GUIDE TO RESEARCH DATA MANAGEMENT
This guide presents information on the effective management of data created through research — including creating a data management plan for grant or project proposals, preserving data after project completion and sharing data with other researchers.
Research data is any systematic collection of information that is used by researchers for analysis. Typical examples of data include:
Research data can also include video, sound, or text data, as long as it is used for systematic analysis. For example, a collection of video interviews use to gather and identify gesture and facial expressions in a study of emotional responses to stimuli would be considered research data.
All research data must be appropriately structured and documented in order for it to be used effectively for analysis. Additionally, any unique programs or models needed to analyze the data should also be preserved.
Protect your data from loss by maintaining good backups and documentation
Secure your data through effective management of sensitive data
Conduct research efficiently by analyzing your data practices
Simplify the use and reuse of your data through proper documentation and application of standards
Increase your research visibility by publishing your datasets and documentation
Meet funding agency, legal and ethical requirements for dissemination and documentation of your research
Preserve and provide access to your data in the long term, allowing future scholars to build on your work