Guide to Data: Manage Data
What is Data Management?
Data management is the process of controlling the information generated during a research project. Any research will require some level of data management, and funding agencies are increasingly requiring scholars to plan and execute good data management practices.
Data often have a longer lifespan than the research project that creates them. Researchers may continue to work on data after funding has ceased, follow-up projects may analyze or add to the data and data may be re-used by other researchers. Well organized, well documented, preserved and shared data are invaluable to advance scientific inquiry and to increase opportunities for learning and innovation.
Data Management Plans
Data management plans (DMP), defined broadly, are " documents that provide researchers with a mechanism for stating how they will manage data associated with at least part of a research project’s data lifecycle" (Smale et al., 2018). Many funding agencies now require DMPs, but even when not required, the library recommends researchers write one prior to research to aid in organization and re-use of data. A typical DMP might include sections for: Description and Format of Data, Metadata, Sharing and Reuse Policies, Data Storage, and other relevant information depending on the project.
How to write a DMP:
Check for any requirements or templates from your institution or funding agency
Use a resource like the DMP Tool, a free, open-source site to guide the process.
Use the Open Science Framework's DMP suggestions
Talk to your liaison librarian
Just for fun, read My Data Management Plan - a satire
Ethics
Your collection, reporting, storing, and sharing of data must be ethical and avoid harm.
Consider DataEthics' guidelines and questionnaire for ethical data or view Vallor and Rewak's Introduction to Data Ethics.
Naming and Documenting
It is important to have a documented naming convention for your data files. A naming convention makes it easy to organize and locate files. To create a naming convention, think about:
How will I want to find my files? By date, creator, project, or something else?
What are the three most important elements of the file that should be included in the name?
How can I document consistency--using lowercase or uppercase letters, underscores between words, etc.?
Use the checklists and worksheets below to draft your naming convention
CalTech Naming Convention Worksheet
OSF/Harvard Naming Convention Checklist
Similarly, you'll want to include a README file for your data. README files will outline why your data was collected, give full descriptions of all variables, and include any context or detail that would be helpful for someone reading or reusing data. Check out Cornell's README template for ideas.
Storage & Sharing
To store your data, choose file formats that are widely adopted, open, and accessible. The University of Illinois has a support matrix to help visualize choices.
Check with your institution or funding agency for repositories or look into the open repositories listed on the Find Data page.
- Last Updated: Apr 17, 2024 1:21 PM
- URL: https://libguides.gvsu.edu/dataguide
