Lewis Library provides consultation services to help you navigate available resources throughout the data lifecycle. Contact us or your Library Liaison to schedule an appointment.

This quick five-minute video reiterates the importance of good data management. It uses real-world examples of poor data storage, lack of metadata, and the impact of reusability.

The Research Process

Before You Begin

• Explore funding agency requirements for data and write your Data Management Plan (DMP).
  • FAIRsharing.org to find funder policies and DMPTool to create your DMP.
  • SPARC compiles a list of sharing requirements by federal funding agency.
• Consider Institutional Review Board (IRB) policies when contemplating sharing data on human subjects.
• Explore online tools to learn about the data life cycle and how to manage data.

During Your Research

• Consider and create the metadata you will need to provide along with your data so others can understand and reuse.
  • FAIRsharing.org lists standards and links to different databases.
• Learn about the basics of copyright and the Creative Commons copyright license.
• Select applications to store and back up your active data that offer flexibility, functionality, and access.
  • LabArchives is a digital lab notebook and is free for HSC researchers.

After Research Ends

• Share and publish your data with the appropriate data archive or repository.
• Learn how to cite datasets and ensure your data are cited correctly.