Research Data Management: Home

"Research data management (or RDM) is a term that describes the organization, storage, preservation, and sharing of data collected and used in a research project."

– University of Pittsburgh

The Merriam-Webster dictionary defines data as "factual information (such as measurements or statistics) used as a basis for reasoning, discussion, or calculation". Depending on the research, data can come in a variety of forms. You can think of data as anything created or collected during the research process that helps support your ideas and findings. Below are a few examples.

• Documents and spreadsheets
• Questionnaires, transcripts, codebooks
• Lab notebooks
• Health indicators (blood cell counts, vital signs, BMI, etc.)
• Survey responses
• Measurements generated by laboratory equipment
• Software code, software for simulation
• Images, videos, sound files

Data Sharing and Management Snafu in 3 Short Acts by Karen Hanson, Alisa Surkis & Karen Yacobucci. New York University Health Sciences Libraries

The video above shows why sharing and managing your data can be important. Here are some of the benefits for following best practices in research data management:

• Comply with funder and publisher data management and sharing requirements.
• Data can be understood by a wide audience.
• Open data can help accelerate scientific progress.
• Your data will less likely be lost, damaged, or destroyed.
• Having a data management plan will save you time and effort.
  • Researchers on the team will have clear expectations of their roles in the project's data lifecycle.
  • Less data duplication.
  • Quicker data discovery.

We thank Stephen Gabrielson for creating most of this helpful guide!

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