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Collect, manage, and analyze data

Need assistance with data collection or management?

Ideally, plans for data collection, management, and analysis should be developed during the planning phase of a project. Once a project is underway, it is more difficult to create or change data management plans while ensuring scientific aims are met and findings are reusable and reproducible.

The "Related Resources" on this page contain specific policies, tools, and training options that may be helpful in guiding the data needs of a project once it is already underway. This page also provides guidance for determining data collection methods, management and storage solutions, and developing analysis plans if revision is needed on any of those aspects of a project.


Data collection

Data collection strategies should be based upon what data outputs are essential for the aims of a project, and what appropriate and approved methods are needed to obtain that data. Access the Develop the data management plan page for best practices and considerations for research methods to help think through specific data collection needs.

  • If specific policies or guidance around data collection methods are needed, the "Related Resources" on this page should be used.
  • If further assistance with data collection methods or operational needs of a project are required, the Plan the project or methodology page should be used to explore which consultative services best fit the project needs.


Data Management

The classification and size of data being collected or obtained will determine the options available for appropriate data management and storage solutions. Refer to the Duke services and data classification guide to determine appropriate storage options or cloud solutions based on the classification of the project data. 

The Develop the data management plan page and the Determine compute and data storage solutions page provide best practices and considerations for determining the appropriate data storage, organization, and documentation for projects.


Data Analysis

Utilizing appropriate data analysis methods, with data that have been cleaned and vetted for quality assurance, are critical to ensuring results are accurately interpreted.